《高性能计算机网络》课程教学课件（讲义）第十章 大数据之Web典型应用 第56讲 推荐系统简介

Mining of Massive Web Data第56讲推荐系统简介更多资料：http://www.mmds.org武汉理工大学计算机科学与技术学院

Mining of Massive Web Data 更多资料：h1p://www.mmds.org ᦇᓒ๢ᑀ਍Өದ๞਍ᴺ ᒫ56ᦖ വគᔮᕹᓌՕ

计算机科学考技术学院Advanced Data AnalyticsText MiningInformation RetrievalWeb SearchRecommenderSystemSocial ComputingBig Data武铺理工大学

Advanced Data Analytics Text Mining Information Retrieval Web Search Recommender System Social Computing Big Data

计算机科学考技术学院第21讲推荐系统简介Problem DomainBasicTechniquesContentbasedRecommendation武铺理工大学

ᒫ21ᦖ വគᔮᕹᓌՕ Problem Domain Content based Recommenda?on Basic Techniques

计鲜机科学考技术学院Which mobile phone should I buy?0?NOHe3130aen tare(34/2a)13072059(4/182013)nniit1ATe11/2023/20134/24/20131448angs(3/220139(2/225Information.Overloaded SocietyDecision-making problemscerLmLguidC1m0t1.400PShup.seleTTTHTCBASIS0panSH837(2/5/20)(as)(wans)ns3(325/2015)(4/8/2013)(4/23/20133(418/2013)(1/16420135减接里工大学

Which mobile phone should I buy? Informa?on Overloaded Society – Decision-making problems

计好机科学与技术学院Traditional Solutions·Conversationswithfriends? Information from trusted 3rd party·Consult an expert·SearchinformationfromtheInternet·Decisiontheorymethods·GutdecisionJustfollowthecrowd武接殖工大学

• Conversa?ons with friends • Informa?on from trusted 3rd party • Consult an expert • Search informa?on from the Internet • Decision theory methods • Gut decision • Just follow the crowd • . Tradi?onal Solu?ons

计算机科学与技术学院RecommenderSystemaresoftwareagentsthat elicitthe interests and preferences ofindividual consumers[...Jandmake recommendations accordinglyThey have the potential to support and improve the quality ofwhilethedecisionsSmakesearchingforandconsumersselectingproductsonline[Xiao&Benbasat,MiSQ,2007]MovieRecommendationMOVIESIlike"Drama"MoviesHere'sthemoviesyoumaylike1.TheShawshankRedemption2.AnotherHappyDay武铺理工大学

Movie Recommendation I like “Drama” Movies Here’s the movies you may like . 1.The Shawshank Redemption 2.Another Happy Day 3

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Amazon.com: Book Recommender System

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Movie Recommender System

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Music Recommender System

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Problem Domain • Recommenda?on systems (RS) help to match users with items • Ease informa?on overload • Sales assistance (guidance, advisory, persuasion,.) • Different system designs / paradigms • Based on availability of exploitable data • Implicit and explicit user feedback • Domain characteris?cs