Jester 2.0: Evaluation of a new linear time collaborative filtering algorithm

被引：16

作者：

Gupta, D ^{[1
]}

Digiovanni, M ^{[1
]}

Narita, H ^{[1
]}

Goldberg, K ^{[1
]}

机构：

[1] Univ Calif Berkeley, IEOR Dept, Alpha Lab, Berkeley, CA 94720 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：

10.1145/312624.312718

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Jester is a WWW-based system that allows users to retrieve jokes based on their ratings of sample jokes. Our emphasis is on a new principal component analysis (PCA) and clustering-based linear time collaborative filtering algorithm for efficient and effective personalized information retrieval. Let m be the number of users in the database (currently over 12000) and n be the number of jokes rated by a user to characterize his or her preference (currently 10). We report new results comparing Jester 1.0's O(nm) algorithm with Jester 2.0's O(n) algorithm: the latter improves the retrieval effectiveness by more than 40% and reduces retrieval time by a factor of 12,000.

引用

页码：291 / 292

页数：2