000			03504nam a22004215i 4500
988			_aEbook_one2one
999			_c81527 _d81527 _x1
001			81527
003			ES-MaUEC
005			20240611040137.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			151210s2015 gw | s |||| 0|eng d
020			_a9783319236544
024	7		_a10.1007/978-3-319-23654-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.5913 _b2015 EB
100	1		_aCambria, Erik _0Local _0http://id.loc.gov/authorities/names/no2012155591 _1http://viaf.org/viaf/283846500 _993992
245	1	0	_aSentic Computing : _bA Common-Sense-Based Framework for Concept-Level Sentiment Analysis _cby Erik Cambria, Amir Hussain.
250			_a1st ed. 2015.
264		1	_aCham, Switzerland _bSpringer _c2015
300			_a1 recurso en línea (XXII, 176 páginas) _b54 ilustraciones, 40 ilustraciones en color
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_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: â€� Â{u396E}tic Computing's multi-disciplinary approach to sentimentÂ{u2821}analysis-evidenced byÂ{u4A25} concomitant use of AI, linguistics and psychology for knowledge representation and inference â€� Â{u396E}tic Computingâ€{u3833}hift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text â€� Â{u396E}tic 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 byÂ{u4CA0} Amir HussainÂ{u086E}d Dr Erik CambriaÂ{u1BA4} will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction and systems.
988			_aEBOOK, EBSPRINGER, GOBI_sep2018
650		7	_aSemántica _xProceso de datos _9175270 _2embne
650		7	_aInteligencia artificial _2embne _9413115
700	1		_aHussain, Amir _0Local _1http://viaf.org/viaf/75831747 _986026
710	2		_aSpringerLink (Online service) _0Local _0http://id.loc.gov/authorities/names/no2005046756 _1http://viaf.org/viaf/148105729 _9106996
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-23654-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
907			_a.b12901179 _b10-10-17 _c18-01-16
942			_2lcc _cLE
945			_aRC321-580 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11570799 _z06-04-17
998			_b10/2018 _dz _ek _feng _ggw _h0