Conceptual Indexing for Multilingual Information Retrieval

Guyot, Jacques; Radhouani, Saïd; Falquet, Gilles

doi:10.1007/11878773_11

Cited by 9 publications

(5 citation statements)

References 3 publications

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“…We think that WSD-based indexing is a promising approach for language-independent indexing and retrieval systems. Although an efficient WSD is essential to create good conceptual indexes, we demonstrated in [7] that ambiguous indexes (with several concepts for some terms) are often sufficient to reach a good multilingual retrieval performance, for the reasons mentioned above. We also revealed that non-trivial queries, like those treated in our study, require adding domain knowledge during indexing and querying process.…”

Section: Resultsmentioning

confidence: 97%

Analysis of Word Sense Disambiguation-Based Information Retrieval

Guyot

Falquet

Radhouani

et al. 2009

Lecture Notes in Computer Science

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Abstract.Several studies have tried to improve retrieval performances based on automatic Word Sense Disambiguation techniques. So far, most attempts have failed. We try, through this paper, to give a deep analysis of the reasons behind these failures. During our participation at the Robust WSD task at CLEF 2008, we performed experiments on monolingual (English) and bilingual (Spanish to English) collections. Our official results and a deep analysis are described below, along with our conclusions and perspectives.

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Section: Resultsmentioning

confidence: 97%

Analysis of Word Sense Disambiguation-Based Information Retrieval

Guyot

Falquet

Radhouani

et al. 2009

Lecture Notes in Computer Science

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“…En effet, nos travaux sur (i) les annotations sémantiques et les documents techniques (Ghoula et al, 2007), (ii) les bibliothèques numériques sémantiques (Falquet et al, 2009) et (iii) l'indexation conceptuelle et la désambiguï-sation (Guyot et al, 2005), nous ont permis de modéliser, manipuler et générer ces ressources. En se basant sur ces travaux et sur l'étude des ressources (cf.…”

Section: Métadonnéesunclassified

Modèle d’entrepôt de ressources hétérogènes pour le traitement sémantique des documents

Ghoula¹,

Falquet²,

Guyot³

2010

Document numérique

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-------------------------------------------------------------------------------------------------------------------- RÉSUMÉ. Les ressources documentaires sont riches en connaissances d'un domaine donné. L'extraction et la représentation de ces connaissances est un problème largement exploré dont la solution est basée sur l'utilisation de ressources ontologiques, terminologiques et linguistiques. Ces ressources ont des types et des modèles de représentations hétérogènes. Nous effectuons des représentations multiples des ressources à l'aide de différents modèles de contenus. Ceci est modélisé par une ontologie générique qui formalise les modèles des ressources, les opérations que nous pouvons effectuer sur ces ressources et les processus

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“…Through a conceptual indexing process, each document doc is represented by a set of concepts: doc = {c}. Our approaches for conceptual indexing and the underlying results are detailed in our previous works: multilingual text retrieval [10][11], Image retrieval [12] and video retrieval [16].…”

Section: B Multi-dimensional Document Indexingmentioning

confidence: 99%

FlexIR: a Domain-Specific Information Retrieval System

2009

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Abstract-We present a precise search engine adapted to professional environments which are characterized by a domain (e.g. medicine, law, sport, and so on). In our approach, each domain has its own terminology (i.e. a set of terms that denote its concepts: team, player, etc.) and it is organized along dimensions, such as person, location, etc. The dimensions, as described below, are made of concepts and semantic relationships that represent a particular perspective or point of view on the domain. We mainly use the notion of domain dimension to: i) precisely index document content, and ii) develop an interactive interface which allows the user to precisely describe his or her information need and therefore precisely access the document collection.Index Terms-Information retrieval, domain dimensions, user interface.

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Conceptual Indexing for Multilingual Information Retrieval

Cited by 9 publications

References 3 publications

Analysis of Word Sense Disambiguation-Based Information Retrieval

Analysis of Word Sense Disambiguation-Based Information Retrieval

Modèle d’entrepôt de ressources hétérogènes pour le traitement sémantique des documents

FlexIR: a Domain-Specific Information Retrieval System

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