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2008
ACM

Mining multi-faceted overviews of arbitrary topics in a text collection

9 years 2 months ago
Mining multi-faceted overviews of arbitrary topics in a text collection
A common task in many text mining applications is to generate a multi-faceted overview of a topic in a text collection. Such an overview not only directly serves as an informative summary of the topic, but also provides a detailed view of navigation to different facets of the topic. Existing work has cast this problem as a categorization problem and requires training examples for each facet. This has three limitations: (1) All facets are predefined, which may not fit the need of a particular user. (2) Training examples for each facet are often unavailable. (3) Such an approach only works for a predefined type of topics. In this paper, we break these limitations and study a more realistic new setup of the problem, in which we would allow a user to flexibly describe each facet with keywords for an arbitrary topic and attempt to mine a multi-faceted overview in an unsupervised way. We attempt a probabilistic approach to solve this problem. Empirical experiments on different genres of tex...
Xu Ling, Qiaozhu Mei, ChengXiang Zhai, Bruce R. Sc
Added 30 Nov 2009
Updated 30 Nov 2009
Type Conference
Year 2008
Where KDD
Authors Xu Ling, Qiaozhu Mei, ChengXiang Zhai, Bruce R. Schatz
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