A proposal for annotation, semantic similarity and classification of textual documents

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Bibliographic Details
Title: A proposal for annotation, semantic similarity and classification of textual documents
Authors: Nauer, Emmanuel, Napoli, Amedeo
Contributors: Knowledge representation, reasonning (ORPAILLEUR), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Université Paul Verlaine - Metz (UPVM)
Source: Artificial Intelligence: Methodology, Systems, and Applications ; The 12th International Conference on Artificial Intelligence: Methodology, Systems, Applications - AIMSA 2006. AI, people and the web ; https://hal.science/hal-00102585 ; The 12th International Conference on Artificial Intelligence: Methodology, Systems, Applications - AIMSA 2006. AI, people and the web, 2006, Varna, Bulgaria. pp.201-212, ⟨10.1007/11861461_22⟩
Publisher Information: CCSD
Springer Berlin / Heidelberg
Publication Year: 2006
Collection: Université de Lorraine: HAL
Subject Terms: domain ontology, content-based classification of documents, document annotation, semantic similarity, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Subject Geographic: Varna, Bulgaria
Description: The original publication is available at www.springerlink.com ; International audience ; In this paper, we present an approach for classifying documents based on the notion of a semantic similarity and the effective representation of the content of the documents. The content of a document is annotated and the resulting annotation is represented by a labeled tree whose nodes and edges are represented by concepts lying within a domain ontology. A reasoning process may be carried out on annotation trees, allowing the comparison of documents between each others, for classification or information retrieval purposes. An algorithm for classifying documents with respect to semantic similarity and a discussion conclude the paper.
Document Type: conference object
Language: English
DOI: 10.1007/11861461_22
Availability: https://hal.science/hal-00102585
https://hal.science/hal-00102585v1/document
https://hal.science/hal-00102585v1/file/en_an-aimsa-06.pdf
https://doi.org/10.1007/11861461_22
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.F9624926
Database: BASE
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