Conceptual Graph Aboutness

Theodorus Huibers Iadh Ounis 1 Jean-Pierre Chevallet 2
2 MRIM - Modélisation et Recherche d’Information Multimédia [Grenoble]
LIG - Laboratoire d'Informatique de Grenoble, Inria - Institut National de Recherche en Informatique et en Automatique
Abstract : Aboutness is fundamental to information retrieval. It appears in questions like: is the characterisation of a document about the representation of an information need? In an information retrieval model based on conceptual graphs like Elen, a conceptual graph is a representative of the information inherent in the document and query. Graph operators can be used to determine whether a graph is a generalisation of another graph, in which case the information carried by the graph is said to be about the information carried by the generalisation of the graph. In this article we want to compare this conceptual graph aboutness with aboutness derivations of other information retrieval models. The aboutness derivations are first mapped to a situated logic framework. Within this framework, the axioms that drive the retrieval process can be filtered out. The retrieval mechanism can then be compared with other approaches according to which axioms they are governed by. Using this method we can show that Elen is indeed closely related to other classical aboutness derivations, and that in some aspects it has even more potential from an information retrieval perspective.
Type de document :
Communication dans un congrès
The 4th International Conference on Conceptual Structures (ICCS'96). Lecture Notes in Artificial Intelligence LNAI #1115, Springer-Verlag, ISBN 3-540-61534-2, 1996, Sydney, Australia. pp.130--144, 1996
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https://hal.inria.fr/hal-00953971
Contributeur : Marie-Christine Fauvet <>
Soumis le : vendredi 28 février 2014 - 16:08:08
Dernière modification le : jeudi 11 janvier 2018 - 06:22:06

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Theodorus Huibers, Iadh Ounis, Jean-Pierre Chevallet. Conceptual Graph Aboutness. The 4th International Conference on Conceptual Structures (ICCS'96). Lecture Notes in Artificial Intelligence LNAI #1115, Springer-Verlag, ISBN 3-540-61534-2, 1996, Sydney, Australia. pp.130--144, 1996. 〈hal-00953971〉

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