000 02513nam a22005055i 4500
001 978-94-007-5070-8
003 DE-He213
005 20140220083347.0
007 cr nn 008mamaa
008 120728s2012 ne | s |||| 0|eng d
020 _a9789400750708
_9978-94-007-5070-8
024 7 _a10.1007/978-94-007-5070-8
_2doi
050 4 _aR-RZ
072 7 _aMBGR
_2bicssc
072 7 _aMED000000
_2bisacsh
082 0 4 _a610
_223
100 1 _aCambria, Erik.
_eauthor.
245 1 0 _aSentic Computing
_h[electronic resource] :
_bTechniques, Tools, and Applications /
_cby Erik Cambria, Amir Hussain.
264 1 _aDordrecht :
_bSpringer Netherlands :
_bImprint: Springer,
_c2012.
300 _aXVIII, 153 p. 39 illus., 35 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Cognitive Computation,
_x2212-6023 ;
_v2
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.
650 0 _aMedicine.
650 0 _aData mining.
650 0 _aMathematics.
650 0 _aConsciousness.
650 1 4 _aBiomedicine.
650 2 4 _aBiomedicine general.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aMathematics, general.
650 2 4 _aLinguistics (general).
650 2 4 _aCognitive Psychology.
700 1 _aHussain, Amir.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9789400750692
830 0 _aSpringerBriefs in Cognitive Computation,
_x2212-6023 ;
_v2
856 4 0 _uhttp://dx.doi.org/10.1007/978-94-007-5070-8
912 _aZDB-2-SBL
999 _c104841
_d104841