Bibliography References Validation using Emergent Architecture
Identifieur interne : 001624 ( Crin/Curation ); précédent : 001623; suivant : 001625Bibliography References Validation using Emergent Architecture
Auteurs : F. Parmentier ; A. BelaïdSource :
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Abstract
In this paper, we present an AI approach for the semantic recognition of bibliography references. The objectif is to produce for each reference a structured flow containing, in UNIMARG format, the list of the different sub-fields recognized and semantically validated. References are given by an OCR flow in SGML format. For the component recognition, we use a generic model of a reference class and an approach based on hypotheses production and verification about component limits in the reference area. Once limits are found, each component is validated according to the relationships between its terms (for example, co-authors) and between terms within different components (for example, relationships between authors and keywords (themes) in the title). These relationships are validated from references written by the same authors or by authors in close domains and located in a reference data base. We use an emergent architecture based on a Concept Network. The Concept Network is dynamic\, ; it allows concepts and, consequently, ``agents'' to emerge. This new architecture is experimented on some paper references belonging to our laboratory references.
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<term>emergent architecture</term>
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<front><div type="abstract" xml:lang="en" wicri:score="3013">In this paper, we present an AI approach for the semantic recognition of bibliography references. The objectif is to produce for each reference a structured flow containing, in UNIMARG format, the list of the different sub-fields recognized and semantically validated. References are given by an OCR flow in SGML format. For the component recognition, we use a generic model of a reference class and an approach based on hypotheses production and verification about component limits in the reference area. Once limits are found, each component is validated according to the relationships between its terms (for example, co-authors) and between terms within different components (for example, relationships between authors and keywords (themes) in the title). These relationships are validated from references written by the same authors or by authors in close domains and located in a reference data base. We use an emergent architecture based on a Concept Network. The Concept Network is dynamic\, ; it allows concepts and, consequently, ``agents'' to emerge. This new architecture is experimented on some paper references belonging to our laboratory references.</div>
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<BibTex type="inproceedings"><ref>parmentier94b</ref>
<crinnumber>94-R-251</crinnumber>
<category>3</category>
<equipe>READ</equipe>
<author><e>Parmentier, F.</e>
<e>Belaïd, A.</e>
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<title>Bibliography References Validation using Emergent Architecture</title>
<booktitle>{Proceedings International Conference on Document Analysis and Recognition, Montréal (Canada)}</booktitle>
<year>1994</year>
<volume>2</volume>
<pages>532-535</pages>
<month>aug</month>
<keywords><e>bibliography reference</e>
<e>emergent architecture</e>
<e>knowledge database</e>
<e>stochastic learning</e>
<e>semantic validation</e>
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<abstract>In this paper, we present an AI approach for the semantic recognition of bibliography references. The objectif is to produce for each reference a structured flow containing, in UNIMARG format, the list of the different sub-fields recognized and semantically validated. References are given by an OCR flow in SGML format. For the component recognition, we use a generic model of a reference class and an approach based on hypotheses production and verification about component limits in the reference area. Once limits are found, each component is validated according to the relationships between its terms (for example, co-authors) and between terms within different components (for example, relationships between authors and keywords (themes) in the title). These relationships are validated from references written by the same authors or by authors in close domains and located in a reference data base. We use an emergent architecture based on a Concept Network. The Concept Network is dynamic\, ; it allows concepts and, consequently, ``agents'' to emerge. This new architecture is experimented on some paper references belonging to our laboratory references.</abstract>
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