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_a9783319236544 _9978-3-319-23654-4 |
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_a10.1007/978-3-319-23654-4 _2doi |
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_aSpringer _cSpringer _dRU-ToGU |
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_a612.8 _223 |
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_aCambria, Erik. _eauthor. _9451154 |
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245 | 1 | 0 |
_aSentic Computing _helectronic resource _bA Common-Sense-Based Framework for Concept-Level Sentiment Analysis / _cby Erik Cambria, Amir Hussain. |
250 | _a1st ed. 2015. | ||
260 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2015. |
||
300 |
_aXXII, 176 p. 54 illus., 40 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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490 | 1 |
_aSocio-Affective Computing ; _v1 |
|
505 | 0 | _aIntroduction -- SenticNet -- Sentic Patterns -- Sentic Applications -- Conclusion -- Index. | |
520 | _aThis volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web. Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed: • Sentic Computing's multi-disciplinary approach to sentiment analysis-evidenced by the concomitant use of AI, linguistics and psychology for knowledge representation and inference • Sentic Computing’s shift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text • Sentic Computing's shift from statistics to linguistics-implemented by allowing sentiments to flow from concept to concept based on the dependency relation between clauses This volume is the first in the Series Socio-Affective Computing edited by Dr Amir Hussain and Dr Erik Cambria and will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction and systems. | ||
650 | 0 |
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650 | 0 |
_aNeurosciences. _9302217 |
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_aData mining. _9306371 |
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650 | 0 |
_aSemantics. _9309803 |
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650 | 0 |
_aCognitive psychology. _9566360 |
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650 | 1 | 4 |
_aBiomedicine. _9566246 |
650 | 2 | 4 |
_aNeurosciences. _9302217 |
650 | 2 | 4 |
_aData Mining and Knowledge Discovery. _9306372 |
650 | 2 | 4 |
_aSemantics. _9309803 |
650 | 2 | 4 |
_aCognitive Psychology. _9566362 |
700 | 1 |
_aHussain, Amir. _eauthor. _9330983 |
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710 | 2 |
_aSpringerLink (Online service) _9143950 |
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_aSocio-Affective Computing ; _9467876 |
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856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-23654-4 |
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