Recommending biomedical resources: A fuzzy linguistic approach based on semantic web
Identifieur interne : 000161 ( Main/Exploration ); précédent : 000160; suivant : 000162Recommending biomedical resources: A fuzzy linguistic approach based on semantic web
Auteurs : J. M. Morales-Del-Castillo [Espagne] ; Eduardo Peis [Espagne] ; Antonio A. Ruiz [Espagne] ; E. Herrera-Viedma [Espagne]Source :
- International Journal of Intelligent Systems [ 0884-8173 ] ; 2010-12.
English descriptors
- Teeft :
- Biomedical, Biomedical resources, Biomedical sciences, Certain degree, Collaborative recommendation module, Communication processes, Conceptual schemes, Document repository, Exchange information, Experimental outcomes, Formal ontology, Group decision, Ieee trans, Incomplete information, Information agents, Information retrieval, Information science, Information sources, Information systems, Intelligent systems, Interface agent, International conference, International journal, June, Linguistic, Linguistic context, Linguistic information, Linguistic label, Linguistic labels, Linguistic preference relation, Linguistic term, Ltering, Modeling, Modeling techniques, Module, Multiagent model, National cancer institute, Natural language, Other users, Preference, Preference relation, Preference relations, Recommendation process, Recommender, Recommender system, Recommender systems, Relevant items, Resource, Semantic, Semantic level, Semantic similarity, Simple experiment, Software, Software agents, Syst, Task agent, Taxonomic tree, Test thesaurus, Theoretical background, Thesaurus, User, User generation module, User2 user3 user4 user5 user6 user7 user8 user9, Weighted preferences, Wiley periodicals.
Abstract
One of the key issues in dynamic research areas, such as that of biomedical sciences, is the development of tools capable to retrieve and provide users relevant resources from large repositories according to their information needs. In this paper, we present a filtering and recommender system that applies Semantic Web technologies and fuzzy linguistic modeling techniques to provide users valuable information about resources that fit their interests. To carry out the recommendation process, we have defined three software agents (interface, task, and information agents) that are distributed in a five level hierarchical architecture. The system is also capable of to deal with incomplete information to define enriched user profiles and, therefore, soften the problem of cold start. A simple evaluation has been carried out, and the experimental outcomes reveal a reasonable good performance of the system in terms of precision and recall. © 2010 Wiley Periodicals, Inc.
Url:
DOI: 10.1002/int.20447
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">One of the key issues in dynamic research areas, such as that of biomedical sciences, is the development of tools capable to retrieve and provide users relevant resources from large repositories according to their information needs. In this paper, we present a filtering and recommender system that applies Semantic Web technologies and fuzzy linguistic modeling techniques to provide users valuable information about resources that fit their interests. To carry out the recommendation process, we have defined three software agents (interface, task, and information agents) that are distributed in a five level hierarchical architecture. The system is also capable of to deal with incomplete information to define enriched user profiles and, therefore, soften the problem of cold start. A simple evaluation has been carried out, and the experimental outcomes reveal a reasonable good performance of the system in terms of precision and recall. © 2010 Wiley Periodicals, Inc.</div>
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