J. Konstan

Publications280
h-index75
Citations43,830
Highly Influential Citations3,180
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Top 100 relevant results, sorted by most influential
Item-based collaborative filtering recommendation algorithms
Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live interaction. These systems,… Expand
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Evaluating collaborative filtering recommender systems
Recommender systems have been evaluated in many, often incomparable, ways. In this article, we review the key decisions in evaluating collaborative filtering recommender systems: the user tasks being… Expand
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The MovieLens Datasets: History and Context
The MovieLens datasets are widely used in education, research, and industry. They are downloaded hundreds of thousands of times each year, reflecting their use in popular press programming books,… Expand
  • 1,570
  • 202
Analysis of recommendation algorithms for e-commerce
ABSTRACT Re ommender systems apply statisti al and knowledge disovery te hniques to the problem of making produ t re ommendations during a live ustomer intera tion and they are a hieving widespread… Expand
  • 1,859
  • 120
GroupLens: applying collaborative filtering to Usenet news
newsgroups carry a wide enough spread of messages to make most individuals consider Usenet news to be a high noise information resource. Furthermore, each user values a different set of messages.… Expand
  • 2,478
  • 119
Improving recommendation lists through topic diversification
In this work we present topic diversification, a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user's complete spectrum of interests. Though… Expand
  • 1,467
  • 113
An algorithmic framework for performing collaborative filtering
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial… Expand
  • 1,087
  • 101
Application of Dimensionality Reduction in Recommender System - A Case Study
Abstract : We investigate the use of dimensionality reduction to improve performance for a new class of data analysis software called "recommender systems" Recommender systems apply knowledge… Expand
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  • 100
Explaining collaborative filtering recommendations
Automated collaborative filtering (ACF) systems predict a person's affinity for items or information by connecting that person's recorded interests with the recorded interests of a community of… Expand
  • 1,430
  • 97
An Algorithmic Framework for Performing Collaborative Filtering
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