Title :
The design and implementation of personalized news recommendation system
Author :
Xuejiao Han ; Wenqian Shang ; Shuchao Feng
Author_Institution :
Sch. of Comput. Sci., Commun. Univ. of China, Beijing, China
fDate :
June 28 2015-July 1 2015
Abstract :
With the development of network information technology, a lot of news comes into the view of Internet users. We have entered the “information overload” era. So how to find useful information becomes more and more important. Personalized news recommendation is a kind of technology to find the news that users want to get urgently. It is based on the browsing history of many users. Through analysis of their interests, we can realize the personalized news recommendation for different people. In our system, we propose an improved association rules. This method associates with collaborative filtering algorithm to form a hybrid recommendation algorithm. Through using this new algorithm, we can generate recommendation lists and realize the personalized news recommendation.
Keywords :
Internet; collaborative filtering; data mining; recommender systems; Internet users; association rules; browsing history; collaborative filtering algorithm; hybrid recommendation algorithm; information overload; network information technology; personalized news recommendation system; recommendation list generation; Collaboration; Databases; Education; Filtering; Filtering algorithms; association rules; collaborative filtering algorithm; hybrid recommendation algorithm; personalized news recommendation;
Conference_Titel :
Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on
Conference_Location :
Las Vegas, NV
DOI :
10.1109/ICIS.2015.7166653
