Academic Journals Database
Disseminating quality controlled scientific knowledge

Proposing a New Metric for Collaborative Filtering

Author(s): Arash Bahrehmand | Reza Rafeh

Journal: Journal of Software Engineering and Applications
ISSN 1945-3116

Volume: 04;
Issue: 07;
Start page: 411;
Date: 2011;
Original page

Keywords: Recommendation Systems | Collaborative filtering | Similarity Metric

The aim of a recommender system is filtering the enormous quantity of information to obtain useful information based on the user’s interest. Collaborative filtering is a technique which improves the efficiency of recommendation systems by considering the similarity between users. The similarity is based on the given rating to data by similar users. However, user’s interest may change over time. In this paper we propose an adaptive metric which considers the time in measuring the similarity of users. The experimental results show that our approach is more accurate than the traditional collaborative filtering algorithm.
Affiliate Program     

Tango Jona
Tangokurs Rapperswil-Jona