Abstract. Many current recommender systems exploit textual annotations (tags) provided by users to retrieve and suggest online contents. The text-based recommendation provided by t...
Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, ...
— recently, search engines become more critical for finding information over the World Wide Web where web content growing fast, the user's satisfaction of search engine resu...
Hamada M. Zahera, Gamal F. El-Hady, W. F. Abd El-W...
We propose a novel hybrid recommendation model in which user preferences and item features are described in terms of semantic concepts defined in domain ontologies. The exploitati...
Repositories like arXiv1 and knowledge bases like CiteSeer2 are increasingly becoming central to academicians and researchers. However, current systems provide too little semantic...
In this paper, we describe a buzz-based recommender system based on a large source of queries in an eCommerce application. The system detects bursts in query trends. These bursts ...