Kagan Vadim (19 results)
NOT TO PERISH: Articles by an American Professor of Russian
Croft, Lee B.; Baehr, Alicia C.; Heuer, Patrick J.; Nielsen, Jaime R.; Sarlo, Shane C.; Tribble, Shamella; Abbott, Andrew W.; Ecton, Jeremy; Harris, Jon; Kagan, Vadim S.
- Softcover
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NOT TO PERISH: Articles by an American Professor of Russian
Croft, Lee B.; Baehr, Alicia C.; Heuer, Patrick J.; Nielsen, Jaime R.; Sarlo, Shane C.; Tribble, Shamella; Abbott, Andrew W.; Ecton, Jeremy; Harris, Jon; Kagan, Vadim S.
- Softcover
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Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
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Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Language: English
Published by Springer 2013-10, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: Chiron Media, Wallingford, United KingdomChiron Media
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Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
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Condition: New. pp. 92.
Language: English
Published by Springer-Verlag New York Inc, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 81 pages. 9.00x6.00x0.25 inches. In Stock.
Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: 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 computatio…nal 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.
More imagesLanguage: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: 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.
Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
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Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: Mispah books, Redhill, SURRE, United KingdomMispah books
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Paperback. Condition: Like New. Like New. book.
Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
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Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer New York Okt 2013, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: 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 eme…rging 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.
Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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Condition: 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.
Language: English
Published by Springer, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Condition: New. PRINT ON DEMAND pp. 92.
Language: English
Published by Springer New York, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Condition: 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 e…xplores how emerging computational techn.
Language: English
Published by Springer, Springer Okt 2013, 2013
Series: Book 103 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: 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 emergin…g 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.
