|
Title:
|
CONTEXT-AWARE RECOMMENDATION BASED ON MULTI-CRITERIA COMMUNITIES |
|
Author(s):
|
Thuy Ngoc Nguyen, An Te Nguyen |
|
ISBN:
|
978-989-8533-20-3 |
|
Editors:
|
Hans Weghorn |
|
Year:
|
2013 |
|
Edition:
|
Single |
|
Keywords:
|
Context-aware recommender system, collaborative filtering, multi-criteria communities, matrix factorization. |
|
Type:
|
Full Paper |
|
First Page:
|
19 |
|
Last Page:
|
26 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
Recommender systems (RSs) have been designed to solve the information overload problem by providing users with personalized recommendations, and now are becoming increasingly popular. Typically, RSs are based on collaborative filtering which is a technique predicting usersÂ’ interest by using opinions of like-minded users through their ratings on items. Recently, context-aware recommender systems (CARSs) have been developed to exploit additionally contextual information such as time, place and so on for providing better recommendations. However, the majority of CARSs use ratings as a unique criterion for building communities and ignore other available data. In this paper, rather than exploit single-criterion rating communities, we will incorporate multi-criteria communities to generate context-aware recommendations. The experiments show that our method performs better than other context-aware approaches. |
|
|
|
|
|
|
