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Refereed Papers
Track: Search: Applications
Paper Title:
Automatic Online News Issue Construction in Web Environment
Authors:
- Canhui Wang(Tsinghua University)
- Min Zhang(Tsinghua University)
- Shaoping Ma(Tsinghua University)
- Liyun Ru(Tsinghua University)
Abstract:
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.
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