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Record Nr. |
UNINA9910254352303321 |
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Titolo |
Information Filtering and Retrieval [[electronic resource] ] : DART 2014: Revised and Invited Papers / / edited by Cristian Lai, Alessandro Giuliani, Giovanni Semeraro |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
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ISBN |
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Edizione |
[1st ed. 2017.] |
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Descrizione fisica |
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1 online resource (VII, 117 p. 50 illus.) |
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Collana |
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Studies in Computational Intelligence, , 1860-949X ; ; 668 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Computational Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Time Event Extraction to Boost an Information Retrieval System -- Interactive Text Categorisation: The Geometry of Likelihood Spaces -- Mining Movement Data to Extract Personal Points of Interest: A Feature Based Approach -- SABRE: a Sentiment Aspect-Based Retrieval Engine -- Monitoring and Supporting People that Need Assistance: the BackHome Experience -- The Relevance of Providing Useful and Personalized Information to Therapists and Caregivers in Tele*. |
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Sommario/riassunto |
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This book focuses on new research challenges in intelligent information filtering and retrieval. It collects invited chapters and extended research contributions from DART 2014 (the 8th International Workshop on Information Filtering and Retrieval), held in Pisa (Italy), on December 10, 2014, and co-hosted with the XIII AI*IA Symposium on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The chapters of this book present a comprehensive review of related works and the current state of the art. The contributions from both practitioners and researchers have been carefully reviewed by experts in the area, who also gave useful suggestions to improve the quality of the book. |
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