An algorithmic framework for performing collaborative filtering

被引：1300

作者：

Herlocker, JL ^{[1
]}

Konstan, JA ^{[1
]}

Borchers, A ^{[1
]}

Riedl, J ^{[1
]}

机构：

[1] Univ Minnesota, Dept Comp Sci & Engn, Minneapolis, MN 55455 USA

来源：

SIGIR'99: PROCEEDINGS OF 22ND INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL | 1999年

关键词：

D O I：

10.1145/312624.312682

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Automated collaborative filtering is quickly becoming a popular technique for reducing information overload often as a technique to complement content-based information filtering systems. In this paper we present an algorithmic framework for performing collaborative filtering and new algorithmic elements that increase the accuracy of collaborative prediction algorithms. We then present a set of recommendations on selection of the right collaborative filtering algorithmic components.

引用

页码：230 / 237

页数：8

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