Intelligent Information Access: Studies in Computational Intelligence, cartea 301
Editat de Giuliano Armano, Marco de Gemmis, Giovanni Semeraroen Limba Engleză Paperback – 5 sep 2012
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Specificații
ISBN-13: 9783642263873
ISBN-10: 3642263879
Pagini: 152
Ilustrații: XII, 138 p. 1 illus. in color.
Dimensiuni: 155 x 235 x 8 mm
Greutate: 0.2 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642263879
Pagini: 152
Ilustrații: XII, 138 p. 1 illus. in color.
Dimensiuni: 155 x 235 x 8 mm
Greutate: 0.2 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Enhancing Conversational Access to Information through a Socially Intelligent Agent.- Annotating and Identifying Emotions in Text.- Improving Ranking by Respecting the Multidimensionality and Uncertainty of User Preferences.- Data Mining on Folksonomies.- A Uniform Theoretic Approach to Opinion and Information Retrieval.- A Suite of Semantic Web Tools Supporting Development of Multilingual Ontologies.
Textul de pe ultima copertă
Intelligent Information Access techniques attempt to overcome the limitations ofcurrent search devices by providing personalized information items and product/service recommendations. They normally utilize direct or indirect user input andfacilitate the information search and decision processes, according to user needs,preferences and usage patterns. Recent developments at the intersection of InformationRetrieval, Information Filtering, Machine Learning, User Modelling, NaturalLanguage Processing and Human-Computer Interaction offer novel solutions thatempower users to go beyond single-session lookup tasks and that aim at servingthe more complex requirement: “Tell me what I don’t know that I need to know”.Information filtering systems, specifically recommender systems, have been revolutionizingthe way information seekers find what they want, because they effectivelyprune large information spaces and help users in selecting items that best meet theirneeds and preferences. Recommender systems rely strongly on the use of variousmachine learning tools and algorithms for learning how to rank, or predict userevaluation, of items. Information Retrieval systems, on the other hand, also attemptto address similar filtering and ranking problems for pieces of information such aslinks, pages, and documents. But they generally focus on the development of globalretrieval 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 multidisciplinaryperspective. It comprises six chapters authored by participants in theresearch event Intelligent Information Access, held in Cagliari (Italy) in December2008.
Caracteristici
Recent research on Intelligent Information Access State-of-the-art book Writteny by leading experts in this field