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Formal Concept Analysis and Information Retrieval – A Survey

Identifieur interne : 000478 ( Main/Exploration ); précédent : 000477; suivant : 000479

Formal Concept Analysis and Information Retrieval – A Survey

Auteurs : Victor Codocedo [France] ; Amedeo Napoli [France]

Source :

RBID : Hal:hal-01186196

English descriptors

Abstract

One of the first models to be proposed as a document index for retrieval purposes was a lattice structure, decades before the introduction of Formal Concept Analysis. Nevertheless, the main notions that we consider so familiar within the community (" extension " , " intension " , " closure operators " , " order ") were already an important part of it. In the '90s, as FCA was starting to settle as an epistemic community, lattice-based Information Retrieval (IR) systems smoothly transitioned towards FCA-based IR systems. Currently, FCA theory supports dozens of different retrieval applications, ranging from traditional document indices to file systems, recommendation, multi-media and more recently, semantic linked data. In this paper we present a comprehensive study on how FCA has been used to support IR systems. We try to be as exhaustive as possible by reviewing the last 25 years of research as chronicles of the domain, yet we are also concise in relating works by its theoretical foundations. We think that this survey can help future endeavours of establishing FCA as a valuable alternative for modern IR systems.

Url:
DOI: 10.1007/978-3-319-19545-2_4


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<div type="abstract" xml:lang="en">One of the first models to be proposed as a document index for retrieval purposes was a lattice structure, decades before the introduction of Formal Concept Analysis. Nevertheless, the main notions that we consider so familiar within the community (" extension " , " intension " , " closure operators " , " order ") were already an important part of it. In the '90s, as FCA was starting to settle as an epistemic community, lattice-based Information Retrieval (IR) systems smoothly transitioned towards FCA-based IR systems. Currently, FCA theory supports dozens of different retrieval applications, ranging from traditional document indices to file systems, recommendation, multi-media and more recently, semantic linked data. In this paper we present a comprehensive study on how FCA has been used to support IR systems. We try to be as exhaustive as possible by reviewing the last 25 years of research as chronicles of the domain, yet we are also concise in relating works by its theoretical foundations. We think that this survey can help future endeavours of establishing FCA as a valuable alternative for modern IR systems.</div>
</front>
</TEI>
<affiliations>
<list>
<country>
<li>France</li>
</country>
<region>
<li>Auvergne-Rhône-Alpes</li>
<li>Grand Est</li>
<li>Lorraine (région)</li>
<li>Rhône-Alpes</li>
</region>
<settlement>
<li>Lyon</li>
<li>Metz</li>
<li>Nancy</li>
</settlement>
<orgName>
<li>Université Claude Bernard Lyon 1</li>
<li>Université de Lorraine</li>
<li>Université de Lyon</li>
</orgName>
</list>
<tree>
<country name="France">
<region name="Auvergne-Rhône-Alpes">
<name sortKey="Codocedo, Victor" sort="Codocedo, Victor" uniqKey="Codocedo V" first="Victor" last="Codocedo">Victor Codocedo</name>
</region>
<name sortKey="Napoli, Amedeo" sort="Napoli, Amedeo" uniqKey="Napoli A" first="Amedeo" last="Napoli">Amedeo Napoli</name>
</country>
</tree>
</affiliations>
</record>

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