Authors:
Özlem Özgöbek
1
;
Jon Atle Gulla
2
and
R. Cenk Erdur
3
Affiliations:
1
NTNU and Ege University, Norway
;
2
NTNU, Norway
;
3
Ege University, Turkey
Keyword(s):
Recommender Systems, News Source, News Recommendation.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Recommendation Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Software Agents and Internet Computing
Abstract:
Recommender systems aim to deliver the most suitable item to the user without the manual effort of the
user. It is possible to see the applications of recommender systems in a lot of different domains like music,
movies, shopping and news. Recommender system development have many challenges. But the dynamic and
diverse environment of news domain makes news recommender systems a little bit more challenging than other
domains. During the recommendation process of news articles, personalization and analysis of news content
plays an important role. But beyond recommending the articles itself, we think that where the news come from
is also very important. Different news sources have their own style, view and way of expression and they may
give the user a complete, balanced and wide perspective of news stories. In this paper we explain the need
for including news sources in news recommendation and propose a news source recommendation method by
finding out the implicit relations and similar
ities between news sources by using semantics and association
rules.
(More)