Recomender Systems

Introduction to Recommender SystemGuo, Guangming guogg.good@gmail.comOutline Background & DefinitionSome history worth notingVarious applicationsMain-stream approachEvaluationSome resources2012-12-19Lab of Semantic Computing and Data Mining2Outline Background & DefinitionRelated areasChallengesParadigms Some history worth notingVarious applicationsMain-stream approachEvaluationSome resources2012-12-19Lab of Semantic Computing and Data Mining3Become clear with basic conceptsFirst step of learning

Building blocks of new ideas

Define the rules to play with

Prerequisites for communication

2012-12-194Lab of Semantic Computing and Data MiningDefinition of Recommender Systems Also named recommendation systems A subclass of information filtering system that seek to predict the 'rating' or 'preference' that a user would give to an item (such as music, books, or movies) or social element (e.g. people or groups) they had not yet considered, using a model built from the characteristics of an item (content-based approaches) or the user's social environment (collaborative filtering approaches). --http://en.wikipedia.org/wiki/Recommender2012-12-19Lab of Semantic Computing and Data Mining5More truthImportant vertical technique in data miningOne of the most success solution for industry

Became an independent research area in 1990sMany highly reputed academic conferences such as SIGIR, KDD, ICML, WWW, EMNLP et al. have it as their subtopics.RecSys is fully devoted to this areaData mining/machine learning approach1) specifying heuristics that define the utility function and empirically validating its performance2) estimating the utility function that optimizes certain performance criterion, such as the mean square error.

2012-12-19Lab of Semantic Computing and Data Mining6ChanllengesCold startLong tailData sparsityScalability Social & TemporalContext-awarePersonality-awareBeing accuracy is not enough2012-12-19Lab of Semantic Computing and Data Mining7Related Research AreaCognitive scienceText miningNatural Language ProcessingInformation retrievalMachine learningAssociation miningApproximation theoryManagement scienceConsumer choice in marketing2012-12-19Lab of Semantic Computing and Data Mining8Long tail, user modeling8Paradigm of RecSysContent-based recommendations: recommended items similar to the ones the user preferred in the past;Collaborative recommendations: recommended items that people with similar tastes and preferences liked in the past;Knowledge-based recommendations: recommended items based existing knowledge models that fit the needs of usersHybrid approaches: Combination of various input data or/and composition various mechanism

2012-12-19Lab of Semantic Computing and Data Mining9BackgroundUniverse Problem in Information AgeInformation overloadFrom SE to Recsys pull vs. pushWeb 1.0 vs. web 2.0Leverage the existing user generated dataUser profileBehavior history on the web,RatingClick through data, browse dataGreat benefits(win-win)Help users find valuable informationHelp business make more profits

2012-12-19Lab of Semantic Computing and Data Mining10Outline Background & DefinitionSome history worth notingNetflix prizeVarious applicationsMain-stream approachEvaluationSome resources2012-12-19Lab of Semantic Computing and Data Mining11A peak in the historyResearch on collaborative filtering algorithm reached a peak during the Netflix movie recommendation competition

October 2, 2006 ~ September 21, 2009

RMSEMust outperform baseline by 10%

2012-12-19Lab of Semantic Computing and Data Mining12The Million Dollar Programming PrizeThe Netflix PrizeGreatly energize the research in RecsysLast from 2006 to 2009Finalist: BellKors Pragamatic Chaos teamA joint-teamAndreas Tscher and Michael Jahrer ( Commendo Research &Consulting GmbH), originally team BigChaosRobert Bell, and Chris Volinsky (AT& T), Yehuda Koren (Yahoo),originally team BellKorMartin Piotte and Martin Chabbert, originally team Pragmatic TheoryThe ensemble TeamThe most accurate algorithm in 2007 used an ensemble method of 107 different algorithmic approaches2012-12-19Lab of Semantic Computing and Data Mining13Outline Background & DefinitionSome history worth notingVarious applicationsMain-stream approachEvaluationSome resources2012-12-19Lab of Semantic Computing and Data Mining14Existing applicationsNews/Article recommendationTargeted Advertisement Tags RecommendationMobile Recommendation

E-commerceBooks, movies, music2012-12-19Lab of Semantic Computing and Data Mining1515BenefitsAlternative to Search Engine

Boost the profitAmazon et al.

Better user experience2012-12-19Lab of Semantic Computing and Data Mining16Outline Background & DefinitionSome history worth notingVarious applicationsMain-stream approachContent-basedCollaborative filteringEvaluationSome resources2012-12-19Lab of Semantic Computing and Data Mining17Content-basedSimple compute the similarityCosine similarity or pearson correlation coefficientTF-IDF

Utilize dimensionality reductionLDA2012-12-19Lab of Semantic Computing and Data Mining18Collaborative filteringAssociation miningMemory-basedNearest-neighborsModel-basedLatent fator model

Some comparisonSpace & timeTheory foundation and interpretability

2012-12-19Lab of Semantic Computing and Data Mining1919Latent factor model2012-12-19Lab of Semantic Computing and Data Mining20http://en.wikipedia.org/wiki/Lanczos_algorithm20Computations2012-12-19Lab of Semantic Computing and Data Mining21Partial SVD of the original matrixFunk-svd: http://sifter.org/~simon/journal/20061211.html21Outline Background & DefinitionSome history worth notingVarious applicationsMain-stream approachEvaluationSome resources2012-12-19Lab of Semantic Computing and Data Mining22Evaluation CriterionUser satisfaction by quesionnairePrecisionRMSETop-kCoverageDiversityNoveltySerendipityOriginally thinking recommendation has non-sense2012-12-19Lab of Semantic Computing and Data Mining23Outline Background & DefinitionSome history worth notingVarious applicationsMain-stream approachEvaluationSome resources2012-12-19Lab of Semantic Computing and Data Mining242012-12-19Lab of Semantic Computing and Data Mining25

Sam Roweis25Resourceswww.recsyswiki.com

by http://blog.csdn.net/lzt1983/article/details/7914536

2012-12-19Lab of Semantic Computing and Data Mining26