Vadim kagan (19 risultati)

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  • Lingua: Inglese

    Editore: CAPSTONE PUBLICATIONS, 2008

    0578004682 / 9780578004686

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    Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections

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  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices

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  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections

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  • Lingua: Inglese

    Editore: Springer 2013-10, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: Chiron Media, Wallingford, Regno UnitoChiron Media

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  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: Books Puddle, New York, NY, U.S.A.Books Puddle

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    EUR 75,64

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    Condizione: New. pp. 92.

  • Lingua: Inglese

    Editore: Springer-Verlag New York Inc, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    EUR 75,28

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    Paperback. Condizione: Brand New. 81 pages. 9.00x6.00x0.25 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 77,12

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techniques such as sentiment mining can be used in real-time to identify posts that contain PTSD-related signals, flag those posts, and bring them to the attention of psychologists, thus providing an automated flag and referral capability. The use of sentiment extraction technologies allows automatic in-depth analysis of opinions and emotions expressed by individuals in their online posts. By training these automated systems with input from academic and clinical experts, the systems can be refined so that the accuracy of their detection of possible PTSD signals is comparable to that of psychologists reading the same online posts. While a portion of the literature on this and related topics explores the correlation between text patterns in archived documents and PTSD, no literature to date describes a system performing real-time analysis. Our system allows analysts to quickly identify, review, and validate online posts which have been flagged as exhibiting signs or symptoms of PTSD and enables follow-up, thus allowing for the presentation of treatment options to the authors of those posts. We describe the ontology of PTSD-related terms (i.e., terms which signal PTSD and related conditions) that need to be tracked, the algorithms used for extraction of the intensity of these signals, and the training process used to fine-tune sentiment analysis algorithms. We then present the results of processing a validation data set, different from the training set, comparing the algorithmic output with opinions of clinical psychologists, and explain how the concept can be extended to detect signals of other psychological conditions. We present a sample system architecture and implementation which can be used to engage users and theirfamilies, either anonymously or eponymously, and use the sentiment extraction algorithms as an early screening tool to alert clinicians to participants who may require close monitoring or follow-up. Finally, we describe a user test conducted with users recruited from the Veteran population and present the results of the analyses on the data.

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    Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Taschenbuch. Condizione: Neu. Sentiment Analysis for PTSD Signals | Vadim Kagan (u. a.) | Taschenbuch | SpringerBriefs in Computer Science | x | Englisch | 2013 | Springer | EAN 9781461430964 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Paperback. Condizione: Like New. Like New. book.

  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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  • Lingua: Inglese

    Editore: Springer New York Okt 2013, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techniques such as sentiment mining can be used in real-time to identify posts that contain PTSD-related signals, flag those posts, and bring them to the attention of psychologists, thus providing an automated flag and referral capability. The use of sentiment extraction technologies allows automatic in-depth analysis of opinions and emotions expressed by individuals in their online posts. By training these automated systems with input from academic and clinical experts, the systems can be refined so that the accuracy of their detection of possible PTSD signals is comparable to that of psychologists reading the same online posts. While a portion of the literature on this and related topics explores the correlation between text patterns in archived documents and PTSD, no literature to date describes a system performing real-time analysis. Our system allows analysts to quickly identify, review, and validate online posts which have been flagged as exhibiting signs or symptoms of PTSD and enables follow-up, thus allowing for the presentation of treatment options to the authors of those posts. We describe the ontology of PTSD-related terms (i.e., terms which signal PTSD and related conditions) that need to be tracked, the algorithms used for extraction of the intensity of these signals, and the training process used to fine-tune sentiment analysis algorithms. We then present the results of processing a validation data set, different from the training set, comparing the algorithmic output with opinions of clinical psychologists, and explain how the concept can be extended to detect signals of other psychological conditions. We present a sample system architecture and implementation which can be used to engage users and their families, either anonymously or eponymously, and use the sentiment extraction algorithms as an early screening tool to alert clinicians to participants who may require close monitoring or follow-up. Finally, we describe a user test conducted with users recruited from the Veteran population and present the results of the analyses on the data. 92 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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    EUR 74,77

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    Condizione: New. Print on Demand pp. 92 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

  • Lingua: Inglese

    Editore: Springer, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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    EUR 77,04

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    Condizione: New. PRINT ON DEMAND pp. 92.

  • Lingua: Inglese

    Editore: Springer New York, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techn.

  • Lingua: Inglese

    Editore: Springer, Springer Okt 2013, 2013

    1461430968 / 9781461430964

    Serie: Libro 103 di 322 - SpringerBriefs in Computer Science

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techniques such as sentiment mining can be used in real-time to identify posts that contain PTSD-related signals, flag those posts, and bring them to the attention of psychologists, thus providing an automated flag and referral capability. The use of sentiment extraction technologies allows automatic in-depth analysis of opinions and emotions expressed by individuals in their online posts. By training these automated systems with input from academic and clinical experts, the systems can be refined so that the accuracy of their detection of possible PTSD signals is comparable to that of psychologists reading the same online posts. While a portion of the literature on this and related topics explores the correlation between text patterns in archived documents and PTSD, no literature to date describes a system performing real-time analysis. Our system allows analysts to quickly identify, review, and validate online posts which have been flagged as exhibiting signs or symptoms of PTSD and enables follow-up, thus allowing for the presentation of treatment options to the authors of those posts. We describe the ontology of PTSD-related terms (i.e., terms which signal PTSD and related conditions) that need to be tracked, the algorithms used for extraction of the intensity of these signals, and the training process used to fine-tune sentiment analysis algorithms. We then present the results of processing a validation data set, different from the training set, comparing the algorithmic output with opinions of clinical psychologists, and explain how the concept can be extended to detect signals of other psychological conditions. We present a sample system architecture and implementation which can be used to engage users and theirfamilies, either anonymously or eponymously, and use the sentiment extraction algorithms as an early screening tool to alert clinicians to participants who may require close monitoring or follow-up. Finally, we describe a user test conducted with users recruited from the Veteran population and present the results of the analyses on the data.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 92 pp. Englisch.