Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl  Home/Search
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Abstract: Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live interaction. These systems, especially the k-nearest neighbor collaborative filtering based ones, are achieving widespread success on the Web. The tremendous growth in the amount of available information and the number of visitors to Web sites in recent years poses some key challenges for recommender systems. These are: producing... (Update)
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BibTeX entry: (Update)
B. M. Sarwar, G. Karypis, J. A. Konstan, and J. Riedl. Item-based collaborative filtering recommendation algorithms. In Proc. of the 10th International World Wide Web Conference (WWW10), Hong Kong, May 2001. http://citeseer.ist.psu.edu/article/sarwar01itembased.html More
@inproceedings{ sarwar01itembased,
author = "Badrul M. Sarwar and George Karypis and Joseph A. Konstan and John Reidl",
title = "Item-based collaborative filtering recommendation algorithms",
booktitle = "World Wide Web",
pages = "285-295",
year = "2001",
url = "citeseer.ist.psu.edu/article/sarwar01itembased.html" }
Citations (may not include all citations):568 Indexing by Latent Semantic Analysis - Deerwester, Dumais et al. - 1990
474 Advances in Knowledge Discovery and Data Mining (context) - Fayyad, Piatetsky-Shapiro et al. - 1996
254 GroupLens: An Open Architecture for Collaborative Filtering .. - Resnick, Iacovou et al. - 1994
226 Using Collaborative Filtering to Weave an Information Tapest.. (context) - Goldberg, Nichols et al. - 1992
192 Using Linear Algebra for Intelligent Information Retrieval - Berry, Dumais et al. - 1995
188 Empirical Analysis of Predictive Algorithms for Collaborativ.. - Breese, Heckerman et al. - 1998
159 Recommender Systems (context) - Resnick, Varian - 1997
155 GroupLens: Applying Collaborative Filtering to Usenet News - Konstan, Miller et al. - 1997
111 Recommending and Evaluating Choices in a Virtual Community o.. (context) - Hill, Stead et al. - 1995
102 An Algorithmic Framework for Performing Collaborative Filter.. (context) - Herlocker, Konstan et al. - 1999
92 Social Information Filtering: Algorithms for Automating 'Wor.. - Shardanand, Maes - 1995
80 Learning Collaborative Information Filters - Billsus, Pazzani - 1998
65 PHOAKS: A System for Sharing Recommendations - Terveen, Hill et al. - 1997
65 Recommendation as Classification: Using Social and Content-b.. - Basu, Hirsh et al. - 1998
52 Combining Collaborative Filtering With Personal Agents for B.. - Good, Schafer et al. - 1999
50 Application of Dimensionality Reduction in Recommender Syste.. - Sarwar, Karypis et al. - 2000
41 Using Filtering Agents to Improve Prediction Quality in the .. - Sarwar, Konstan et al. - 1998
31 Clustering Methods for Collaborative Filtering - Ungar, Foster - 1998
30 Analysis of Recommendation Algorithms for E-Commerce - Sarwar, Karypis et al. - 2000
28 Data Mining for Direct Marketing: Problems and Solutions - Ling, Li - 1998
24 Recommender Systems in E-Commerce - Schafer, Konstan et al. - 1999
18 Evaluation of Item-Based Top-N Recommendation Algorithms - Karypis - 2000
14 Mining Business Databases - Brachman, Khabaza et al. - 1996
14 Zero Defections: Quality Comes to Services (context) - Reichheld, Sasser - 1990
12 The One to One Future : Building Relationships One Customer .. (context) - Peppers, Rogers - 1997
7 Factor Analysis: An Applied Approach (context) - Cureton, D'Agostino - 1983
7 Loyalty-Based Management (context) - Reichheld - 1993
6 Understanding and Improving Automated Collaborative Filterin.. (context) - Herlocker - 2000
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