Personalization and Recommender Systems
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Gediminas Adomavicius | Zan Huang | Alexander Tuzhilin | Zan Huang | A. Tuzhilin | G. Adomavicius | Alexander Tuzhilin
[1] MAGDALINI EIRINAKI,et al. Web mining for web personalization , 2003, TOIT.
[2] Frank van Harmelen,et al. Web Ontology Language: OWL , 2004, Handbook on Ontologies.
[3] Luo Si,et al. A study of mixture models for collaborative filtering , 2006, Information Retrieval.
[4] Elaine Rich,et al. User Modeling via Stereotypes , 1998, Cogn. Sci..
[5] Tianyi Jiang,et al. Improving Personalization Solutions through Optimal Segmentation of Customer Bases , 2006, IEEE Transactions on Knowledge and Data Engineering.
[6] Michael J. Pazzani,et al. A personal news agent that talks, learns and explains , 1999, AGENTS '99.
[7] James Bennett,et al. The Netflix Prize , 2007 .
[8] Bradley N. Miller,et al. Using filtering agents to improve prediction quality in the GroupLens research collaborative filtering system , 1998, CSCW '98.
[9] Hsinchun Chen,et al. Analyzing Consumer-Product Graphs: Empirical Findings and Applications in Recommender Systems , 2005, Manag. Sci..
[10] Kartik Hosanagar,et al. Blockbuster Culture's Next Rise or Fall: The Impact of Recommender Systems on Sales Diversity , 2007, Manag. Sci..
[11] John Riedl,et al. Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.
[12] Eric Horvitz,et al. Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach , 2000, UAI.
[13] Michael J. Pazzani,et al. Learning Collaborative Information Filters , 1998, ICML.
[14] Ramnath K. Chellappa,et al. Personalization versus Privacy: An Empirical Examination of the Online Consumer’s Dilemma , 2005, Inf. Technol. Manag..
[15] Peter E. Rossi,et al. The Value of Purchase History Data in Target Marketing , 1996 .
[16] John Riedl,et al. E-Commerce Recommendation Applications , 2004, Data Mining and Knowledge Discovery.
[17] Arvind K. Tripathi,et al. Design of a shopbot and recommender system for bundle purchases , 2006, Decis. Support Syst..
[18] Robin Cohen,et al. Hybrid Recommender Systems for Electronic Commerce , 2000 .
[19] Chrysanthos Dellarocas,et al. The Digitization of Word-of-Mouth: Promise and Challenges of Online Feedback Mechanisms , 2003, Manag. Sci..
[20] Tsvi Kuflik,et al. Privacy-enhanced collaborative filtering , 2005 .
[21] John Riedl,et al. Application of Dimensionality Reduction in Recommender System - A Case Study , 2000 .
[22] Neil J. Hurley,et al. Collaborative recommendation: A robustness analysis , 2004, TOIT.
[23] Naren Ramakrishnan,et al. Scouts, promoters, and connectors: The roles of ratings in nearest-neighbor collaborative filtering , 2007, TWEB.
[24] William W. Cohen,et al. Recommendation as Classification: Using Social and Content-Based Information in Recommendation , 1998, AAAI/IAAI.
[25] Olfa Nasraoui,et al. World Wide Web Personalization , 2005 .
[26] Mark Rosenstein,et al. Recommending and evaluating choices in a virtual community of use , 1995, CHI '95.
[27] Robin D. Burke,et al. Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.
[28] Manfred K. Warmuth,et al. The Weighted Majority Algorithm , 1994, Inf. Comput..
[29] Anindya Ghose,et al. Personalized Pricing and Quality Differentiation , 2005, Manag. Sci..
[30] Sumit Sarkar,et al. The Role of the Management Sciences in Research on Personalization , 2003, Manag. Sci..
[31] Wolfgang Wörndl,et al. A Hybrid Recommender System for Context-aware Recommendations of Mobile Applications , 2007, 2007 IEEE 23rd International Conference on Data Engineering Workshop.
[32] R. Blattberg,et al. Database marketing , 1997 .
[33] Tianyi Jiang,et al. Segmenting Customers from Population to Individuals: Does 1-to-1 Keep Your Customers Forever? , 2006, IEEE Transactions on Knowledge and Data Engineering.
[34] Hans-Peter Kriegel,et al. Ieee Transactions on Knowledge and Data Engineering Probabilistic Memory-based Collaborative Filtering , 2022 .
[35] Michael J. Pazzani,et al. Learning and Revising User Profiles: The Identification of Interesting Web Sites , 1997, Machine Learning.
[36] Dennis McLeod,et al. Yoda: An Accurate and Scalable Web-Based Recommendation System , 2001, CoopIS.
[37] M. Wedel,et al. Market Segmentation: Conceptual and Methodological Foundations , 1997 .
[38] Tianyi Jiang,et al. Dynamic Micro Targeting: Fitness-Based Approach to Predicting Individual Preferences , 2007, ICDM.
[39] Joseph A. Konstan,et al. Content-Independent Task-Focused Recommendation , 2001, IEEE Internet Comput..
[40] Gediminas Adomavicius,et al. Incorporating contextual information in recommender systems using a multidimensional approach , 2005, TOIS.
[41] Lillian N. Cassel,et al. Client Side Personalization , 2001, DELOS.
[42] Jaideep Srivastava,et al. Web usage mining: discovery and applications of usage patterns from Web data , 2000, SKDD.
[43] Arvind Rangaswamy,et al. From Many to One: Personalized Product Fulfillment Systems , 2002 .
[44] Don Peppers,et al. The One to One Future , 1993 .
[45] K. Sudhir,et al. Optimal Marketing Strategies for a Customer Data Intermediary , 2007 .
[46] Loriene Roy,et al. Content-based book recommending using learning for text categorization , 1999, DL '00.
[47] Edward I. George,et al. A bayesian model for collaborative filtering , 1999, AISTATS.
[48] CroftW. Bruce,et al. Information filtering and information retrieval , 1992 .
[49] Georgios Paliouras,et al. Web Usage Mining as a Tool for Personalization: A Survey , 2003, User Modeling and User-Adapted Interaction.
[50] Raymond J. Mooney and Paul N. Bennett and Loriene Roy,et al. Book Recommending Using Text Categorization with Extracted Information , 1998 .
[51] H. Sebastian Seung,et al. Selective Sampling Using the Query by Committee Algorithm , 1997, Machine Learning.
[52] G. Linden,et al. People Who Read This Article Also Read... , 2008, IEEE Spectrum.
[53] Michael J. Pazzani,et al. User Modeling for Adaptive News Access , 2000, User Modeling and User-Adapted Interaction.
[54] Il Im,et al. A framework for classifying personalization scheme used on e-commerce Websites , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.
[55] John Riedl,et al. Combining Collaborative Filtering with Personal Agents for Better Recommendations , 1999, AAAI/IAAI.
[56] Feng Qiu,et al. Automatic identification of user interest for personalized search , 2006, WWW '06.
[57] Benjamin M. Marlin,et al. Modeling User Rating Profiles For Collaborative Filtering , 2003, NIPS.
[58] Paul H. Zipkin,et al. The Limits of Mass Customization , 2001 .
[59] George Karypis,et al. Item-based top-N recommendation algorithms , 2004, TOIS.
[60] Bradley N. Miller,et al. GroupLens: applying collaborative filtering to Usenet news , 1997, CACM.
[61] G. Häubl,et al. Preference Construction and Persistence in Digital Marketplaces: The Role of Electronic Recommendation Agents , 2003 .
[62] Barry Smyth,et al. Case-Based Recommendation , 2007, The Adaptive Web.
[63] John Riedl,et al. GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.
[64] K. Arrow. Social Choice and Individual Values , 1951 .
[65] Amit P. Sheth,et al. Semantic Content Management for Enterprises and the Web , 2001 .
[66] G. Nürnberger. Approximation by Spline Functions , 1989 .
[67] Zan Huang,et al. Selectively acquiring ratings for product recommendation , 2007, ICEC.
[68] Raymond J. Mooney,et al. Content-boosted collaborative filtering for improved recommendations , 2002, AAAI/IAAI.
[69] Judith Masthoff,et al. A Survey of Explanations in Recommender Systems , 2007, 2007 IEEE 23rd International Conference on Data Engineering Workshop.
[70] John Riedl,et al. PolyLens: A recommender system for groups of user , 2001, ECSCW.
[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] Thomas Hofmann,et al. Latent Class Models for Collaborative Filtering , 1999, IJCAI.
[73] Thomas Hofmann,et al. Latent semantic models for collaborative filtering , 2004, TOIS.
[74] I. Simonson,et al. Determinants of Customers' Responses to Customized Offers: Conceptual Framework and Research Propositions , 2003 .
[75] Barry Smyth,et al. Recommendation to Groups , 2007, The Adaptive Web.
[76] K. Srinivasan,et al. Learning About Customers Without Asking , 2002 .
[77] Kenta Oku,et al. Context-Aware SVM for Context-Dependent Information Recommendation , 2006, 7th International Conference on Mobile Data Management (MDM'06).
[78] Gediminas Adomavicius,et al. Personalization technologies , 2005, Commun. ACM.
[79] Matthias Ehrgott,et al. Multicriteria Optimization , 2005 .
[80] Sergio A. Alvarez,et al. Efficient Adaptive-Support Association Rule Mining for Recommender Systems , 2004, Data Mining and Knowledge Discovery.
[81] Anindya Datta,et al. A Conceptual Model and Algebra for On-Line Analytical Processing in Decision Support Databases , 2001, Inf. Syst. Res..
[82] R. Schaback,et al. Characterization and construction of radial basis functions , 2001 .
[83] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[84] Z. John Zhang,et al. Competitive One-to-One Promotions , 2002, Manag. Sci..
[85] M. Buhmann. Multivariate Approximation and Applications: Approximation and interpolation with radial functions , 2001 .
[86] Cynthia A. Thompson,et al. Personalized Conversational Case-Based Recommendation , 2000, EWCBR.
[87] Luo Si,et al. Collaborative filtering with decoupled models for preferences and ratings , 2003, CIKM '03.
[88] David M. Pennock,et al. Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments , 2001, UAI.
[89] M. Powell,et al. Approximation theory and methods , 1984 .
[90] George Karypis,et al. Evaluation of Item-Based Top-N Recommendation Algorithms , 2001, CIKM '01.
[91] Boi Faltings,et al. Conversational recommenders with adaptive suggestions , 2007, RecSys '07.
[92] Li Chen,et al. Trust building with explanation interfaces , 2006, IUI '06.
[93] Michel Wedel,et al. Leveraging Missing Ratings to Improve Online Recommendation Systems , 2006 .
[94] Batul J. Mirza,et al. Jumping Connections: A Graph-Theoretic Model for Recommender Systems , 2001 .
[95] Michael J. Pazzani,et al. A Framework for Collaborative, Content-Based and Demographic Filtering , 1999, Artificial Intelligence Review.
[96] David D. Lewis,et al. Heterogeneous Uncertainty Sampling for Supervised Learning , 1994, ICML.
[97] Hsinchun Chen,et al. A graph model for E-commerce recommender systems , 2004, J. Assoc. Inf. Sci. Technol..
[98] Doug Riecken,et al. Introduction: personalized views of personalization , 2000, CACM.
[99] Yoram Singer,et al. Learning to Order Things , 1997, NIPS.
[100] Osmar R. Zaïane,et al. Combining Usage, Content, and Structure Data to Improve Web Site Recommendation , 2004, EC-Web.
[101] Gediminas Adomavicius,et al. Using Data Mining Methods to Build Customer Profiles , 2001, Computer.
[102] Zhou Xingshe,et al. An adaptive in-vehicle multimedia recommender for group users , 2005, 2005 IEEE 61st Vehicular Technology Conference.
[103] Yoav Shoham,et al. Fab: content-based, collaborative recommendation , 1997, CACM.
[104] David A. Cohn,et al. Active Learning with Statistical Models , 1996, NIPS.
[105] Bamshad Mobasher,et al. Intelligent Techniques for Web Personalization , 2005, Lecture Notes in Computer Science.
[106] Gediminas Adomavicius,et al. Multidimensional Recommender Systems: A Data Warehousing Approach , 2001, WELCOM.
[107] Heikki Mannila,et al. Discovering Frequent Episodes in Sequences , 1995, KDD.
[108] Stuart E. Middleton,et al. Ontological user profiling in recommender systems , 2004, TOIS.
[109] Gediminas Adomavicius,et al. Integrating User Behavior and Collaborative Methods in Recommender Systems , 2004 .
[110] John Riedl,et al. Shilling recommender systems for fun and profit , 2004, WWW '04.
[111] Virgílio A. F. Almeida,et al. Masks: Bringing Anonymity and Personalization Together , 2003, IEEE Secur. Priv..
[112] David M. Pennock,et al. Collaborative filtering with maximum entropy , 2004, IEEE Intelligent Systems.
[113] Mark Claypool,et al. Combining Content-Based and Collaborative Filters in an Online Newspaper , 1999, SIGIR 1999.
[114] Chih-Hung Liu,et al. Intelligent agent-based systems for personalized recommendations in Internet commerce , 2002, Expert Syst. Appl..
[115] J. J. Rocchio,et al. Relevance feedback in information retrieval , 1971 .
[116] Ah Chung Tsoi,et al. Computing customized page ranks , 2006, TOIT.
[117] Gediminas Adomavicius,et al. An Architecture of e-Butler: A Consumer-Centric Online Personalization System , 2002, Int. J. Comput. Intell. Appl..
[118] F. Dwyer. Customer lifetime valuation to support marketing decision making , 1997 .
[119] David A. Cohn,et al. Improving generalization with active learning , 1994, Machine Learning.
[120] Akhmed Umyarov,et al. Leveraging aggregate ratings for better recommendations , 2007, RecSys '07.
[121] Zhiqiang Zheng,et al. Personalization from incomplete data: what you don't know can hurt , 2001, KDD '01.
[122] Surajit Chaudhuri,et al. An overview of data warehousing and OLAP technology , 1997, SGMD.
[123] Michael R. Solomon,et al. Predictability and Personalization in the Service Encounter , 1987 .
[124] Krishna Kumar,et al. Learn Sesame, a Learning Agent Engine , 1997, Appl. Artif. Intell..
[125] David Heckerman,et al. Empirical Analysis of Predictive Algorithms for Collaborative Filtering , 1998, UAI.
[126] Sean M. McNee,et al. Getting to know you: learning new user preferences in recommender systems , 2002, IUI '02.
[127] Paul Resnick,et al. Recommender systems , 1997, CACM.
[128] Anne Rogers,et al. Hancock: a language for extracting signatures from data streams , 2000, KDD '00.
[129] Pattie Maes,et al. Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.
[130] Douglas B. Terry,et al. Using collaborative filtering to weave an information tapestry , 1992, CACM.
[131] Gerard Salton,et al. Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer , 1989 .
[132] Pinar Keskinocak,et al. Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions , 2003, IEEE Engineering Management Review.
[133] John Riedl,et al. Explaining collaborative filtering recommendations , 2000, CSCW '00.
[134] Craig Boutilier,et al. Active Collaborative Filtering , 2002, UAI.
[135] Rajiv M. Dewan,et al. Adoption of Internet-Based Product Customization and Pricing Strategies , 2000 .
[136] Gediminas Adomavicius,et al. New Recommendation Techniques for Multicriteria Rating Systems , 2007, IEEE Intelligent Systems.
[137] Steffen Staab,et al. Handbook on Ontologies in Information Systems , 2003 .
[138] David Maxwell Chickering,et al. Dependency Networks for Inference, Collaborative Filtering, and Data Visualization , 2000, J. Mach. Learn. Res..
[139] Alfred Kobsa,et al. Privacy-Enhanced Web Personalization , 2007, The Adaptive Web.
[140] Alexander Tuzhilin,et al. Personalization in Context: Does Context Matter When Building Personalized Customer Models? , 2006, Sixth International Conference on Data Mining (ICDM'06).
[141] Luo Si,et al. Preference-based Graphic Models for Collaborative Filtering , 2002, UAI.
[142] Guy Shani,et al. An MDP-Based Recommender System , 2002, J. Mach. Learn. Res..
[143] Greg Linden,et al. Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .
[144] Tao Luo,et al. Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization , 2004, Data Mining and Knowledge Discovery.
[145] Hsinchun Chen,et al. Link prediction approach to collaborative filtering , 2005, Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '05).
[146] Naren Ramakrishnan,et al. Privacy Risks in Recommender Systems , 2001, IEEE Internet Comput..
[147] Jaideep Srivastava,et al. Automatic personalization based on Web usage mining , 2000, CACM.
[148] David M. Pennock,et al. Categories and Subject Descriptors , 2001 .
[149] John Riedl,et al. Analysis of recommendation algorithms for e-commerce , 2000, EC '00.
[150] Ivan Koychev,et al. Learning to recommend from positive evidence , 2000, IUI '00.
[151] Hsinchun Chen,et al. Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering , 2004, TOIS.
[152] Wenliang Du,et al. Privacy-preserving collaborative filtering using randomized perturbation techniques , 2003, Third IEEE International Conference on Data Mining.
[153] Djemel Ziou,et al. A Graphical Model for Context-Aware Visual Content Recommendation , 2008, IEEE Transactions on Multimedia.
[154] Douglas W. Oard,et al. Implicit Feedback for Recommender Systems , 1998 .
[155] Naoki Abe,et al. Collaborative Filtering Using Weighted Majority Prediction Algorithms , 1998, ICML.
[156] Chris Anderson,et al. The Long Tail: Why the Future of Business is Selling Less of More , 2006 .
[157] Jari Vesanen,et al. Building bridges for personalization: A process model for marketing , 2006 .
[158] Jun Wang,et al. Unifying user-based and item-based collaborative filtering approaches by similarity fusion , 2006, SIGIR.
[159] Ganesh Iyer,et al. Research Note Consumer Addressability and Customized Pricing , 2002 .
[160] Heikki Mannila,et al. Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction , 2001, KDD '01.
[161] Gediminas Adomavicius,et al. Expert-Driven Validation of Rule-Based User Models in Personalization Applications , 2004, Data Mining and Knowledge Discovery.
[162] Yizhak Idan,et al. Customer lifetime value modeling and its use for customer retention planning , 2002, KDD.
[163] Jonathan L. Herlocker,et al. Evaluating collaborative filtering recommender systems , 2004, TOIS.
[164] Yoram Singer,et al. An Efficient Boosting Algorithm for Combining Preferences by , 2013 .
[165] Anthony Jameson,et al. More than the sum of its members: challenges for group recommender systems , 2004, AVI.
[166] Neil J. Hurley,et al. Attacking Recommender Systems: A Cost-Benefit Analysis , 2007, IEEE Intelligent Systems.
[167] Kenneth Y. Goldberg,et al. Eigentaste: A Constant Time Collaborative Filtering Algorithm , 2001, Information Retrieval.
[168] Jean Duchon,et al. Splines minimizing rotation-invariant semi-norms in Sobolev spaces , 1976, Constructive Theory of Functions of Several Variables.
[169] P. K. Kannan,et al. Pricing of Information Products on Online Servers: Issues, Models, and Analysis , 2002, Manag. Sci..
[170] Francesco Ricci,et al. MobyRek: a conversational recommender system for on-the-move travellers. , 2006 .
[171] Balaji Padmanabhan,et al. Evaluation of Online Personalization Systems: A Survey of Evaluation Schemes and a Knowledge-Based Approach , 2005 .
[172] Loren Terveen,et al. PHOAKS: a system for sharing recommendations , 1997, CACM.
[173] Balaji Padmanabhan,et al. On the Use of Optimization for Data Mining: Theoretical Interactions and eCRM Opportunities , 2003, Manag. Sci..
[174] James D. Hess,et al. Customized Products: A Competitive Analysis , 2005 .
[175] J. Ben Schafer,et al. DynamicLens: A Dynamic User-Interface for a Meta-Recommendation System , 2005 .
[176] David C. Schmittlein,et al. Counting Your Customers: Who-Are They and What Will They Do Next? , 1987 .
[177] Yi Zhang,et al. Novelty and redundancy detection in adaptive filtering , 2002, SIGIR '02.
[178] Don Peppers,et al. Managing Customer Relationships: A Strategic Framework , 2004 .
[179] Ken Lang,et al. NewsWeeder: Learning to Filter Netnews , 1995, ICML.
[180] Francesco Ricci,et al. Learning and adaptivity in interactive recommender systems , 2007, ICEC.
[181] Hsinchun Chen,et al. A Unified Recommendation Framework Based on Probabilistic Relational Models , 2005 .
[182] Maurice D. Mulvenna,et al. Personalization on the Net using Web mining: introduction , 2000, CACM.
[183] Greg Linden,et al. Interactive Assessment of User Preference Models: The Automated Travel Assistant , 1997 .
[184] Ravi Kumar,et al. Recommendation systems: a probabilistic analysis , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).
[185] Z. John Zhang,et al. Individual Marketing with Imperfect Targetability , 2000 .
[186] S. Kotha. Mass Customization: The New Frontier in Business Competition , 1992 .