Lecture7-RS-Products&Users

Products
• Use users’ context
– – – – – – – – Current time Location & Change Searched keywords Calendar items Translated info Exchange Rate Traffic info, weather info Nearby information, e.g., film info, tourist info…
Outlincuz!
• Android Apps Recommendation in Wandoujia • Google now – from recommendation perspective • Wandou Xibaibai
• Needs
– Find high-quality long-tail apps
• Effectively • Efficiently
Products
• User-oriented recommendation
– – – – Personal Center User interested apps recommendation More natural for android users Apps recommendation is not daily needed
Problems (1)
• Anti-spam
– Comment-spam detection – Low-quality apps detection –…
• Apps Relevancy calculation
– Individual apps relevancy – Apps group relevancy – Time freshness –…
• Recommend Information
Problems
• Too many kinds of context, use what? • Too many kinds of items can be recommended, recommend what? • How to recommend beyond items, but sequences of items, such as travel advice • How to recommend?
豌豆洗白白（2）
豌豆洗白白（3）
Basic Technical Problems
• Apps Relevancy calculation
• Recommendation Reason Detection • User feedback based recommendation
Google Now From Recommendation Perspective
Problems (4)
• Evaluation Metrics
– Online evaluation
• CTR • #Clicks from Recommendation Area
– Offline evaluation
• • • • Precision @ top n Time freshness RMSE Recommended posts quality
Recommender Systems Products & Users
Conglei Yao Wandoujia 2013-04-18
Disclaimers
• This talk presents the opinions of the speaker. It does not reflect the views of Wandoujia or other entity. • Algorithms, techniques, features, etc mentioned here might or might not be in use by Wandoujia or any other companies. • This lecture is purely about products and users analysis of recommendation systems.
• When to recommend?
• How to react to user’s feedback?
Wandou Xibaibai
Android Apps Problems
• Not secuity problems
– 豌豆荚综合腾讯手机管家、360手机卫士和LBE 安全大师三家的检测结果，仅有3.5%不安全
Products
• User-oriented recommendation
– – – – Personal Center User interested posts recommendation Complex, inconsistent with users’ habit Need efforts to redesign architecture
• Forum post-oriented recommendation
– Recommend relevant posts to each post users read – Simply, more natural – Less efforts to redesign architecture
Problems (1)
Problems (4)
• Evaluation Metrics
– Online evaluation
• CTR • Retention
– Offline evaluation
• • • • F1 RMSE Recommendation Reason quality Recommended apps diversity
What’s Google Now?
Users
• Android users
– Search on Google – Use Google Calendar – Allow Google to access their locations – Use other Google products –…
• Newly publish form posts • Delete form posts •…
– System throughout
Problems (3)
• UI Design
– Recommendation area in post page? – Number of recommended posts? – Ranking sequence? – More symbol? – Recommendation Reason？ –…
Problems (2)
• System Architecture
– – – – Millions of apps Most of apps in long-tail Millions of daily users Dynamically changing data
• • • • User installed apps User uninstalled apps User generated comments …
Android Apps Recommendation in Wandoujia
Users
• Behavior
– Looks for Apps
• Top apps, new users • high-quality long-tail apps
– Read/write/reply comments
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• But 山寨 Apps problems
– 26%的应用为山寨应用 – 26.4%的应用包含通知栏广告 – Top100应用100%被山寨
Some Examples
• 搜狗输入法
– – – – – – – – C3B1A16276CAF5E3E8B29E6AB610BFC7 2CFA981A02024839B490D5B0B4F53EA3 BE07BD65C471A2CA326B8CF81F5727DF 2DBCE66AC7969DFE45A6CA7E5F2679D8 B1ACC131F5E95B76522EEEEB535D351E AC86327463189F74B091AA0B61141C2D 67D89A51AE4B84C9DC9146AA4C0A93E6 FC8CEF72E0A782EE069719340A3D9F74
– System throughout
Problems (3)
• UI Design
– Recommendation area in Wandoujia? – Number of recommended apps for each user? – Ranking sequence? – Recommendation Reason –…
Form Posts Recommendation in Discuz!
Users
• Behavior
– Frequent-visited Discuz! sites – Frequent-visited forums – Read/write/reply posts
• Needs