Intelligent information access
Intelligent Information Access techniques attempt to overcome the limitations of current search devices by providing personalized information items and product/ service recommendations. They normally utilize direct or indirect user input and facilitate the information search and decision processes,...
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| Autor principal: | |
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| Outros Autores: | , , , |
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado em: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edição: | 1st ed. 2010. |
| coleção: | Studies in Computational Intelligence
301 |
| Acesso em linha: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Intelligent information access, Giuliano Armano, Marco de Gemmis, Giovanni Semeraro ... [et al.], (eds.), Berlin, Springer, 2010, 1 vol. (XII-135 p.), Studies in computational intelligence, 978-3-642-13999-4 • Intelligent Information Access, Texte imprimé, 9783642263873 • Intelligent information access, Giuliano Armano, Marco de Gemmis, Giovanni Semeraro ... [et al.], (eds.), Berlin, Springer, 2010, 1 vol. (XII-135 p.), Studies in computational intelligence, 978-3-642-13999-4 • Intelligent Information Access, Texte imprimé, 9783642140013 |
| Resumo: | Intelligent Information Access techniques attempt to overcome the limitations of current search devices by providing personalized information items and product/ service recommendations. They normally utilize direct or indirect user input and facilitate the information search and decision processes, according to user needs, preferences and usage patterns. Recent developments at the intersection of Information Retrieval, Information Filtering, Machine Learning, User Modelling, Natural Language Processing and Human-Computer Interaction offer novel solutions that empower users to go beyond single-session lookup tasks and that aim at serving the more complex requirement: Tell me what I don t know that I need to know . Information filtering systems, specifically recommender systems, have been revolutionizing the way information seekers find what they want, because they effectively prune large information spaces and help users in selecting items that best meet their needs and preferences. Recommender systems rely strongly on the use of various machine learning tools and algorithms for learning how to rank, or predict user evaluation, of items. Information Retrieval systems, on the other hand, also attempt to address similar filtering and ranking problems for pieces of information such as links, pages, and documents. But they generally focus on the development of global retrieval techniques, often neglecting individual user needs and preferences. The book aims to investigate current developments and new insights into methods, techniques and technologies for intelligent information access from a multidisciplinary perspective. It comprises six chapters authored by participants in the research event Intelligent Information Access, held in Cagliari (Italy) in December 2008 |
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| Descrição do item: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9783642140006 |
| ISSN: | 1860-9503 |
| Acesso: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |