Term Extraction Through Unithood and Termhood Unification

@inproceedings{Vu2008TermET,
  title={Term Extraction Through Unithood and Termhood Unification},
  author={Thuy Vu and AiTi Aw and Min Zhang},
  booktitle={IJCNLP},
  year={2008}
}
Term Extraction (TE) is an important component of many NLP applications. In general, terms are extracted for a given text collection based on global context and frequency analysis on words/phrases association. These extracted terms represent effectively the text content of the collection for knowledge elicitation tasks. However, they fail to dictate the local contextual information for each document effectively. In this paper, we refine the state-of-the-art C/NCValue term weighting method by… CONTINUE READING
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  • The precision for local term extraction improves by 12% when compared to pure linguistic based extraction method.
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