6533b871fe1ef96bd12d16a5

RESEARCH PRODUCT

AN ONTOLOGY-BASED RECOMMENDER SYSTEM USING HIERARCHICAL MULTICLASSIFICATION FOR ECONOMICAL E-NEWS

David WernerNuno SilvaChristophe CruzAurélie Bertaux

subject

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]recommender system[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]Multi-label classification[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO.INFO-IT ] Computer Science [cs]/Information Theory [cs.IT]machine learning[INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]e-newsontology[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUS

description

International audience; This paper focuses on a recommender system of economic news articles. Its objectives are threefold: (i) automatically multi-classify new economic articles, (ii) recommend articles by comparing profiles of users and multi-classification of articles, and (iii) managing the vocabulary of the economic news domain to improve the system based on seamlessly intervention of documentalists. In this paper we focus on the automatic multi-classification of the articles, managed by inference process of ontologies, and the enrichment of the documentalist-oriented ontology which provides the necessary capabilities to the DL reasoner for automatic multi-classification.

https://hal.archives-ouvertes.fr/hal-01086189