Building search context with sliding window for information seeking
Jie Yu, Jie Gong, Fangfang Liu · 2011
With the rapid development of Internet, how to obtain and represent personalized information in user's activity of information seeking is a key issue in information retrieval. This paper presents a novel method to build personalized search context which represents semantic background in user's information seeking. Search context is composed of terms and semantic relation which is extracted based on Web-snippets returned from search engine. In addition, sliding window algorithm is applied in mining semantic relation in search context. Experimental results demonstrate the effectiveness of our method in clustering algorithm which plays an important role in information retrieval. It can be seen that this method has a brilliant perspective in the field of personalized search.