Knowledge Collaboration by Mining Software Repositories
MIS简答题解读
MIS 简答题Chapter1SHORT-ANSWER QUESTIONS (p. 33)1.What is the relationship between management information systems (MIS)and information technology (IT)?ANSWER: MIS is a broad business function and the study of the use of IT. ITis a set of tools and a resource within MIS.2.What four steps should an organization follow in determining whichtechnologies to use?ANSWER: The four steps are: (1) assess the state of competition and industrypressures, (2) determine business strategies, (3) identify important businessprocesses, and (4) align technology tools with the business processes.3.What is the relationship between data, information, business intelligence (BI),and knowledge?ANSWER: Each build on the previous. Data are raw facts, while information isdata that has meaning. Business intelligence is collective information thatgives you the ability to make strategic business decisions. Finally, knowledge isa broad term that can encompass BI context, how to affect BI, patents andtrademarks, and organizational know-how.4.How does the granularity of information change as it moves from lower toupper organizational levels?ANSWER: At the lowest levels, information granularity is very fine becausepeople need tremendous detail to perform their jobs. As information moves upthrough the organization, it becomes more coarse because people don’ t need as much detail but rather aggregations of information.5.What is the difference between a technology-literate knowledge worker andan information-literate knowledge worker?ANSWER: A technology-literate knowledge worker knows how and when toapply technology; that is, he/she understands the value and role of technology.An information-literate knowledge worker knows all about information; thatis, he/she understands the value and role of information.6.How do ethics differ from laws?ANSWER: Laws either clearly require or prohibit an action. Ethics are moresubjective, more a matter of personal or cultural interpretation.17.What role does the Five Forces Model play?ANSWER:Porter ’Five s Forces Model helps business people understand therelative attractiveness of an industry and the industry’ s competitive pressures i terms of buyer power, supplier power, threat of substitute products or services,threat of new entrants, and rivalry among existing competitors.8.Why are competitive advantages never permanent?ANSWER:Once an organization creates a competitive advantage, allcompetitors move to offer similar or even better competitive advantages,thus nullifying the competitive advantage of the first organization.9.What are the three generic strategies according to Michael Porter?ANSWER: The three generic strategies according to Michael Porter are:overall cost leadership, differentiation, and focus.10.How are Porter ’ s three generic strategies, an-theabove-line versusa below-the-line approach, and the RGT framework similar?ANSWER: They are similar as follows: (1) run = overall cost leadership =bottom line, (2) grow = focus and differentiation = top line, and (3) transform =(new) differentiation = top line (when the focus is innovation).11.What is the role of value-chain analysis?ANSWER: Value-chain analysis is a systematic approach to assessing andimproving the value of business processes within your organization to furtherincrease it competitive strengths. So, value-chain analysis helps you identifyimportant business processes and how technology might help support them.Chapter2SHORT-ANSWER QUESTIONS (p. 59)1.Why is the traditional buy-hold-sell inventory model an expensive andpotentially risky one?ANSWER: The traditional inventory model requires that (1) you createinventory without a known demand, (2) you keep a lot of inventory throughoutthe supply chain, and (3) you sell off obsolete inventory at a very low price.2.What is the role of a supply chain management (SCM) system? ANSWER:The role of a supply chain management (SCM) system isto support supplychain management activities by automating the tracking of inventory andinformation among business processes and across companies.23.How does SCM fit into Porter’ s three generic strategies?ANSWER:SCM is most commonly associated with the overall cost leadership generic strategy.4.What are the typical functions in a CRM system?ANSWER:The typical functions in a CRM system include sales forceautomation, customer service and support, and marketing campaign management and analysis.5.How does CRM fit into the RGT framework?ANSWER:CRM is most commonly associated with growing the organization in the RGT framework.6.What is the difference between front office and back office systems? ANSWER:A front office system is the primary interface to a customer and asales channel, while a back office system is used to fulfill and supportcustomer orders.7.For what five things does e-collaboration provide support?ANSWER: E-collaboration supports (1) work activities within integratedcollaboration environments, (2) knowledge management with knowledgemanagement systems, (3) social networking with social networking systems, (4) learning with e-learning tools, and (5) informal collaboration to support open-source information.8.What is the difference between a social networking site and a socialnetworking system?ANSWER: A social networking site(e.g., Myspace) is a site on which youpost information about yourself, create a network of friends, share content, and so on. A social networking system is an IT system that links you to people you know and, from there, to people your contacts know.9.What is open-source information?ANSWER: Open-source information is content that is publicly available (in a broad sense), free of charge, and most often updateable by anyone.10.What are the three most common ways in which the IT function can beplaced within an organization?ANSWER: The three most common ways in which the IT functions can beplaced are: top-down silo, matrix, and fully integrated.311.How are the structuring of the IT function and the philosophical approach toIT interrelated?ANSWER: They are interrelated in that the philosophical approach is mostoften implemented as a specific structure. Wait-and-see organizations tend to centralize the IT function in a top-down silo approach, while early IT adopters tend to disperse the IT function (i.e., either matrix or fully integrated).12.What is an enterprise resource planning (ERP) system?ANSWER: An ERP system is a collection of integrated software for businessmanagement, accounting, finance, HR, project and inventory management,supply chain, customer relationship management, e-collaboration, etc. Chapter3SHORT-ANSWER QUESTIONS (p. 90)1. What is business intelligence? Why it is more than just information?ANSWER: Business intelligence is knowledge–knowledge about your customers, your competitors, your partners, your competitive environment, and your own internal operations. It is more than just information because it combines various types of information to allow you to make better decisions and operate more productively.2.What is online transaction processing (OLTP)?ANSWER: OLTP is the gathering of input information, processing that information, and updating existing information to reflect the gathered and processed information.3.What is online analytical processing (OLAP)?ANSWER: Online analytical processing (OLAP) is the manipulation of information to support decision making. It differs from OLTP in that it does not process transactions but rather manipulates existing information to support the making of a decision.4.What is the most popular database model?ANSWER:The most popular database model is the relational database model.5.How are primary and foreign keys different?ANSWER: A primary key is a field that uniquely identifies a record in a relation of a database while a foreign key is a primary key of one file that appears in another file. So, primary keys must be unique in a given relation while4foreign keys do not have to be. They are the same in that both are used toenforce integrity constraints.6.What are the five software components of a database management system?ANSWER: The five important software components of a DBMS are (1)DBMS engine, (2) data definition subsystem, (3) data manipulation subsystem, (4)application generation subsystem, and (5) data administration subsystem.7.How are QBE tools and SQL similar? How are they different?ANSWER: QBE tools and SQL are similar in that they both give you the ability to create queries to find information in a database. They are different in that QBE tools provide a GUI interface while SQL requires that you create your query in statement form.8. What is a data warehouse? How does it differ from a database?ANSWER: The four types of information according to what informationdescribes are internal, external, objective, and subjective.9.What are the four major types of data-mining tools?ANSWER: The four major types of data mining tools are intelligent agents,query-and-reporting tools, multidimensional analysis tools, and statistical tools.10. What is a data mart? How is it similar to a data warehouse?ANSWER: A data mart is a subset of a data warehouse in which only afocused portion of the data warehoused information is kept.Chapter4SHORT-ANSWER QUESTIONS (p. 123)11.What are the four types of decision discussed in this chapter? Give an exampleof each.ANSWER: Nonrecurring, or ad hoc, decision is one that you make infrequently (perhaps only once) and you may even have different criteria for determining the best solution each time. A merger with another company is an example.Recurring decisions are decisions that you have to make repeatedly and often periodically, whether weekly, monthly, quarterly, or yearly. An example would be which route to take to go to work. Nonstructured decision a decision for which there may be several “ right answers” and there is no precise way to get a right answer. An example would be whether to change a company’ sstrategy.Structured decision is a decision where processing a certain kind of information in a specified way so that you will always get the right answer. An examplewould be deciding how much to pay employees. p. 95512. What are the four steps in making a decision?ANSWER:The four steps are intelligence, design, choice, and implementation.p.9613.What is a DSS? Describe its components.?ANSWER: A decision support system (DSS) is a highly flexible and interactive IT system that is designed to support decision making when the problem is not structured. The components of a decision support system are the model management component, the data management component, and the user interface management component. p. 9814. What is a geographic information system used for?ANSWER: A geographic information system is used for any type of information that can be represented spatially. p. 10315.How is information represented in a geographic information system? ANSWER:A geographic information system represents information in overlapping layers.p. 103.16.What is artificial intelligence? Name the artificial intelligence systems usedwidely in business?ANSWER: Artificial intelligence (AI ) is the science of making machinesimitate human thinking and behavior. The types of artificial intelligence widely used in business are expert systems, neural networks, genetic algorithms, and intelligent agents. p. 10417.What are four advantages of an expert system?ANSWER: Four advantages would be their ability to handle large amounts of data; to reduce errors; to aggregate information from various sources; and to improve customer service. p. 10618. What sort of problems is an expert system used for?ANSWER: An expert system is used or diagnostic (what’wrong?)s andprescriptive (what to do?) types of problems. p. 10519. What sort of problem does a neural network solve?ANSWER: A neural network solves problems involving the recognition anddifferentiation of pattersn. p. 10820.What three concepts of evolution are used by the genetic algorithm?ANSWER: The three concepts are selection, mutation, and crossover.Selection is the feature of a genetic algorithm that give preference to better6outcomes. Mutation is a feature of a genetic algorithm; it’ s the process of trying combinations and evaluating the success (or failure) of the outcome Crossover.isthe feature of a genetic algorithm where portions of good outcomes arecombined in the hope of creating an even better outcome. p. 11221. What are intelligent agents? What tasks can they perform?ANSWER: Intelligent agents are software that assists you, or act on yourbehalf, in performing repetitive computer-related tasks. They can find gooddeals on the Internet, monitor computer networks for failures, fill out forms, playcomputer games, and so on. p. 11312.What is a multi-agent system?ANSWER: A multi-agent system is a group of intelligent agents that each hasthe ability to work independently and to interact with others. p. 11613.What do monitoring-and-surveillance agents do?ANSWER: Monitoring-and-surveillance agents (or predictive agents) areintelligent agents that observe and report on equipment. p. 114Chapter5SHORT-ANSWER QUESTIONS (p. 155)1.What is electronic commerce?ANSWER: Electronic commerce is commerce, but it is commerce acceleratedand enhanced by IT, in particular the Internet.2.How can use you a B2B e-marketplace to reduce your dependency on aparticular supplier?ANSWER: You can use a B2B e-marketplace to find other suppliers and alsoparticipate in reverse auctions to find the best supplier with the best price.3.How do convenience and specialty items differ in the B2C e-commerce businessmodel?ANSWER: Convenience items are lower-priced but something needed on afrequent basis. Specialty items are higher-priced, ordered on a less frequentbasis, and often require customization.4.Why do commoditylike and digital items sell well in the B2C e-commerce business model?ANSWER: Commoditylike items work well because they are the same nomatter where you buy them. Digital products work well because there is no realassociated shipping or storage costs.75.What is mass customization?ANSWER:Mass customization is the ability of an organization to give itscustomers the opportunity to tailor its product or service to the customer’ s specifications.6.How does a reverse auction work?ANSWER:In a reverse auction, you place a request for products and/orservices and suppliers continually submit lower bids until there is only onesupplier left.7.How are vertical and horizontal e-marketplaces different?ANSWER:Vertical e-marketplaces connect buyers and sellers in a givenindustry while horizontal e-marketplaces connect buyers and sellers acrossmany industries.8.What can a marketing mix include for a B2C e-commerce business?ANSWER: A marketing mix for a B2C business can include registering withsearch engines, online ads, viral marketing, and affiliate programs.9.What are the major types of B2C e-commerce payment systems?ANSWER: The major types of B2C e-commerce payment systems includecredit cards, smart cards, financial cybermediaries, electronic checks, andElectronic Bill Presentment and Payment.10.What is the difference between a client-side digital wallet and a server-sidedigital wallet?ANSWER: You keep a client-side digital wallet on your personal computerwhile a server-side digital wallet is stored on a Web server.11.How are Secure Sockets Layers (SSLs) and Secure Electronic Transactions (SETs)different? How are they the same?ANSWER: SSLs and SETs are different in that SETs also provide a mechanismfor ensuring the legitimacy of the user of the payment device. They are both thesame in that they create a secure connection between the client and the servercomputers.Chapter6SHORT-ANSWER QUESTIONS (p. 189)1.What are the three primary groups of people who undertake thesystems development process?8ANSWER: The three primary groups of people who undertake the systemsdevelopment process are in-house IT specialists (insourcing), end users(selfsourcing), and another organization outsourcing().2.What is the systems development life cycle?ANSWER: The SDLC is a structured step-by-step approach for developinginformation systems.3.What are scope creep and feature creep?ANSWER: Scope creep occurs when the scope of the project increases beyond its original intentions. Feature creep occurs when developers (and end users) add extra features that were not part of the initial requirements.4.How do the four implementation methods differ?ANSWER: Parallel implementation uses both the old and new systems until the new system is verified. Plunge implementation immediately ceasesusing the old system and begins using the new system. Pilot implementation converts only a group of users until the new system is verified. Phased implementationconverts only a portion of the system until it can be verified.5.What is component-based development?ANSWER: Component-based development is a general approach to systems development that focuses on building small self-contained b locks of code (components) that can be reused across a variety of applications within an organization.6.How are component-based development and a service-orientedarchitecture related?ANSWER: Component-based development is a technical implementation of a service-oriented architecture (SoA). An SoA is a holistic perspective of how an organization views and treats resources such as information and technology.7.Why do organizations prototype?ANSWER: Organizations prototype for a variety of reasons: (1) to gather requirements, (2) to help determine requirements, (3) to prove that a system is technically feasible, and (4) to sell the idea of a proposed system.8.What are the advantages of selfsourcing?ANSWER: The advantages of selfsourcing are many including: improving requirements determination, increasing end user participation and sense of ownership, increasing speed of systems development, and reducing the invisible backlog.99.What is the difference between a selling prototype and a proof-of-concept prototype?ANSWER: A selling prototype is used to convince people of the worth of a proposed system while a proof-of-concept prototype is used to prove the technical feasibility of a proposed system.10.What is the role of a service level agreement (SLA) in outsourcing?ANSWER: A service level agreement in outsourcing defines the work to be done, the time frame, the metrics that will be used to measure the success of the systems development effort, and the costs.11. What are the three geopolitical forms of outsourcing?ANSWER: The three geopolitical forms of outsourcing include onshoreoutsourcing, nearshore outsourcing, and offshore outsourcing.Chapter7SHORT-ANSWER QUESTIONS (p. 220)1.How can a service-oriented architecture (SoA) be used to guide theorganization of the future?ANSWER: A service-oriented architecture (SoA) can guide the organization of the future by enabling it to respond more adeptly to customers, end users,software development, information needs, and hardware requirements.2.How have ERP systems evolved over the last 30 years?ANSWER: ERP starts in the 1970s as basic material requirements planningsystems. They then moved into an MRP II stage in which decision support and executive support capabilities were added. In the early 1990s, financials andaccounting functions were integrated. Today finally, they are called ERP II, acomplete integration of resource planning driven by customer relationshipmanagement and supply chain management activities.3.Why is interoperability important?ANSWER: Interoperability provides the capability for two or more computingcomponents to share information and other resources, even if they are madeby different manufacturers.4.What are the main differences between a decentralized infrastructure anda centralized infrastructure?ANSWER: A decentralized infrastructure involves little or no sharing of IT andIT-related resources, while a centralized infrastructure involves the complete10sharing of IT and IT-related resources (albeit from one centrally-control location).5.How does a client/server infrastructure work?ANSWER: A client/server network works by having one or more computers that are servers provide services to other computers, called clients.6.What are the four types of a tiered infrastructures?ANSWER: The four types of tiered infrastructures are 1-tier (presentation), 2-tier (application), 3-tier (data), and n-tier (business logic).7.How do efficiency and effectiveness metrics differ?ANSWER: Efficiency focuses on doing something right, such as reducing time or number of errors, while effectiveness focuses on doing the right things, such as making the right decisions.8.What are some commonly used infrastructure-centric metrics?ANSWER: Commonly used infrastructure-centric metrics include throughput,transaction speed, system availability, accuracy, response time, and scalability.9.What are some commonly used Web-centric metrics?ANSWER: Commonly used Web-centric metrics include unique visitors, total hits, page exposures, conversion rate, click-through, cost-per-thousand,abandoned registrations, and abandoned shopping carts.10.Why are service level agreements important when contracting the services ofan application service provider (ASP)?ANSWER: A service level agreement (SLA) would provide the quantifiablemeasures by which the ASP must provide services.11.What is a business continuity plan?ANSWER: A business continuity plan is a step-by-step guideline defininghow the organization will recover from a disaster or extended disruption of its business processes.12.Why do organizations implement a disaster recovery plan before testing it?ANSWER: Organizations implement a disaster recovery plan before testing it because organization cannot test their disaster recovery plans until the planis implemented.11。
海洋开发和海洋保护之间平衡的英语作文
海洋开发和海洋保护之间平衡的英语作文全文共3篇示例，供读者参考篇1The Balance between Ocean Exploitation and Ocean ConservationIntroductionThe ocean is a vast and complex ecosystem that provides numerous benefits to humans, including food, transportation, recreation, and climate regulation. However, as human activities have expanded, the ocean has faced increasing pressures from pollution, overfishing, habitat destruction, and climate change. Balancing the needs of ocean development and conservation is essential to ensure the health and sustainability of this crucial resource.Development of the OceanThe ocean has long been seen as a source of economic opportunity and growth. The development of offshore oil and gas resources, fishing, shipping, and tourism has created jobs, generated revenue, and contributed to economic growth. These activities have helped meet the needs of a growing globalpopulation and have provided valuable products and services to consumers around the world.However, the rapid expansion of ocean development has led to numerous negative impacts on marine ecosystems. Overfishing has depleted fish populations, destroyed habitats, and disrupted marine food webs. Pollution from industrial and agricultural runoff, oil spills, and plastic waste has contaminated water, killed marine life, and harmed human health. The acidification and warming of the ocean due to climate change have threatened coral reefs, shellfish, and other marine organisms.Conservation of the OceanIn response to these challenges, there has been a growing recognition of the need to protect and conserve the ocean. Governments, international organizations, non-governmental organizations, and businesses have implemented a variety of policies and initiatives to safeguard marine ecosystems and promote sustainable ocean use. Marine protected areas, fisheries management plans, pollution control measures, and climate change mitigation strategies have been established to preserve the health and biodiversity of the ocean.Conservation efforts have been successful in some areas, such as the recovery of depleted fish stocks, the restoration of damaged habitats, and the reduction of plastic pollution. However, there is still much work to be done to achieve the long-term sustainability of the ocean. The impacts of climate change, habitat destruction, overfishing, and pollution continue to threaten the health and resilience of marine ecosystems.Balancing Development and ConservationFinding the right balance between ocean development and conservation is a complex and challenging task. On the one hand, there is a need to meet the growing demand for food, energy, transportation, and recreation while creating jobs and fostering economic growth. On the other hand, there is a need to protect the ocean from overexploitation, degradation, and collapse to ensure its continued productivity, resilience, and biodiversity.To achieve this balance, it is essential to adopt an integrated and holistic approach to ocean management that takes into account the interconnectedness of marine ecosystems, human activities, and climate change. This approach should involve the collaboration of governments, scientists, industry, and civil society to develop and implement effective policies and practices that promote sustainable ocean use and conservation.Key principles for balancing ocean development and conservation include:1. Precautionary approach: Governments, businesses, and individuals should take proactive measures to prevent harm to the ocean and its inhabitants, even in the absence of full scientific certainty.2. Ecosystem-based management: Policies and practices should consider the interconnections and interactions of marine species, habitats, and processes to maintain the health and resilience of marine ecosystems.3. Science-based decision-making: Decisions about ocean development and conservation should be informed by the best available scientific knowledge and evidence to ensure their effectiveness and sustainability.4. Stakeholder engagement: All stakeholders, including governments, industry, communities, and NGOs, should be involved in the planning, implementation, and monitoring of ocean management initiatives to promote transparency, accountability, and inclusivity.ConclusionAchieving a balance between ocean development and conservation is essential to ensure the long-term health and sustainability of the ocean. By adopting an integrated and holistic approach to ocean management, governments, businesses, and individuals can protect marine ecosystems, promote sustainable ocean use, and secure the benefits of the ocean for future generations. Only through cooperation, innovation, and shared responsibility can we safeguard the ocean for the benefit of all.篇2Title: Balancing Ocean Development and ConservationIntroductionThe ocean is a vast and diverse ecosystem that plays a critical role in regulating the Earth's climate, providing food and livelihoods for millions of people, and supporting biodiversity. As human populations continue to grow and demands for resources increase, there is a pressing need to balance the development of the ocean with its conservation.Development of the OceanThe ocean is a valuable source of natural resources, including fish, minerals, and energy. Fisheries are a major sourceof protein for billions of people around the world, and many coastal communities rely on fishing for their livelihoods. Additionally, the ocean contains vast reserves of minerals such as manganese, copper, and cobalt, which are used in electronics, construction, and other industries. Offshore oil and gas exploration also provide significant economic benefits to countries with coastal resources.Conservation of the OceanDespite its importance as a source of resources, the ocean is facing numerous threats from human activities. Overfishing, pollution, habitat destruction, and climate change are all putting immense pressure on marine ecosystems. Species are being lost at an alarming rate, coral reefs are dying off, and plastic pollution is choking our oceans. The loss of biodiversity and degradation of marine environments have negative impacts on both local communities and global ecosystems.Finding the BalanceBalancing the development of the ocean with its conservation is a complex challenge that requires careful planning and management. Sustainable practices, such as sustainable fisheries management, marine protected areas, and renewable energy development, are key to ensuring thelong-term health and productivity of the ocean. Collaboration between governments, industry, scientists, and local communities is essential to finding solutions that benefit both people and the environment.ConclusionIn conclusion, the development of the ocean and its conservation are intricately linked and must be approached in a holistic manner. By prioritizing sustainable practices and working together to find creative solutions, we can ensure that the ocean remains a valuable resource for future generations. It is up to all of us to take action to protect and preserve this essential ecosystem.篇3Title: Balancing Ocean Development and ConservationIn recent years, the ocean has become a focal point for both development and conservation efforts. On one hand, there is a growing demand for the exploration and utilization of marine resources to support economic growth and human well-being. On the other hand, there is a pressing need to protect the ocean's delicate ecosystems and biodiversity. Striking a balance between ocean development and conservation is crucial toensure the sustainable use of marine resources and the preservation of the ocean for future generations.The oceans cover over 70% of the Earth's surface and play a vital role in regulating the planet's climate, providing food and livelihoods for millions of people, and supporting a diverse range of marine species. However, unsustainable practices such as overfishing, pollution, and habitat destruction have put immense pressure on marine ecosystems and threatened their long-term health and productivity.To address these challenges, governments, international organizations, NGOs, and the private sector are increasingly focusing on both ocean development and conservation initiatives. On one hand, there is a growing interest in harnessing the economic potential of the ocean through activities such as deep-sea mining, aquaculture, and marine biotechnology. These activities have the potential to generate significant economic benefits, create jobs, and promote innovation and technological advancement.On the other hand, there is a growing recognition of the need to protect the ocean's valuable resources and ensure their sustainable use. Conservation efforts such as marine protected areas, sustainable fisheries management, and ecosystem-basedapproaches to marine spatial planning are being implemented to safeguard the health and resilience of marine ecosystems and biodiversity.Balancing ocean development and conservation requires a multi-faceted approach that takes into account the complex interactions between human activities and the marine environment. It involves balancing the needs of different stakeholders, including governments, businesses, local communities, and environmental groups, and integrating social, economic, and environmental considerations intodecision-making processes.Key principles for achieving a balance between ocean development and conservation include:1. Promoting sustainable development: Ensuring that ocean development activities are carried out in a manner that is environmentally sustainable, economically viable, and socially responsible. This includes adopting best practices, technologies, and management strategies that minimize negative impacts on the marine environment and maximize benefits for both present and future generations.2. Implementing effective conservation measures: Establishing and enforcing regulations, policies, andmanagement frameworks that protect marine ecosystems and biodiversity from harmful activities such as pollution, overfishing, and habitat destruction. This includes designating marine protected areas, establishing fishery quotas, and implementing ecosystem-based management approaches.3. Enhancing stakeholder engagement: Involving all relevant stakeholders in decision-making processes related to ocean development and conservation, including governments, businesses, local communities, and civil society organizations. This includes promoting transparency, accountability, and participation in decision-making processes to ensure that the interests of all stakeholders are taken into account.4. Fostering innovation and collaboration: Encouraging innovation, research, and collaboration among governments, businesses, academia, and civil society to develop new technologies, tools, and solutions for sustainable ocean development and conservation. This includes promoting information sharing, capacity building, and public-private partnerships to address common challenges and achieve shared goals.5. Building resilience and adaptation: Enhancing the resilience of marine ecosystems and coastal communities toclimate change, ocean acidification, and other environmental stressors by promoting adaptive management, ecosystem-based approaches, and sustainable livelihoods. This includes supporting communities that are vulnerable to the impacts of ocean development and conservation and ensuring that they have the knowledge, resources, and capacity to adapt to changing conditions.By adopting a balanced approach to ocean development and conservation, we can ensure the long-term health and sustainability of marine ecosystems and biodiversity while also promoting economic growth, human well-being, and social equity. It is essential that we work together to find innovative solutions that meet the needs of both people and the planet and secure a healthy and prosperous future for the ocean and its inhabitants.。
矿业工程专业英语
矿业工程专业英语Pursuing a Promising Path: The Significance of Mining Engineering EnglishThe field of mining engineering has long been a critical component of global industrial development, playing a pivotal role in extracting and processing the natural resources that fuel our modern way of life. As the demand for these resources continues to grow, the importance of mining engineering has become increasingly evident, necessitating a strong command of the English language to navigate the international landscape of this dynamic industry.One of the primary reasons why mining engineering English is so crucial is the inherent global nature of the field. Mining operations are often located in remote regions, spanning across national boundaries and involving a diverse array of stakeholders from around the world. Effective communication and collaboration are essential in this context, and a proficiency in English serves as the universal language that enables seamless information exchange, technical discussions, and the coordination of complex projects.Moreover, the advancement of mining technology and techniqueshas led to a rapid evolution in the industry, with new methods, equipment, and best practices constantly emerging. The ability to stay abreast of these developments requires a strong command of English, as the majority of scientific literature, industry publications, and technical manuals are published in this language. By mastering English, mining engineers can access a wealth of knowledge, participate in global dialogues, and contribute to the ongoing progress of the field.Beyond the practical considerations, the importance of mining engineering English also extends to the professional growth and career prospects of those working in the industry. Many multinational mining companies operate across borders, and the ability to communicate effectively in English is often a prerequisite for securing high-level positions, participating in international conferences and workshops, and collaborating with colleagues from diverse cultural backgrounds. Proficiency in English can unlock a world of opportunities, enabling mining engineers to expand their networks, share their expertise, and ultimately, advance their careers.Furthermore, the significance of mining engineering English extends beyond the confines of the industry itself. As the global economy becomes increasingly interconnected, the skills and knowledge acquired by mining engineers can have far-reaching implications. The ability to navigate complex technical and commercial landscapes,collaborate with international partners, and effectively communicate in English can be valuable assets in a wide range of industries, from infrastructure development to sustainable energy solutions.In conclusion, the importance of mining engineering English cannot be overstated. It is a critical tool that enables professionals in this field to navigate the global landscape, stay at the forefront of technological advancements, and unlock a world of career opportunities. By prioritizing the development of English language skills, mining engineers can position themselves for success, contribute to the ongoing progress of the industry, and ultimately, play a vital role in shaping a more sustainable and prosperous future for all.。
GIS专业英语词汇
地理信息系统（GIS）词汇表accreditation 委派accuracy 准确度acquisition 获取activity patterns 活动模式added value 附加值adjacency邻接Aeolian 伊奥利亚人的, 风的, 风蚀的Age of Discovery 发现的年代aggregation聚合algorithm, definition算法,定义ambiguity 不明确analytical cartography 分析制图application programming interfaces(APIs) 应用编程接口ARCGis 美国ESRI公司开发的世界先进的地理信息系统软件ArcIMS 它是个强大的，基于标准的工具，让你快速设计和管理Internet地图服务ArcInfo 在ArcGIS软件家族中，ArcInfo是GIS软件中功能最全面的。
它包含ArcView和ArcEditor所有功能，并加上高级空间处理和数据转换ArcNews 美国ESRI向用户终生免费赠送的ArcNews报刊ArcSDE ArcSDE在ESRI GIS软件和DBMS之间提供通道，是一个空间数据引擎ArcUser Magazine 为ESRI用户创建的报刊ArcView 桌面GIS和制图软件，提供数据可视化，查询，分析和集成功能，以及创建和编辑地理数据的能力ARPANET ARPA 计算机网（美国国防部高级研究计划局建立的计算机网）aspatial data 非空间数据Association of Geographic Information (AGI) 地理信息协会attribute data 属性数据attributes, types 属性，类型attributive geographic data 属性地理数据autocorrelation 自相关Autodesk MapGuide 美国Autodesk公司生产的Web GIS软件Automated mapping/facility management(AM/FM) systems 自动绘图/设备管理系统facilities 设备avatars 化身A VIRIS 机载可见光/红外成像光谱仪azimuthal projections 方位投影batch vectorization 批量矢量化beer consumption 啤酒消费benchmarking 基准Berry, Brian best fit line 最优线binary counting system 二进制计算系统binomial distribution 二项式分布bivariate Gaussian distribution 二元高斯分布block encoding 块编码Bosnia, repartitioning 波斯尼亚，再分离成两个国家buffering 缓冲区分析Borrough, Peter Business and service planning(retailing) application in petroleum and convenience shopping石油和便利购物的业务和服务规划（零售）应用business drivers 业务驱动business, GIS as 业务，地理信息系统作为Buttenfield, Barbara cadasters 土地清册Callingham, Martin cannibalizing 调拨Cartesian coordinate system笛卡尔坐标系Cartograms 统计地图cartographic generalization 制图综合cartographic modeling 地图建模cartometric transformations 量图变换catalog view of database 数据库目录视图census data人口普查数据Census of Population 人口普查central Place Theory 中心区位论central point rule 中点规则central tendency 中心倾向centroid 质心choropleth mapping分区制图choosing a GIS 选择一个地理信息系统class 类别classification generalization 分类综合client 客户端client-server C/S结构客户端-服务器cluster analysis 聚类分析clutter 混乱coastline weave 海岸线codified knowledge 编码知识COGO data 坐标几何数据COGO editing tools 坐标几何编辑工具Collaboration 协作Local level 地方级National level 国家级Collection-level metadata 获取级元数据Commercial-off-the-shelf (COTS) systems 成熟的商业化系统chemas-microsoft-comfficeffice" />>>Commom object request broker architecture (CORBA) 公共对象请求代理体系结构Community, GIS 社区，地理信息系统Competition 竞争Component GIS 组件地理信息系统Component object model (COM) 组件对象模型Computer assisted mass appraisal (CAMA) 辅助大量估价，>>Computer-aided design (CAD)-based GIS 基于计算机辅助制图的地理信息系统Models 数据模型Computer-aided software engineering (CASE) tool 计算机辅助软件工程工具Concatenation 串联Confidence limits 置信界限Conflation 异文合并Conformal property 等角特性Confusion matrix 混淆矩阵Conic projections 圆锥投影Connectivity 连接性Consolidation 巩固Constant term 常数项Contagious diffusion 传染扩散Continuing professional development (CPD) 持续专业发展Coordinates 坐标Copyright 版权Corridor 走廊Cost-benefit analysis 成本效益分析Cost-effectiveness evaluation 成本效率评估Counting method 计算方法Cresswell, Paul Customer support 客户支持Cylindrical Equidistant Projection 圆柱等距投影Cylindrical projections 圆柱投影Dangermond, Jack 美国ESRI总裁>>dasymetric mapping 分区密度制图>>data 数据>>automation 自动化>>capture costs 获取代价>>capture project 获取工程>>collection workflow 采集工作流>>compression 压缩>>conversion 转换>>definition 定义>>geographic, nature of 地理数据，数据的性质>>GIS 地理信息系统>>industry 产业>>integration 集成>>mining挖掘>>transfer 迁移>>translation 转化>>data model 数据模型>>definition 定义>>levels of abstraction 提取等级>>in practice 实际上>>types 类型>>database 数据库>>definition 定义>>design 设计>>generalization 综合>>global 全球的>>index 索引>> multi-user editing 多用户编辑>>structuring 结构>>database management system (DBMS) 数据库管理系统>>capabilities 能力>>data storage 数据存储>>geographic extensions 地理扩展>>types 类型>>Dayton Accord 达顿协定，1995年12月达顿协定(DAYTON ACCORD)签订,巴尔干和平已经实现,波斯尼亚(包括黑塞哥维那)再被分解成两个国家>>decision support 决策支持>>deductive reasoning 演绎推理>>definitions of GIS 地理信息系统的各种定义>>degrees of freedom 自由度>>density estimation 密度估算>>dependence in space 空间依赖>>desktop GIS 桌面地理信息系统>>desktop paradigms 桌面范例>>Digital Chart of the World (DCW) 世界数字化图>>digital divide 数字鸿沟>>Digital Earth 数字地球>>Digital elevation models (DEMs) 数字高程模型>>Digital line graph (DLG) 数字线划图>>Digital raster graphic (DRG) 数字影像图>>Digital representation 数字表现>>Digital terrain models 数字地形模型>>Digitizing 数字化>>DIME (Dual Independent Map Encoding) program 美国人口调查局建立的双重独立地图编码系统>>Dine CARE >>Discrete objects 离散对象>>Douglas-Poiker algorithm 道格拉斯-普克算法，一种矢量数据抽稀算法>>Dublin Core metadata standard 都柏林核心元数据标准>>Dynamic segmentation 动态分割>>Dynamic simulation models 动态仿真模型>>Easting 朝东方>>Ecological fallacy 生态谬误>>e-commerce 电子商业>>editing 编辑education 教育>>electromagnetic spectrum 电磁光谱>>ellipsoids 偏振光椭圆率测量仪>>of rotation 旋转的>>emergency evacuation 应急撤退>>encapsulation 封装>>environmental applications 环境应用>>environmental impact 环境影响>>epidemiology 流行病学>>equal area property 等面积特性>>Equator 赤道>>ERDAS ERDAS公司是世界上最大的专业遥感图像处理软件公司，用户遍布100多个国家，软件套数超过17000套。
知识管理专业术语
• Value Innovation 价值创新 Vertical Collaborationa 垂直整合 Virtual Community 虚拟社群 Virtual Organization 虚拟组织 Value Proposition 价值主张 Virtual Team 虚拟团队
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• Wetware 湿件 Wikipedia 维基百科 Wisdom Management System （WMS） 智慧管理系统 Workflow 工作流
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• Learning Community 学习社区 Learning Organization 学习型组织 Local Knowledge 当地知识 Lower-Level Learning 低阶学习
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• Mentoring 师徒制 Metadata 元数据 Mode of Mind 心智模式
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• Data 数据 Data mining 资料挖掘 Data warehouse(DW) 数据仓库 Demand-pull 需求拉动 Diffusion 传播 Digital Nervous System 数字神经系统 Discontinuance 中止 Discontinuity of Knowledge 知识中断 Discussion 讨论区 Decision-making costs 决策成本 Decision supporting system(DSS) 决策支持系统 Digital Nervous System 数字神经系统 Document Management 文件（文档）管理
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• Joint knowledge production 关联知识生产 Just in Time Learning (JITL) 及时学习
英语发明机器人如何好好实现的作文80词
英语发明机器人如何好好实现的作文80词全文共3篇示例，供读者参考篇1The development of English-speaking robots is acutting-edge technology that has the potential to revolutionize the way we communicate and interact with machines. However, creating a truly effective and fully functional English-speaking robot poses many challenges that must be carefully considered and addressed.First and foremost, the language processing capabilities of the robot must be top-notch. This includes the ability to understand and interpret English language input from users, as well as generate coherent and contextually relevant responses. Natural language processing algorithms and machine learning techniques must be leveraged to achieve this level of language proficiency.Furthermore, the robot must possess a vast and up-to-date knowledge base in order to provide accurate and informative responses to user queries. This knowledge base can bepopulated through data mining, web scraping, and other means of information retrieval.In addition to language processing and knowledge representation, the robot must also be equipped with advanced sensor technologies to perceive and navigate its environment. Computer vision, speech recognition, and other sensory technologies must be integrated to enable the robot to interact with users in a variety of contexts.Ultimately, the successful realization of an English-speaking robot requires a multidisciplinary approach that combines expertise in linguistics, artificial intelligence, robotics, and human-computer interaction. By leveraging the latest advancements in these fields, researchers and engineers can pave the way for the development of truly intelligent and communicative robots that will enhance our daily lives.篇2How to Successfully Develop English Speaking RobotsThe development of English-speaking robots has become a major focus in the field of artificial intelligence in recent years. With advancements in technology and artificial intelligence, the possibility of creating robots that can communicate effectively inEnglish is becoming increasingly feasible. However, there are several key steps that need to be followed in order to successfully develop English-speaking robots.First and foremost, it is essential to have a clear understanding of the English language, including grammar, vocabulary, and pronunciation. This requires a strong foundation in linguistics and computational linguistics, as well as access to a vast database of English language resources. Natural language processing algorithms can be used to analyze and interpret English text, allowing robots to understand and respond to human speech effectively.In addition, it is important to develop robust speech recognition and synthesis technology that can accurately transcribe and produce English speech. This involves training machine learning models on large datasets of English speech to improve accuracy and fluency. By combining speech recognition and synthesis technologies, robots can engage in more natural and fluid conversations with humans.Furthermore, it is crucial to implement machine learning techniques to continuously improve the performance of English-speaking robots. This involves collecting data on user interactions and feedback, and using this information to refineand optimize the robot's language capabilities. By incorporating reinforcement learning and other adaptive algorithms, robots can adapt to different speaking styles and preferences, enhancing their overall communication skills.Overall, the successful development of English-speaking robots requires a multidisciplinary approach that integrates expertise in linguistics, artificial intelligence, and machine learning. By following these key steps and leveragingcutting-edge technology, researchers can create robots that can effectively communicate in English and enhance human-robot interaction in a variety of applications.篇3How to Successfully Create an English Invention of RobotsIn recent years, the development of robots has made significant progress in various fields, such as manufacturing, healthcare, and even entertainment. As we know, many of these robots are made in countries where English is the primary language. In order to successfully create an English invention of robots, there are several factors to consider.First, it is crucial to have a team of skilled engineers and programmers who are proficient in English. This is because mostof the research and development in robotics is conducted in English, and having a team that can understand and communicate effectively in this language is essential for success.Second, it is important to stay up to date with the latest advancements in technology and robotics. This can be done by attending conferences, workshops, and other events where experts in the field present their work. By staying informed, the team can ensure that their robots are cutting-edge and competitive in the market.Third, collaboration with other institutions and companies can also be beneficial. By working together with other experts in the field, the team can leverage their knowledge and resources to create more advanced and innovative robots.Overall, creating an English invention of robots requires a combination of skilled professionals, continuous learning, and collaboration. By following these guidelines, the team can increase their chances of success and create robots that are both innovative and impactful.。
SAP Knowledge Management 概览
SAP NetWeaver Knowledge Management (知识管理) 概览戴浩SAP NetWeaver Advisory Office APA知识管理（KM ）–不仅仅是一种技术SAP NetWeaver 知识管理：方案和功能总结架构/集成可能性对知识管理的评论“对知识的投资可以获得最好的回报”Benjamin Franklin，投资人“我们信息充足，但急需知识”John Naisbitt，作家“整合是一个开始；保持整合状态意味着进步；协同工作才能取得成功”Henry Ford，企业家“一个企业的学习并将学习成果转化为行动的能力是最根本的竞争优势”Jack Welch，通用电气前任主席“我协同合作，所以我知道”知识管理世界杂志变革始终意味着知识传输昨天纵向孤岛今天横向流程始终（而且进一步提高）基于个人知识的合作：记录下来或者存在人们的头脑中永久变革知识管理：不仅仅是工具和技术！技术只是知识管理的一个方面其它方面包括：战略n开放的企业文化n对错误的容忍度n人与人的信任n动机n“通过实践学习”n共同的价值和语言流程n嵌入到日常工作行为中n衡量能力n业务流程的监控不同用户需要不同的信息CxO经理员工结构化信息非结构化信息非结构化信息的特点容易被任何人创建存在于各种不同的地方需要人员交互用于业务环境内统一化将会很好，但是...…信息分布于组织内...组织n 分公司n 部门n 团队n ...技术n Web 服务器n 文件服务器n SAP 系统n DM 系统n ...语义n 类别n 关键字n 浏览层次n ...…结果是n 人们不能找到正确的信息n 相关的信息无法关联n 无法实现人员之间的协作和信息交流n…Divider Page Section B SAP NetWeaver 知识管理：方案和功能知识管理–不仅仅是一种技术总结架构/ 集成可能性SAP NetWeaver ™－将企业服务体系的构想变为现实知识管理和协作是n SAP NetWeaver ™的关键功能之一n 紧密集成到SAP 企业门户中n 用于管理非结构化信息n 用于鼓励实践群体n 可根据客户业务需求而扩展的框架n 可集成第三方文档库和协作产品的开放设计…挑战1：集中访问文档通过SAP EP 集中访问非结构化信息挑战2：不同种类的文档库通过SAP EP 集中接入非结构化信息集成现有的第三方知识库将文档直接存储在SAP 企业门户环境中SAP NetWeaver –知识管理“将所有信息集中到一个知识库中是不可能的...”知识管理提供了n 一个搜索的能力n 一个统一的浏览模式n 一个look&feeln 一个接入建立在分布式知识库上的知识管理服务SAP 企业门户知识管理包括n 内容管理n 搜索和分类（TREX ）SAP 合作伙伴知识库的集成认证随SAP知识管理提供的标准连接器n‘自身’KM的知识库n文件系统n Web 服务器（http / https）n WebDAVn Lotus Domino (5.x)合作伙伴认证n IXOS DocuLink 4.6C（或更高版n FileNet P8n其它厂商的认证正在开发或讨论中n合作伙伴连接器信息可参见：n其它集成机制：u iViews（例如Documentum）u专用工具（例如Lotus）客户及合作伙伴可以开发自己的连接器（‘库管理器’）：请访问ht t p://w ww.sdK n ow l ed搜索能力搜索n全文n属性不同搜索模式n精确n语言：利用查询条件搜索n模糊：允许错误的搜索n通配符搜索，使用* 或? n复杂表达的短语搜索n布尔运算符n高亮/ HTML 转换/ 与维护的关键字链接n内容摘录n联合搜索（使用其它搜索引擎索引）文本挖掘n搜索相似文档（例如‘另见‘）n自动将文档分类举例：SAP Enterprise Portal 6.0中的搜索结果挑战3：用户希望传播信息通过SAP EP 集中接入非结构化信息在企业组织内传播信息在KM 内创建文档特性n文件上传n以KM 内存储的模板创建新文件n属性n版本管理n许可n发布工作流n定时发布n自动索引/ 分类存储n透明的跨知识库存储（如果授予写入权限）创建HTML 内容：XML 表格作者以基于Web 的表格编写内容（XML表格）读者以企业统一的look&feel 查看HTML 内容，可以接入所有KM 服务挑战4：用户需要成功的协同合作通过SAP EP 集中接入非结构化信息与同事的协作SAP NetWeaver 协同合作：组成部份业务上下文集成到知识管理和协同合作中知识管理WebDAV文件服务器WebCM 知识库Lotus NotesIXOS Doculink企业门户协同合作协作室实时协作群件集成第三方异步协作业务应用业务流程FileNet P8……NetWeaver2004中的协作启动台查看联系人中有谁在线开始实时或异步协作（使用SAP 或SAP 合作伙伴的工具）虚拟团队中用于会议的协作室基于模板的协作室结构可重复利用所有的门户iViews了解团队成员中有谁在线，并通过同步和异步协作服务进行联系挑战5：将KM 嵌入到业务流程中将KM 嵌入到业务流程中1.3a. …3b. …举例：经理自助服务（MSS）使用NetWeaver2004中的KM给所有用户的商业智能信息：信息广播发送电子邮件发布到KM （一次性、定时）嵌入到协作室中订阅反馈备注搜索…知识管理–不仅仅是一种技术SAP NetWeaver 知识管理：方案和功能架构/ 集成可能性总结KM 平台: 结构特征KM平台Array n Applications around unstructured informationn People-centric collaborationn Enterprise content management 开放的结构n Plug-able repository managersn Plug-able servicesn Standard Interfaces WebDAV, ICE n Open namespacesn Partners / customers can develop their own repostitory managers不同平台的连接器n HTTP, FTP, FILE, WebDAV, LDAPn JDBC, IMAP, UDDIKM 平台的主要组成部份FS MailNewsCMKM 结构Browser, PDA, … iView Server(Authentication, Delivery, …)WebDAV 服务器ICE 服务器Web ServicesKM iViews(Home, Links, …)Other iViewsKM Controls(Search, Resource List, …)Repository Framework(Resources, Folders, ACL, Versioning, Locking, …)Repository Manager Repository ManagerRepository Services(Retrieval, Subscription, Crawler, ..) Retrieval and ClassificationSubscription ServerInternal RepositoryExternal RepositorySearch IndicesSubscription DatabaseKM 结构细节Enterprise Portal Application Controls KM Core Global ServiceURIMapper Notificator Pipeline Ordered List IndexManager Content Access Scheduler Connection Pool Mime Handler Cache Object-Type Handler Crawler App-Log .... System LandscapeiView serverPortalContentDirectoryUser management WDF HTMLBKM Framework FilterNameSpace Property ContentWIKI Stream XSLT HTMLProtocolICE WebDAV SOAPRepository ManagerMail Simple FS User manageme nt ICE Filesystem WebDAV WCMSubManangerNamespace Content News Property Security SKWF LDAP Versioning LockingRepository ServicesDiscussion Comment EventLog Subscription Applicati on Prop. Pers. Notes Rating Time-Base Pub Feedback State Manag. Access StatisticNotes Taxonom iesContent Management 系统不同曾面的集成Browser, PDA, … iView Server(Authentication, Delivery, …)WebDAV ServerICE ServerWeb Services1. CMS iViews 2. CMS iViews KM iViews(Home, …)KM Controls(Resource List, …)Repository Services Repository Framework(Resources, Folders, ACL, Versioning, Locking, …)Repository Manager 1 Rep. Manager 2(Retrieval, Subscription,…)TREX Adapter3.CMS Service Adapter 4.External Content Management System (CMS)KM 组成部分与企业门户平台的集成 做为一个集成的解决方案，KM 平台利用如下企业门户框架的成 份： - KM 终端用户的功能是通过在企业门户 Java iView Runtime 上 执行的iViews实现的 - 用户的管理和认定服务 - 利用企业门户的系统环境服务访问服务器, 例如 外部Web服务器 - 以企业门户持续层存储KM iViews的个性化数据合作伙伴产品的主要集成点EP 的 iViews KM 应用的适配/ 创建 同步协作框架SAP 企业门户知识管理和协作角色群件集成框架设计工 工具 具 设计 KM 工具 内容管理（CM） 协作室服务 搜索和分类（TREX） 实时协作 邮件和日历 管理知识库框架KM 灵活的 UI、报 表、KM 命令等SAP Web 应用服务器知识库管理器 （也通过 WebDAV）KM 知识库外部知识库TREX API 通过 KM/CM API 封装，不公开发布协作室 APISAP 知识管理的参考客户知识管理 – 不仅仅是一种技术 SAP NetWeaver 知识管理： 方案和功能 架构 / 集成可能性 总结知识管理的5个挑战及其SAP NetWeaver 的解决方案在组织内传播信息将 KM 嵌入到业务流程中 3a. … 1. 2. 3b. …通过 SAP EP 集中接入非结构化信息 与同事协作执行在企业门户环境中直接存储文档集成第三方知识库SAP NetWeaver KM – 总结SAP NetWeaver™ 知 识管理是一个开放式和集成化的解 决方案，用于实现在企业组 织内发现、传播和使用非结 构化信息。
分布式知识迁移与联邦式图谱推理
第4卷第1期智能科学与技术学报V ol.4No.1 2022年3月Chinese Journal of Intelligent Science and Technology March 2022 群体知识图谱：分布式知识迁移与联邦式图谱推理陈名杨1，张文2，陈湘楠2，周虹廷1，陈华钧1（1. 浙江大学计算机科学与技术学院，浙江杭州 310007；2. 浙江大学软件学院，浙江杭州 310007）摘 要：群体知识图谱是指通过群体协作，以去中心化或分布式方式管理和维护的知识图谱。
相比现有的集中式管理的知识图谱，群体知识图谱具备知识确权、隐私保护、众包激励、可信溯责等特点。
尝试探讨构建或应用群体知识图谱平台面临的技术挑战。
其中分布式知识迁移考虑在一个分散自治的框架下，通过实现不同来源的多个知识图谱之间的知识迁移，缓解单个知识图谱的知识不完备问题。
其主要难点是在充分保护知识的自治所有权的前提下，尽可能共享有用的知识，以增强各自的知识图谱表示。
联邦式图谱推理也是考虑在一个分布式环境下，通过联邦学习机制实现隐私保护前提下的知识图谱推理。
在分布式知识迁移中，强调在关系集合互相重叠的知识图谱间迁移与实体无关的知识；而在联邦式图谱推理中，强调在多个实体集合互相重叠的知识图谱间共同学习更好的实体嵌入表示。
针对这两个问题分别进行模型设计及实验验证。
关键词：群体知识图谱；联邦学习；知识迁移中图分类号：TP391文献标志码：Adoi: 10.11959/j.issn.2096−6652.202217Collective knowledge graph: meta knowledgetransfer and federated graph reasoningCHEN Mingyang1, ZHANG Wen2, CHEN Xiangnan2, ZHOU Hongting1, CHEN Huajun11. College of Computer Science and Technology, Zhejiang University, Hangzhou 310007, China2. School of Software Technology, Zhejiang University, Hangzhou 310007, ChinaAbstract: Collective knowledge graphs refer to knowledge graphs that are managed and maintained in a decentralized or distributed manner through group collaboration. Compared with the existing centrally managed knowledge graph, the collective knowledge graph has the characteristics of knowledge right confirmation, privacy protection, crowd sourcing incentive, and credible traceability. Tring to explore the technical challenges faced by building and applying a collective knowledge graph platform. For meta knowledge transfer, the knowledge incompleteness of a single knowledge graph by knowledge transfer among multiple knowledge graphs from different sources under a decentralized and autonomous framework was considered. The main difficulty was to enhance the respective knowledge graph representation by sharing useful knowledge with each other as much as possible while fully protecting the autonomous ownership of knowledge.For federated graph reasoning, the knowledge graph reasoning in a distributed environment under the privacy-preserving by means of the federated learning mechanism was considered. Meta knowledge transfer focused on transferring enti-ty-independent knowledge between knowledge graphs with overlapped relation set, while federated graph reasoning aimed at learning better entity embeddings for knowledge graphs with overlapped entity set. The model design and expe-rimental validation for each of these two problems were conducted.Key words: collective knowledge graph, federated learning, knowledge transfer收稿日期：2021−12−27；修回日期：2022−02−25通信作者：陈华钧，huajunsir@基金项目：国家自然科学基金资助项目（No.91846204，No.U19B2027）Foundation Items: The National Natural Science Foundation of China (No.91846204, No.U19B2027)·56·智能科学与技术学报第4卷0引言知识图谱（knowledge graph，KG）旨在用图的形式描述客观世界的实体、概念、事件及其之间的关系。
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Knowledge Collaboration by Mining Software RepositoriesThomas ZimmermannSaarland University, Saarbrücken, Germanytz@AbstractWe will give a short overview on recent approaches to support developers by mining software repositories and outline current and future challenges from which knowledge collaboration can benefit.1. IntroductionWhen people collaborate, they communicate and create documents that are shared among each other. In most projects these artifacts are collected and archived in software repositories: For open source projects, communications between developers are stored in mail-ing lists, newsgroups , and personal archives . Changes to the source code of software are recorded in version archives such as CVS. Failures and feature requests are submitted to and discussed in issue tracking systems such as Bugzilla. Explicit knowledge such as documen-tation and design documents is published on websites or wikis.Recently a new research area evolved that mines software repositories. Although most approaches have focused on understanding software and its evolution so far, software repositories can be leveraged to support developers and their collaboration.In this paper, we will give a short overview on the state-of-art of mining software repositories with respect to collaboration (Section 2), before we outline ongoing and future challenges from which knowledge collabora-tion can benefit (Section 3).2. Supporting DevelopersIn this section we present several examples how his-toric data was used to support collaboration among developers. Our overview is not complete since we favored research that actually resulted in tools. For a broader view on mining software repositories we referto the MSR workshop series [6].Figure 1. After an initial change to a method, eROSE recommends related code locations.Project memory. The Hipikat tool by Cubranic et al. [2] was the first one to combine artifacts from different software repositories such as version ar-chives, bug databases, documentation, and mailing lists. Developers can explicitly query this project memory for related artifacts after selecting an initial artifact. Hipikat’s recommendations are especially useful for newcomers to a software project. Guiding developers. The eROSE tool by Zimmer-mann et al. [10] guides programmers along related changes by mining version archives. When a devel-oper changes f() and other people have changed f() together with g() in the past, eROSE will detect this and suggest “Programmers who changed function f() also changed function g()” (see Figure 1). In contrast to Hipikat, eROSE makes recommendations automatically and suggests specific actions (change, add, or delete something). Software navigation. The NavTracks tool by Singer et al. [7] monitors the navigation history of a single developer and use this data to support her future navigation. DeLine et al. [3] extended this work in their Team Tracks tool to multiple developers that share navigation history. All these tools leverage one or more software reposito-ries to support developers by providing knowledge that is obtained from the past. In the next section, we will outline ongoing research challenges that will further improve knowledge collaboration.3. ChallengesThe research on mining software repositories is cur-rently in an early stage. There are several ongoing chal-lenges that are relevant for knowledge collaboration. Multiple data sources. Most research focuses only on one data source such as version archives or bug da-tabases. In recent research several software reposito-ries have been combined (starting with Hipikat [2]).This gives additional context to mining. For in-stance, one can assess changes using bug databases, thus getting a notion of good vs. bad knowledge. Fine-grained changes. All tools discussed in Section 2 focused only on artifact level such as files, methods, or bug reports. Recently, more fine-grained changes were analyzed [4] and used to identify usage pat-terns [5] or cross-cutting concerns [1]. Combined with context information this will lead to tools that can assess new changes based on knowledge that is mined from software repositories (think of a self-learning bad smell check across developers). Collecting new data. Most research analyzed existing software repositories. However, at some point the information available will be exhausted. The Nav-Tracks [7] and Team Tracks [3] tools pioneered a new direction. Instead of taking existing repositories they build their own repositories which are then ana-lyzed. This way, one gets more and better data to turn into knowledge. Related research in this area includes waypointing and social tagging of software as proposed by Storey et al. [8].Mining across projects. Typically multiple projects are mined at the same time for understanding soft-ware evolution. However, when it comes to support-ing developer, only single projects were investigated so far. Xie and Pei were the first ones to mine knowledge (usage patterns) across multiple pro-jects [9]. By considering a large amount of projects, one can build a huge knowledge base. The goal will be to improve search engines for source code such as Koders1 and smoothly integrate them into IDEs. Although mining software repositories does not explic-itly support collaboration, it creates knowledge that helps developers. Since this knowledge is mined from data that comes from different developers, one can think of implicit knowledge collaboration: the knowl-edge is collected in the background and shared among developers.1 / 4. References[1] Silvia Breu and Thomas Zimmermann. “Mining Aspects from History.” In Proceedings of the 21st IEEE/ACM Inter-national Conference on Automated Software Engineering (ASE 2006), September 2006.[2] Davor Cubranic, Gail C. Murphy, Janice Singer, Kellogg S. Booth. “Hipikat: A Project Memory for Software Devel-opment.” In IEEE Transactions on Software Engineering, vol. 31, no. 6, pp. 446-465, June 2005.[3] Robert DeLine, Mary Czerwinski, George G. Robertson. “Easing Program Comprehension by Sharing Navigation Data.” In IEEE Symposium on Visual Languages and Hu-man-Centric Computing (VL/HCC 2005), September 2005, Dallas, USA. IEEE Computer Society, pp. 241-248[4] Beat Fluri and Harald C. Gall. “Classifying Change Types for Qualifying Change Couplings.” In Proceedings of the International Conference on Program Comprehension (ICPC), Athens, Greece, June 2006, pp. 35-45.[5] V. Benjamin Livshits and Thomas Zimmermann. “Dy-naMine: Finding Common Error Patterns by Mining Soft-ware Revision Histories.” In Proceedings of the 10th Euro-pean Software Engineering Conference held jointly with 13th ACM SIGSOFT International Symposium on Founda-tions of Software Engineering (ESEC/SIGSOFT FSE 2005), Lisbon, Portugal, September 2005, pp. 296-305.[6] International Workshop on Mining Software Repositories 2004-2006, http://msr.uwaterloo.ca/[7] Janice Singer, Robert Elves, Margaret-Anne Storey. "NavTracks: Supporting Navigation in Software Mainte-nance.” In Proceedings 21st IEEE International Conference on Software Maintenance (ICSM'05), pp. 325-334, Septem-ber 2005.[8] Margaret-Anne Storey, Li-Te Cheng, Ian Bull, and Peter Rigby. “Waypointing and social tagging to support program navigation.” In CHI '06: Extended Abstracts on Human Fac-tors in Computing Systems. Montréal, Québec, Canada, April 2006. ACM Press, New York, NY, pp. 1367-1372.[9] Tao Xie and Jian Pei. “MAPO: mining API usages from open source repositories.” In Proceedings of the Interna-tional Workshop on Mining Software Repositories (MSR '06), Shanghai, China, May 2006. ACM Press, New York, NY, pp. 54-57.[10] Thomas Zimmermann, Peter Weissgerber, Stephan Diehl, Andreas Zeller. "Mining Version Histories to Guide Software Changes.” In IEEE Transactions on Software En-gineering, vol. 31, no. 6, pp. 429-445, June 2005.。