Title :
Article Recommender for Feed Readers with a Loss Compensation Based on the TF-IDF Weight
Author :
Yokota, Daichi ; Fujita, Satoshi
Author_Institution :
Dept. of Inf. Eng., Hiroshima Univ., Hiroshima, Japan
Abstract :
In this paper, we improve the accuracy of item-based collaborative filtering by introducing a loss compensation based on the TF-IDF weight. The proposed scheme is implemented as a part of a feed reader, and is evaluated through the feedback from users.
Keywords :
information filtering; TF-IDF weight; article recommender; feed readers; item-based collaborative filtering; loss compensation; Collaborative Filtering; Recommendation; TF-IDF;
Conference_Titel :
Networking and Computing (ICNC), 2010 First International Conference on
Conference_Location :
Higashi-Hiroshima
Print_ISBN :
978-1-4244-8918-3
Electronic_ISBN :
978-0-7695-4277-5
DOI :
10.1109/IC-NC.2010.21
