In many cases, rather than a keyword search, people intend to see what is going on through the Internet. Then the integrated comprehensive information on news topics is necessary, which we called news issues, including the background, history, current progress, different opinions and discussions, etc. Traditionally, news issues are manually generated by website editors. It is quite a time-consuming hard work, and hence real-time update is difficult to perform. In this paper, a three-step automatic online algorithm for news issue construction is proposed. The first step is a topic detection process, in which newly appearing stories are clustered into new topic candidates. The second step is a topic tracking process, where those candidates are compared with previous topics, either merged into old ones or generating a new one. In the final step, news issues are constructed by the combination of related topics and updated by the insertion of new topics. An automatic online news issue construction process under practical Web circumstances is simulated to perform news issue construction experiments. F-measure of the best results is either above (topic detection) or close to (topic detection and tracking) 90%. Four news issue construction results are successfully generated in different time granularities: one meets the needs like "what's new", and the other three will answer questions like "what's hot" or "what's going on". Through the proposed algorithm, news issues can be effectively and automatically constructed with real-time update, and lots of human efforts will be released from tedious manual work.
The approach of our work is more related to REF , it propose a novel automatic online algorithm for news issue construction, through which news issues can be automatically constructed with real-time update, and lots of human efforts will be released from tedious manual work.
Automatic online news issue construction in web environment
In Proc. of WWW08
Computer Science