Title :
The study in ranking method for web entity
Author_Institution :
Inf. Technol. Coll., Eastern Liaoning Univ., Dandong, China
Abstract :
Along with the rapidly development of the information retrieval and web technology, web entity retrieval has become a new popular way for getting specific information, such as looking for a book or a movie. Like document retrieval, generally there are too many results returned for a query, so ranking is still a necessary step during the entity retrieval process. This paper will focus on the ranking problem for web entity. Two methods are proposed, the first one will rank the results by a relevance score directly and the second one get the final ranking list by a training model. To compare the effective of the two methods, by the same features, we perform related experiments. According to the test data from real web pages, we test the precise of each method and get the conclusion at last.
Keywords :
Internet; information retrieval; document retrieval; information retrieval; ranking method; relevance score; training model; web entity retrieval; web pages; web technology; Chemistry; Information retrieval; Research and development; Support vector machines; Training; Training data; entity retrieval; feature; ranking; relevance score;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569354