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3 results on '"semantic term proximity"'

1. Inclusion lexicale et proximité sémantique entre termes

Author

Ibekwe-Sanjuan, Fidelia, Ibekwe, Fidelia, Equipe de recherche de Lyon en sciences de l'information et de la communication (ELICO), Université Lumière - Lyon 2 (UL2)-École nationale supérieure des sciences de l'information et des bibliothèques (ENSSIB), Université de Lyon-Université de Lyon-Sciences Po Lyon - Institut d'études politiques de Lyon (IEP Lyon), Université de Lyon-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Sciences Po Lyon - Institut d'études politiques de Lyon (IEP Lyon), Université de Lyon-Université de Lyon-École nationale supérieure des sciences de l'information et des bibliothèques (ENSSIB), and Université de Lyon-Université Lumière - Lyon 2 (UL2)

Subjects
proximité sémantique, science and technology watch, [SHS.INFO.INGE]Humanities and Social Sciences/Library and information sciences/domain_shs.info.inge, [SHS.INFO]Humanities and Social Sciences/Library and information sciences, [SHS.INFO.GEST] Humanities and Social Sciences/Library and information sciences/domain_shs.info.gest, semantic term proximity, veille scientifique et technologique, [SHS.INFO.GEST]Humanities and Social Sciences/Library and information sciences/domain_shs.info.gest, acquisition de relations sémantiques, [SHS.INFO] Humanities and Social Sciences/Library and information sciences, proximité sémantique, acquisition de relations sémantiques, semantic relations acquisition, [SHS.INFO.INGE] Humanities and Social Sciences/Library and information sciences/domain_shs.info.inge, agrégats semantiques, inclusion lexicale, lexical inclusion, semantic clusters
Abstract

We study the influence of lexical subsumption on the semantic proximity of terms. By studying the semantic relation between lexically subsumed terms in an existing controlled vocabulary and those in a corpus, we formulate hypotheses on the underlying specific relations. These hypotheses enable us to propose an ordering of term variants found in the corpus, by probability of decreasing semantic proximity. Results from our experiment show that surface indices like the presence of proper names, compounds and the number of added words in a term variant are criteria for ordering the variants of the same term. The ranking obtained will enable us to form more semantically-cohesive clusters. Applications targeted are text mining, question-answering and science and technology watch., Nous étudions l'influence de l'inclusion lexicale sur la proximité sémantique entre termes. A partir de l'analyse des relations entre termes d'une ressource terminologique existante, lexicalement inclus dans ceux issus d'un corpus, nous formulons des hypothèses des relations engendrées. Ces hypothèses nous permettent de proposer un ordonnancement automatique des variantes des termes trouvées dans le corpus, par probabilité de proximité sémantique décroissante. Les premières expérimentations montrent que la prise en compte d'indices morpho-lexicaux comme la présence de noms composés, de noms propres et le nombre d'éléments ajoutés sont des critères à prendre en compte pour classer les variantes d'un même terme. L'ordonnancement obtenu permettra de former des classes de termes sémantiquement homogènes. Les applications visées sont la fouille de textes, la veille scientifique et technologique, la reformulation des requêtes.

Published
2005

2. Strangeness enhancement at mid--rapidity in Pb--Pb collisions at 158 $A$ GeV/c

Author

Andersen, E., Antinori, F., Armenise, N., Bakke, H., Ban, J., Barberis, D., Beker, H., Beusch, W., Bloodworth, I.G., Bohm, J., Caliandro, R., Campbell, M., Cantatore, E., Carrer, N., Catanesi, M.G., Chesi, E., Dameri, M., Darbo, G., Diaczek, A., Di Bari, D., Di Liberto, S., Earl, B.C., Elia, D., Evans, D., Fanebust, K., Fini, R., Fontaine, J.C., Ftacnik, J., Ghidini, B., Grella, G., Guida, M., Heijne, E.H.M., Helstrup, H., Holme, A.K., Huss, D., Jacholkowski, A., Jones, G.T., Jovanovic, P., Jusko, A., Kachelhoffer, T., Kinson, J.B., Kirk, A., Klempt, W., Knudsen, B.T.H., Knudson, K., Kralik, I., Lenti, V., Lietava, R., Loconsole, R.A., Lovhoiden, G., Luptak, M., Mack, V., Manzari, V., Martinengo, P., Mazzoni, M.A., Meddi, F., Michalon, A., Michalon-Mentzer, M.E., Middelkamp, P., Morando, M., Muciaccia, M.T., Nappi, E., Navach, F., Norman, P.I., Osculati, B., Pastircak, B., Pellegrini, F., Piska, K., Posa, F., Quercigh, E., Ricci, R.A., Romano, G., Rosa, G., Rossi, L., Rotscheidt, H., Safarik, K., Saladino, S., Salvo, C., Sandor, L., Scognetti, T., Segato, G., Sene, M., Sene, R., Simone, S., Snoeys, W., Staroba, P., Szafran, S., Thompson, M., Thorsteinsen, T.F., Tomasicchio, G., Torrieri, G.D., Tveter, T.S., Urban, Jakub, Venables, M., Villalobos Baillie, O., Virgili, T., Volte, A., Votruba, M.F., Zavada, P., Lantz, Simone, Physique Corpusculaire et Cosmologie - Collège de France (PCC), Collège de France (CdF (institution))-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherches Subatomiques (IReS), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Cancéropôle du Grand Est-Université Louis Pasteur - Strasbourg I-Centre National de la Recherche Scientifique (CNRS), WA97, Collège de France (CdF)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), and Heyd, Yvette

Subjects
science and technology watch, semantic relations acquisition, [PHYS.NEXP] Physics [physics]/Nuclear Experiment [nucl-ex], semantic term proximity, [PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex], lexical inclusion, semantic clusters
Abstract

We study the influence of lexical subsumption on the semantic proximity of terms. By studying the semantic relation between lexically subsumed terms in an existing controlled vocabulary and those in a corpus, we formulate hypotheses on the underlying specific relations. These hypotheses enable us to propose an ordering of term variants found in the corpus, by probability of decreasing semantic proximity. Results from our experiment show that surface indices like the presence of proper names, compounds and the number of added words in a term variant are criteria for ordering the variants of the same term. The ranking obtained will enable us to form more semantically-cohesive clusters. Applications targeted are text mining, question-answering and science and technology watch.

Published
1999

3. Beta-decay half-lives of very neutron rich Ni, Co, Fe isotopes produced by thermal fission of $^{235}$U and $^{239}$Pu

Author

Bernas, M., Ambruster, P., Bocquet, J.P., Brissot, R., Faust, H., Czakowsi, S., Sida, J.L., bibliotheque, LPSC, Institut de Physique Nucléaire d'Orsay (IPNO), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)

Subjects
science and technology watch, semantic relations acquisition, [PHYS.NEXP] Physics [physics]/Nuclear Experiment [nucl-ex], semantic term proximity, [PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex], lexical inclusion, semantic clusters
Abstract

We study the influence of lexical subsumption on the semantic proximity of terms. By studying the semantic relation between lexically subsumed terms in an existing controlled vocabulary and those in a corpus, we formulate hypotheses on the underlying specific relations. These hypotheses enable us to propose an ordering of term variants found in the corpus, by probability of decreasing semantic proximity. Results from our experiment show that surface indices like the presence of proper names, compounds and the number of added words in a term variant are criteria for ordering the variants of the same term. The ranking obtained will enable us to form more semantically-cohesive clusters. Applications targeted are text mining, question-answering and science and technology watch.

Published
1990

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