A Time-Enhanced Topic Clustering Approach for News Web Search
Time is an important dimension of information space. It plays important roles in Web search, because most Web pages contain time information and many Web queries are time-related. Therefore, exploiting temporal information in Web pages has been a hotspot in the research on Web search. In this paper, the authors focus on the time-enhanced topic clustering issue for news search results. Traditional clustering algorithms are usually based on the common phrases of Web pages, and they have little consideration about using the temporal information of Web pages. From this perspective, they propose a time-enhanced topic clustering algorithm for news Web pages.