Sentic Computing: Techniques, Tools, and ApplicationsIn 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. |
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Sentic Computing: Techniques, Tools, and Applications Erik Cambria,Amir Hussain No preview available - 2012 |
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according activation affective common sense affective information AffectiveSpace AffectNet allows applications approach associated Cambria classification clustering cognitive collection common sense knowledge compared computing ConceptNet concepts consists contains database depending describe detection developed dimension emotions engine evaluation example experience exploited expressed extracted fact feel hence human images important infer intelligent interaction Isanette knowledge base labels learning machine matrix means methods Mind module mood natural language negative objects obtained Open opinion mining particular patient perform polarity positive problem proposed rates reasoning relative represent representation resource retrieval rules Sect selected semantic sentence Sentic sentic computing sentiment analysis similar social space specific structure subjective Table tags task techniques topic troll understanding users usually values vector
Bibliographic information
| Title | Sentic Computing: Techniques, Tools, and Applications Volume 2 of SpringerBriefs in Cognitive Computation |
| Authors | Erik Cambria, Amir Hussain |
| Edition | illustrated |
| Publisher | Springer Science & Business Media, 2012 |
| ISBN | 9400750706, 9789400750708 |
| Length | 153 pages |
| Subjects | › › Computers / Data Science / Data Analytics Language Arts & Disciplines / General Language Arts & Disciplines / Linguistics / General Mathematics / General Medical / General Medical / Research Psychology / Cognitive Psychology & Cognition |
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