Probabilistic models for terminology extraction and knowledge structuring from documents

This paper outlines several problems inherent to knowledge extraction and structuring from textual data, and proposes different probabilistic models for solving them. These models are evaluated on different tasks, and several applications are envisaged.

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Bibliographic Details
Main Authors: Gaussier, E., Cancedda, N.
Format: Conference Proceeding
Language:English
Subjects:
Artificial satellites
Computational modeling
Data mining
Documentation
Europe
Gaussian processes
Indexing
Natural languages
Ontologies
Terminology
Online Access:Request full text
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Description
Summary:This paper outlines several problems inherent to knowledge extraction and structuring from textual data, and proposes different probabilistic models for solving them. These models are evaluated on different tasks, and several applications are envisaged.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2001.973039