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Extraction d'entités dans des collections évolutives (2007)

Abstract
The goal of our work is to use a set of reports and extract named entities, in our case the names of Industrial or Academic partners. Starting with an initial list of entities, we use a first set of documents to identify syntactic patterns that are then validated in a supervised learning phase on a set of annotated documents. The complete collection is then explored. This approach is similar to the ones used in data extraction from semi-structured documents (wrappers) and do not need any linguistic resources neither a large set for training. As our collection of documents would evolve over years , we hope that the performance of the extraction would improve with the increased size of the training set.

Details der Publikation
Download http://hal.inria.fr/inria-00116910/en/
Quelle http://hal.archives-ouvertes.fr/docs/00/16/19/20/PDF/etam.pdf
Herausgeber HAL - CCSd - CNRS
Mitarbeiter Anne-Marie Vercoustre
Archiv CCSd/HAL : e-articles server (based on gBUS) (France)
Keywords Computer Science/Information Retrieval, Computer Science/Document and Text Processing
Typ COMM_ACT
Sprache Französisch
Coverage Entity extraction; wrapping method, extraction pattern