Introduction to Recommender Systems Handbook

Recommender Systems (RSs) are software tools and techniques providing suggestions for items to be of use to a user. In this introductory chapter we briefly discuss basic RS ideas and concepts. Our main goal is to delineate, in a coherent and structured way, the chapters included in this handbook and to help the reader navigate the extremely rich and detailed content that the handbook offers.

[1]  Zunping Cheng,et al.  Effective diverse and obfuscated attacks on model-based recommender systems , 2009, RecSys '09.

[2]  Fan Yang,et al.  An Efficient Neighbor Searching Scheme of Distributed Collaborative Filtering on P2P Overlay Network , 2004, DEXA.

[3]  Ofer Arazy,et al.  Improving Social Recommender Systems , 2009, IT Professional.

[4]  Srujana Merugu,et al.  A scalable collaborative filtering framework based on co-clustering , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

[5]  Francesco Ricci,et al.  Conversational Case-Based Recommendations Exploiting a Structured Case Model , 2008, ECCBR.

[6]  Soe-Tsyr Yuan,et al.  A recommendation mechanism for contextualized mobile advertising , 2003, Expert Syst. Appl..

[7]  Yehuda Koren,et al.  Matrix Factorization Techniques for Recommender Systems , 2009, Computer.

[8]  Barry Smyth,et al.  Group recommender systems: a critiquing based approach , 2006, IUI '06.

[9]  Dan Frankowski,et al.  Collaborative Filtering Recommender Systems , 2007, The Adaptive Web.

[10]  D. Jannach,et al.  Finding Preferred Query Relaxations in Content-based Recommenders , 2006, 2006 3rd International IEEE Conference Intelligent Systems.

[11]  Ahmad A. Kardan,et al.  A hybrid web recommender system based on Q-learning , 2008, SAC '08.

[12]  Robin D. Burke,et al.  Hybrid Web Recommender Systems , 2007, The Adaptive Web.

[13]  Saeed Shiry Ghidary,et al.  Usage-based web recommendations: a reinforcement learning approach , 2007, RecSys '07.

[14]  Tsvi Kuflik,et al.  Examining users' attitude towards privacy preserving collaborative filtering , 2007 .

[15]  Barry Smyth,et al.  On the Role of Diversity in Conversational Recommender Systems , 2003, ICCBR.

[16]  John Riedl,et al.  Is seeing believing?: how recommender system interfaces affect users' opinions , 2003, CHI '03.

[17]  Tom Gross,et al.  Proceedings of the 2007 international ACM conference on Supporting group work , 2007, GROUP 2007.

[18]  Mari Carmen Puerta Melguizo,et al.  A proactive recommendation system for writing: helping without disrupting , 2007, ECCE '07.

[19]  D. Fesenmaier,et al.  Case-based travel recommendations. , 2006 .

[20]  Nalin Sharda,et al.  Tourism Informatics: Visual Travel Recommender Systems, Social Communities, and User Interface Design , 2009 .

[21]  Francesco Ricci,et al.  Adaptive Recommender Systems for Travel Planning , 2008, ENTER.

[22]  Francesco Ricci,et al.  Improving recommender systems with adaptive conversational strategies , 2009, HT '09.

[23]  Francesco Ricci,et al.  Acquiring and Revising Preferences in a Critique-Based Mobile Recommender System , 2007, IEEE Intelligent Systems.

[24]  M. Decker,et al.  Comparison of Different Approaches for Mobile Advertising , 2005, Second IEEE International Workshop on Mobile Commerce and Services.

[25]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[26]  Francesco Ricci,et al.  Product Reviews in Mobile Decision Aid Systems , 2005, PERMID.

[27]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[28]  D. Fesenmaier,et al.  Destination Recommendation Systems: Behavioural Foundations and Applications , 2006 .

[29]  Francesco Ricci,et al.  COOPERATIVE QUERY REWRITING FOR DECISION MAKING SUPPORT AND RECOMMENDER SYSTEMS , 2007, Appl. Artif. Intell..

[30]  Sung Joo Park,et al.  MONERS: A news recommender for the mobile web , 2007, Expert Syst. Appl..

[31]  Von-Wun Soo,et al.  A personalized restaurant recommender agent for mobile e-service , 2004, IEEE International Conference on e-Technology, e-Commerce and e-Service, 2004. EEE '04. 2004.

[32]  Josep Lluís de la Rosa i Esteva,et al.  A Taxonomy of Recommender Agents on the Internet , 2003, Artificial Intelligence Review.

[33]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[34]  Alfred Kobsa,et al.  Generic User Modeling Systems , 2001, User Modeling and User-Adapted Interaction.

[35]  Sean M. McNee,et al.  Improving recommendation lists through topic diversification , 2005, WWW '05.

[36]  Zunping Cheng,et al.  Statistical attack detection , 2009, RecSys '09.

[37]  B. Ohman,et al.  Discrete sensor validation with multilevel flow models , 2002 .

[38]  Hisham M. Haddad.  Proceedings of the 2006 ACM symposium on Applied computing , 2006, SAC.

[39]  Michael J. Pazzani,et al.  A Framework for Collaborative, Content-Based and Demographic Filtering , 1999, Artificial Intelligence Review.

[40]  John Riedl,et al.  E-Commerce Recommendation Applications , 2004, Data Mining and Knowledge Discovery.

[41]  Peter Funk,et al.  Advances in case-based reasoning : 7th European Conference, ECCBR 2004 Madrid, Spain, August 30 - September 2, 2004 : proceedings , 2004 .

[42]  Alfred Kobsa,et al.  The Adaptive Web, Methods and Strategies of Web Personalization , 2007, The Adaptive Web.

[43]  Michael Wooldridge,et al.  Proceedings of the 21st International Joint Conference on Artificial Intelligence , 2009 .

[44]  John Riedl,et al.  Explaining collaborative filtering recommendations , 2000, CSCW '00.

[45]  Padraig Cunningham,et al.  Smart radio - community based music radio , 2001, Knowl. Based Syst..

[46]  Vipin Kumar,et al.  Introduction to Data Mining , 2022, Data Mining and Machine Learning Applications.

[47]  Marko Modsching,et al.  Field study on methods for elicitation of preferences using a mobile digital assistant for a dynamic tour guide , 2006, SAC '06.

[48]  Alfred Kobsa,et al.  Privacy-enhanced personalization , 2006, FLAIRS.

[49]  Johan Koolwaaij,et al.  Context-Aware Recommendations in the Mobile Tourist Application COMPASS , 2004, AH.

[50]  John Riedl,et al.  Do You Trust Your Recommendations? An Exploration of Security and Privacy Issues in Recommender Systems , 2006, ETRICS.

[51]  Ping Yu,et al.  Representative-Based Diversity Retrieval , 2008, 2008 3rd International Conference on Innovative Computing Information and Control.

[52]  Tsvi Kuflik,et al.  Mediation of user models for enhanced personalization in recommender systems , 2007, User Modeling and User-Adapted Interaction.

[53]  Michael Roberts,et al.  Activity-based serendipitous recommendations with the Magitti mobile leisure guide , 2008, CHI.

[54]  Sean M. McNee,et al.  Being accurate is not enough: how accuracy metrics have hurt recommender systems , 2006, CHI Extended Abstracts.

[55]  Esma Aïmeur,et al.  Short-Term Profiling for a Case-Based Reasoning , 2000, ECML.

[56]  Nitya Narasimhan,et al.  Using location for personalized POI recommendations in mobile environments , 2006, International Symposium on Applications and the Internet (SAINT'06).

[57]  S.C. Hui,et al.  An intelligent recommender system using sequential Web access patterns , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..

[58]  Qusay H. Mahmoud,et al.  Provisioning Context-Aware Advertisements to Wireless Mobile Users , 2006, 2006 IEEE International Conference on Multimedia and Expo.

[59]  Giuseppe Carenini,et al.  Towards more conversational and collaborative recommender systems , 2003, IUI '03.

[60]  Judy Kay,et al.  Scrutable Adaptation: Because We Can and Must , 2006, AH.

[61]  Domonkos Tikk,et al.  Scalable Collaborative Filtering Approaches for Large Recommender Systems , 2009, J. Mach. Learn. Res..

[62]  Guy Shani,et al.  An MDP-Based Recommender System , 2002, J. Mach. Learn. Res..

[63]  Enric Plaza,et al.  Case-Based Sequential Ordering of Songs for Playlist Recommendation , 2006, ECCBR.

[64]  Amnon Meisels,et al.  Recommender System from Personal Social Networks , 2007, AWIC.

[65]  Francesco Ricci,et al.  Supporting Travel Decision Making Through Personalized Recommendation , 2004, Designing Personalized User Experiences in eCommerce.

[66]  Wenliang Du,et al.  Privacy-preserving collaborative filtering using randomized perturbation techniques , 2003, Third IEEE International Conference on Data Mining.

[67]  Gerhard Friedrich,et al.  Recommender Systems - An Introduction , 2010 .

[68]  Li Zhuo,et al.  Construction of user preference profile in a personalized image retrieval , 2008, 2008 International Conference on Neural Networks and Signal Processing.

[69]  Francesco Ricci,et al.  Replaying live-user interactions in the off-line evaluation of critique-based mobile recommendations , 2007, RecSys '07.

[70]  Barry Smyth,et al.  Evaluating compound critiquing recommenders: a real-user study , 2007, EC '07.

[71]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[72]  Boris Brandherm,et al.  Gumo - The General User Model Ontology , 2005, User Modeling.

[73]  Sanggil Kang,et al.  A channel recommendation system in mobile environment , 2006, IEEE Transactions on Consumer Electronics.

[74]  Georg Groh,et al.  Recommendations in taste related domains: collaborative filtering vs. social filtering , 2007, GROUP.

[75]  Jennifer Golbeck,et al.  Generating Predictive Movie Recommendations from Trust in Social Networks , 2006, iTrust.

[76]  Sean M. McNee,et al.  Beyond personalization: the next stage of recommender systems research , 2005, IUI '05.

[77]  Barry Smyth,et al.  Mobile information access: A study of emerging search behavior on the mobile Internet , 2007, TWEB.

[78]  Sineenard Pinyapong,et al.  Personalized Shopping Assistance Service at Ubiquitous Shop Space , 2008, 22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008).

[79]  Paolo Avesani,et al.  Trust-Aware Collaborative Filtering for Recommender Systems , 2004, CoopIS/DOA/ODBASE.

[80]  Rossano Schifanella,et al.  MobHinter: epidemic collaborative filtering and self-organization in mobile ad-hoc networks , 2008, RecSys '08.

[81]  Yang Wang,et al.  Performance Evaluation of a Privacy-Enhancing Framework for Personalized Websites , 2009, UMAP.

[82]  Markus Zanker,et al.  A Generic User Modeling Component for Hybrid Recommendation Strategies , 2009, 2009 IEEE Conference on Commerce and Enterprise Computing.

[83]  Naren Ramakrishnan,et al.  When being Weak is Brave: Privacy in Recommender Systems , 2001, ArXiv.

[84]  F. Ricci,et al.  Map-Based Interaction with a Conversational Mobile Recommender System , 2008, 2008 The Second International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies.

[85]  Rashmi R. Sinha,et al.  Comparing Recommendations Made by Online Systems and Friends , 2001, DELOS.

[86]  Tsvi Kuflik,et al.  Cross-representation mediation of user models , 2009, User Modeling and User-Adapted Interaction.

[87]  Kirsten Swearingen,et al.  Beyond Algorithms: An HCI Perspective on Recommender Systems , 2001 .

[88]  Ilya Mironov,et al.  Differentially private recommender systems: building privacy into the net , 2009, KDD.

[89]  John F. Canny,et al.  Collaborative filtering with privacy , 2002, Proceedings 2002 IEEE Symposium on Security and Privacy.

[90]  Gediminas Adomavicius,et al.  Incorporating contextual information in recommender systems using a multidimensional approach , 2005, TOIS.

[91]  Barry Smyth,et al.  Adaptive Selection: An Analysis of Critiquing and Preference-Based Feedback in Conversational Recommender Systems , 2006, Int. J. Electron. Commer..

[92]  Hinrich Schütze,et al.  Introduction to information retrieval , 2008 .

[93]  Greg Linden,et al.  Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .

[94]  Barry Smyth,et al.  Case-based recommender systems , 2005, The Knowledge Engineering Review.

[95]  Naren Ramakrishnan,et al.  Privacy Risks in Recommender Systems , 2001, IEEE Internet Comput..

[96]  John Riedl,et al.  Distributed Recommender Systems for Internet Commerce , 2005, Encyclopedia of Information Science and Technology.

[97]  Yoav Shoham,et al.  Fab: content-based, collaborative recommendation , 1997, CACM.

[98]  Ingoo Han,et al.  Mobile Advertisement Recommender System using Collaborative Filtering: MAR-CF , 2006 .

[99]  Gerhard Fischer,et al.  User Modeling in Human–Computer Interaction , 2001, User Modeling and User-Adapted Interaction.

[100]  Yoav Shoham,et al.  Content-Based, Collaborative Recommendation. , 1997 .

[101]  Bamshad Mobasher,et al.  Intelligent Techniques for Web Personalization , 2005, Lecture Notes in Computer Science.

[102]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[103]  Jae Kyu Lee,et al.  VISCORS: A Visual-Content Recommender for the Mobile Web , 2004, IEEE Intell. Syst..

[104]  Mi Zhang,et al.  Enhancing diversity in Top-N recommendation , 2009, RecSys '09.

[105]  Pattie Maes,et al.  Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.

[106]  R. A. Bailey,et al.  Design of comparative experiments , 2008 .

[107]  Sung-Bae Cho,et al.  Location-Based Recommendation System Using Bayesian User's Preference Model in Mobile Devices , 2007, UIC.

[108]  Fuguo Zhang,et al.  Research on Recommendation List Diversity of Recommender Systems , 2008, 2008 International Conference on Management of e-Commerce and e-Government.

[109]  Fan Yang,et al.  A scalable P2P recommender system based on distributed collaborative filtering , 2004, Expert Syst. Appl..

[110]  Tsvi Kuflik,et al.  Cross-Technique Mediation of User Models , 2006, AH.

[111]  Dimitris Plexousakis,et al.  Incremental Collaborative Filtering for Highly-Scalable Recommendation Algorithms , 2005, ISMIS.

[112]  Jun Wang,et al.  Distributed collaborative filtering for peer-to-peer file sharing systems , 2006, SAC.

[113]  Qin Yong,et al.  RAILWAY PASSENGER TRAFFIC VOLUME PREDICTION BASED ON NEURAL NETWORK , 2007 .

[114]  Barry Smyth,et al.  Similarity vs. Diversity , 2001, ICCBR.

[115]  Gilles Brassard,et al.  Alambic: a privacy-preserving recommender system for electronic commerce , 2008, International Journal of Information Security.

[116]  Pat Langley,et al.  A Personalized System for Conversational Recommendations , 2011, J. Artif. Intell. Res..

[117]  Daniel Billsus,et al.  Learning Probabilistic User Models , 1998 .

[118]  Tsvi Kuflik,et al.  Enhancing privacy and preserving accuracy of a distributed collaborative filtering , 2007, RecSys '07.

[119]  Reza Shokri,et al.  Preserving privacy in collaborative filtering through distributed aggregation of offline profiles , 2009, RecSys '09.

[120]  Francesco Ricci,et al.  Towards Learning User-Adaptive State Models in a Conversational Recommender System , 2007, LWA.

[121]  Benjamin Van Roy,et al.  Manipulation-resistant collaborative filtering systems , 2009, RecSys '09.

[122]  David McSherry,et al.  Diversity-Conscious Retrieval , 2002, ECCBR.

[123]  Gediminas Adomavicius,et al.  Personalization technologies , 2005, Commun. ACM.

[124]  Ido Guy,et al.  Personalized recommendation of social software items based on social relations , 2009, RecSys '09.

[125]  Peter Brusilovsky.  Methods and Techniques of Adaptive Hypermedia , 1996 .