Claude de Loupy

Also published as: Claude De Loupy


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Thematic Cohesion: measuring terms discriminatory power toward themes
Clément de Groc | Xavier Tannier | Claude de Loupy
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We present a new measure of thematic cohesion. This measure associates each term with a weight representing its discriminatory power toward a theme, this theme being itself expressed by a list of terms (a thematic lexicon). This thematic cohesion criterion can be used in many applications, such as query expansion, computer-assisted translation, or iterative construction of domain-specific lexicons and corpora. The measure is computed in two steps. First, a set of documents related to the terms is gathered from the Web by querying a Web search engine. Then, we produce an oriented co-occurrence graph, where vertices are the terms and edges represent the fact that two terms co-occur in a document. This graph can be interpreted as a recommendation graph, where two terms occurring in a same document means that they recommend each other. This leads to using a random walk algorithm that assigns a global importance value to each vertex of the graph. After observing the impact of various parameters on those importance values, we evaluate their correlation with retrieval effectiveness.


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Lexicons from Comparable Corpora for Multilingual Information Retrieval (Lexiques de corpus comparables et recherche d’information multilingue) [in French]
Frederik Cailliau | Ariane Cavet | Clément De Groc | Claude De Loupy
Proceedings of TALN 2013 (Volume 2: Short Papers)


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Un critère de cohésion thématique fondé sur un graphe de cooccurrences (Topical Cohesion using Graph Random Walks) [in French]
Clément de Groc | Xavier Tannier | Claude de Loupy
Proceedings of the Joint Conference JEP-TALN-RECITAL 2012, volume 2: TALN


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Knowledge-Poor Approach to Shallow Parsing: Contribution of Unsupervised Part-of-Speech Induction
Marie Guégan | Claude de Loupy
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011


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OAL: A NLP Architecture to Improve the Development of Linguistic Resources for NLP
Javier Couto | Helena Blancafort | Somara Seng | Nicolas Kuchmann-Beauger | Anass Talby | Claude de Loupy
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

The performance of most NLP applications relies upon the quality of linguistic resources. The creation, maintenance and enrichment of those resources are a labour-intensive task, especially when no tools are available. In this paper we present the NLP architecture OAL, designed to assist computational linguists in the whole process of the development of resources in an industrial context: from corpora compilation to quality assurance. To add new words more easily to the morphosyntactic lexica, a guesser that lemmatizes and assigns morphosyntactic tags as well as inflection paradigms to a new word has been developed. Moreover, different control mechanisms are set up to check the coherence and consistency of the resources. Today OAL manages resources in five European languages: French, English, Spanish, Italian and Polish. Chinese and Portuguese are in process. The development of OAL has followed an incremental strategy. At present, semantic lexica, a named entities guesser and a named entities phonetizer are being developed.

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A French Human Reference Corpus for Multi-Document Summarization and Sentence Compression
Claude de Loupy | Marie Guégan | Christelle Ayache | Somara Seng | Juan-Manuel Torres Moreno
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

This paper presents two corpora produced within the RPM2 project: a multi-document summarization corpus and a sentence compression corpus. Both corpora are in French. The first one is the only one we know in this language. It contains 20 topics with 20 documents each. A first set of 10 documents per topic is summarized and then the second set is used to produce an update summarization (new information). 4 annotators were involved and produced a total of 160 abstracts. The second corpus contains all the sentences of the first one. 4 annotators were asked to compress the 8432 sentences. This is the biggest corpus of compressed sentences we know, whatever the language. The paper provides some figures in order to compare the different annotators: compression rates, number of tokens per sentence, percentage of tokens kept according to their POS, position of dropped tokens in the sentence compression phase, etc. These figures show important differences from an annotator to the other. Another point is the different strategies of compression used according to the length of the sentence.


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Browsing Help for a Faster Retrieval
Eric Crestan | Claude de Loupy
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics


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Improving WSD with Multi-Level View of Context Monitored by Similarity Measure
Eric Crestan | Marc El-Bèze | Claude de Loupy
Proceedings of SENSEVAL-2 Second International Workshop on Evaluating Word Sense Disambiguation Systems


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Using Few Clues Can Compensate the Small Amount of Resources Available for Word Sense Disambiguation
Claude de Loupy | Marc El-Bèze
Proceedings of the Second International Conference on Language Resources and Evaluation (LREC’00)