000 02350nam a22003735i 4500
001 313369
003 MX-SnUAN
005 20160429160651.0
007 cr nn 008mamaa
008 150903s2012 ne | o |||| 0|eng d
020 _a9789400750708
_99789400750708
024 7 _a10.1007/9789400750708
_2doi
035 _avtls000367449
039 9 _a201509030715
_bVLOAD
_c201405070442
_dVLOAD
_y201402251622
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aR-RZ
100 1 _aCambria, Erik.
_eautor
_9355569
245 1 0 _aSentic Computing :
_bTechniques, Tools, and Applications /
_cby Erik Cambria, Amir Hussain.
264 1 _aDordrecht :
_bSpringer Netherlands :
_bImprint: Springer,
_c2012.
300 _axviii, 153 páginas 39 ilustraciones, 35 ilustraciones en color.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aSpringerBriefs in Cognitive Computation,
_x2212-6023 ;
_v2
500 _aSpringer eBooks
520 _aIn this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aHussain, Amir.
_eautor
_9303305
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9789400750692
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-94-007-5070-8
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c313369
_d313369