Enhancing in automatic recognition and extraction of term variants with linguistic features
| Autor: | Alain Zasadzinski, Jean Royauté, Fabienne Ville-Ometz |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Computer science
business.industry Communication Speech recognition Principal (computer security) Search engine indexing Window (computing) Library and Information Sciences computer.software_genre Language and Linguistics Linguistics Term (time) Information extraction Variation (linguistics) Artificial intelligence business computer Word (computer architecture) Sentence Natural language processing |
| Zdroj: | Terminology. 13:35-59 |
| ISSN: | 1569-9994 0929-9971 |
| Popis: | The recognition and extraction of terms and their variants in texts are crucial processes in text mining. We use the ILC platform, an automatic controlled indexing platform, to perform these linguistic processes. We present a methodology for enhancing the recognition of syntactic term variation in English, using syntactic and morpho-syntactic features. Principal spurious variants of terms are ascribed to incorrect word dependencies. To overcome these problems, we consider each term variant as a window on the sentence and introduce two criteria: an internal syntactic criterion which checks that the dependencies between words in the window are respected, and an external criterion which defines boundaries, making it possible to ensure that the window is well positioned in the sentence. The use of these criteria improves filtering of the variants and assists the expert in validating the indexing. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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