Welcome to the InfoSci Platform
Modified Collaborative Filtering Algorithm Based on ItemRank

Modified Collaborative Filtering Algorithm Based on ItemRank

Pengyuan Xu, Yanzhong Dang
Copyright: © 2014 |Volume: 5 |Issue: 1 |Pages: 9
ISSN: 1947-8208|EISSN: 1947-8216|EISBN13: 9781466655492|DOI: 10.4018/ijkss.2014010103
Cite Article Cite Article

MLA

Xu, Pengyuan, and Yanzhong Dang. "Modified Collaborative Filtering Algorithm Based on ItemRank." IJKSS vol.5, no.1 2014: pp.27-35. http://doi.org/10.4018/ijkss.2014010103

APA

Xu, P. & Dang, Y. (2014). Modified Collaborative Filtering Algorithm Based on ItemRank. International Journal of Knowledge and Systems Science (IJKSS), 5(1), 27-35. http://doi.org/10.4018/ijkss.2014010103

Chicago

Xu, Pengyuan, and Yanzhong Dang. "Modified Collaborative Filtering Algorithm Based on ItemRank," International Journal of Knowledge and Systems Science (IJKSS) 5, no.1: 27-35. http://doi.org/10.4018/ijkss.2014010103

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The most crucial component of collaborative filtering recommendation algorithm (CF) is the mechanism of calculating similarities among items or users. In this paper, a new CF algorithm based on ItemRank Similarity (IRS) is proposed, which extracts items' quality characteristics from the similar matrix. The corresponding algorithmic accuracy is measured by the ranking score, precision, recall and F-measure. This algorithm provides remarkably higher accurate predictions than other modified CF algorithm.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.