DocumentCode :
888062
Title :
Digital content recommender on the Internet
Author :
Ha, Sung Ho
Author_Institution :
Kyungpook Nat. Univ., Taegu, South Korea
Volume :
21
Issue :
2
fYear :
2006
Firstpage :
70
Lastpage :
77
Abstract :
On the Web, where information is vast and users are numerous, personalization that aims to offer suitable information to suitable users is essential. To sustain their competitive advantage, portal sites attract many users´ attention by supplying personalized content. Most Web content providers offer all users the same content, failing to satisfy individual users´ needs. Providers should be able to offer suitable users suitable content with suitable speed. To do so, they must be able to identify customers, predict their interests, determine appropriate content, and deliver it in a personalized format during customers´ online sessions. In this paper, the author presents a digital-content recommender system that suggests Web content, in this case news articles, based on a user´s preference when he or she visits an Internet news site and reads the published articles. This recommender system creates a one-to-one relationship between the content provider and the user, raises the user´s satisfaction, and increases loyalty toward the content provider.
Keywords :
Internet; data mining; information filters; information resources; information retrieval; Internet news site; Web personalization; content providers; data mining; digital content recommender system; user preference; user satisfaction; Collaboration; Consumer electronics; Costs; History; Information filtering; Information filters; Navigation; Portals; Recommender systems; Web and internet services; data mining; digital content; personalization; recommender system;
fLanguage :
English
Journal_Title :
Intelligent Systems, IEEE
Publisher :
ieee
ISSN :
1541-1672
Type :
jour
DOI :
10.1109/MIS.2006.24
Filename :
1613823
Link To Document :
بازگشت