A novel approach to keyphrase extraction using augmented transition networks and statistical tools
Article No.: 33, Pages 1 - 4
Abstract
We present a novel approach to extract keyphrases based on Augmented Transition Networks (abbreviated as ATNs) followed by statistical methods from any given article, notes on a particular subject, or any other document source. The use of ATNs has completely ruled out the need of background corpora in identifying the potential keywords and keyphrases. Moreover, the use of ATNs has greatly reduced the search space for the statistical methods. We have devised two new methods namely, relaxed statistical analysis and stringent statistical analysis to identify the separability of phrases into sub phrases. In this paper, the two tier process is discussed in detail and illustrated with examples. We have also discussed the applications of this process briefly.
References
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Peter D. Turney. 2000. Learning algorithms for keyphrase extraction. Information Retrieval, 2(4):303--336.
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Alan L. Tharp. Augmented Transition Networks As A Design Tool For Personalized Database Systems. Computer Science Department, North Carolina State University, Raleigh, North Carolina.
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- A novel approach to keyphrase extraction using augmented transition networks and statistical tools
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March 2011
194 pages
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Published: 25 March 2011
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