NBM and WNBM: Algorithms and Evaluation for personalizing information retrieval in METIORE
Identifieur interne : 003487 ( Hal/Curation ); précédent : 003486; suivant : 003488NBM and WNBM: Algorithms and Evaluation for personalizing information retrieval in METIORE
Auteurs : David Bueno [Espagne] ; Ricardo Conejo [Espagne] ; Amos David [France] ; Cristina Carmona [Espagne]Source :
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Abstract
The current Information Retrieval Systems return hundreds or thousands of documents in response to a query. Users consider only the first 20 or 30, but documents are often sorted according to the query and the results are perhaps not relevant to the users' needs. This situation is even more problematic when non expert users have difficulties in expressing their information requirements. One solution to this problem could be the use of a user model which would complement the query in order to find the best solutions for the user. Most personalized retrieval systems have a single user model for each user which works on the basis that this user will have always the same information needs. Our proposal however is a personalization method based on the current objective of the user. To this end, we have developed two probabilistic algorithms NBM and WNBM which support different kinds of multi parameter databases and in this paper we present new experiments with these algorithms in METIORE to validate our proposal
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DOI: 10.1007/978-3-540-74829-8_125
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This situation is even more problematic when non expert users have difficulties in expressing their information requirements. One solution to this problem could be the use of a user model which would complement the query in order to find the best solutions for the user. Most personalized retrieval systems have a single user model for each user which works on the basis that this user will have always the same information needs. Our proposal however is a personalization method based on the current objective of the user. To this end, we have developed two probabilistic algorithms NBM and WNBM which support different kinds of multi parameter databases and in this paper we present new experiments with these algorithms in METIORE to validate our proposal</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">NBM and WNBM: Algorithms and Evaluation for personalizing information retrieval in METIORE</title><author role="aut"><persName><forename type="first">David</forename><surname>Bueno</surname></persName><email></email><idno type="halauthor">200915</idno><affiliation ref="#struct-48056"></affiliation></author><author role="aut"><persName><forename type="first">Ricardo</forename><surname>Conejo</surname></persName><email></email><idno type="halauthor">131926</idno><affiliation ref="#struct-48056"></affiliation></author><author role="aut"><persName><forename type="first">Amos</forename><surname>David</surname></persName><email>Amos.David@loria.fr</email><idno type="halauthor">172883</idno><orgName ref="#struct-300292"></orgName><affiliation ref="#struct-2493"></affiliation></author><author role="aut"><persName><forename type="first">Cristina</forename><surname>Carmona</surname></persName><email></email><idno type="halauthor">131927</idno><affiliation ref="#struct-48056"></affiliation></author><editor role="depositor"><persName><forename>Amos</forename><surname>David</surname></persName><email>Amos.David@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2007-11-08 11:57:33</date><date type="whenModified">2016-05-19 01:05:35</date><date type="whenReleased">2007-11-08 13:39:03</date><date type="whenProduced">2007-09-12</date><date type="whenEndEmbargoed">2007-11-08</date><ref type="file" target="https://hal.inria.fr/inria-00166290/document"><date notBefore="2007-11-08"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.inria.fr/inria-00166290/file/2007-metoirerawws.PDF"><date notBefore="2007-11-08"></date></ref></edition><respStmt><resp>contributor</resp><name key="103163"><persName><forename>Amos</forename><surname>David</surname></persName><email>Amos.David@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">inria-00166290</idno><idno type="halUri">https://hal.inria.fr/inria-00166290</idno><idno type="halBibtex">bueno:inria-00166290</idno><idno type="halRefHtml">Bruno Apolloni, Robert J. Howlett et Lakhmi Jain. 11th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems - KES 2007, Sep 2007, Vietri sul Mare, Italy. Springer Berlin / Heidelberg, 4694, pp.1024-1032, 2007, Lecture Notes in Computer Science; Knowledge-Based Intelligent Information and Engineering Systems - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy, September 12-14, 2007, Proceedings, Part III. <10.1007/978-3-540-74829-8_125></idno><idno type="halRef">Bruno Apolloni, Robert J. Howlett et Lakhmi Jain. 11th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems - KES 2007, Sep 2007, Vietri sul Mare, Italy. Springer Berlin / Heidelberg, 4694, pp.1024-1032, 2007, Lecture Notes in Computer Science; Knowledge-Based Intelligent Information and Engineering Systems - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy, September 12-14, 2007, Proceedings, Part III. <10.1007/978-3-540-74829-8_125></idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno></seriesStmt><notesStmt><note type="commentary">The original publication is available at www.springerlink.com</note><note type="audience" n="2">International</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">NBM and WNBM: Algorithms and Evaluation for personalizing information retrieval in METIORE</title><author role="aut"><persName><forename type="first">David</forename><surname>Bueno</surname></persName><idno type="halAuthorId">200915</idno><affiliation ref="#struct-48056"></affiliation></author><author role="aut"><persName><forename type="first">Ricardo</forename><surname>Conejo</surname></persName><idno type="halAuthorId">131926</idno><affiliation ref="#struct-48056"></affiliation></author><author role="aut"><persName><forename type="first">Amos</forename><surname>David</surname></persName><email>Amos.David@loria.fr</email><idno type="halAuthorId">172883</idno><orgName ref="#struct-300292"></orgName><affiliation ref="#struct-2493"></affiliation></author><author role="aut"><persName><forename type="first">Cristina</forename><surname>Carmona</surname></persName><idno type="halAuthorId">131927</idno><affiliation ref="#struct-48056"></affiliation></author></analytic><monogr><meeting><title>11th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems - KES 2007</title><date type="start">2007-09-12</date><settlement>Vietri sul Mare</settlement><country key="IT">Italy</country></meeting><editor>Bruno Apolloni, Robert J. Howlett et Lakhmi Jain</editor><imprint><publisher>Springer Berlin / Heidelberg</publisher><biblScope unit="serie"></biblScope><biblScope unit="volume">4694</biblScope><biblScope unit="pp">1024-1032</biblScope><date type="datePub">2007</date></imprint></monogr><idno type="doi">10.1007/978-3-540-74829-8_125</idno></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">METIORE</term><term xml:lang="en">Information Retrieval</term><term xml:lang="en">Recommender Systems</term><term xml:lang="en">NBM</term><term xml:lang="en">WNBM</term><term xml:lang="en">Naïve Bayes</term><term xml:lang="en">user modelling</term><term xml:lang="en">user profile</term><term xml:lang="en">information retrieval system</term></keywords><classCode scheme="halDomain" n="info.info-ir">Computer Science [cs]/Information Retrieval [cs.IR]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">The current Information Retrieval Systems return hundreds or thousands of documents in response to a query. Users consider only the first 20 or 30, but documents are often sorted according to the query and the results are perhaps not relevant to the users' needs. This situation is even more problematic when non expert users have difficulties in expressing their information requirements. One solution to this problem could be the use of a user model which would complement the query in order to find the best solutions for the user. Most personalized retrieval systems have a single user model for each user which works on the basis that this user will have always the same information needs. Our proposal however is a personalization method based on the current objective of the user. To this end, we have developed two probabilistic algorithms NBM and WNBM which support different kinds of multi parameter databases and in this paper we present new experiments with these algorithms in METIORE to validate our proposal</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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