Sentic Computing: Techniques, Tools, and Applications by Erik Cambria

By Erik Cambria

In this publication good judgment computing thoughts are extra constructed and utilized to bridge the semantic hole among word-level typical language information and the concept-level critiques conveyed by way of those. particularly, the ensemble software of graph mining and multi-dimensionality aid strategies is exploited on good judgment wisdom bases to increase a unique clever engine for open-domain opinion mining and sentiment research. The proposed strategy, termed sentic computing, plays a clause-level semantic research of textual content, which permits the inference of either the conceptual and emotional details linked to average language reviews and, therefore, a extra effective passage from (unstructured) textual details to (structured) machine-processable data.

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Philadelphia (2002). 11. : Learning multilingual subjective language via crosslingual projections. ACL. Prague, In (2007) 12. : Just how mad are you? Finding strong and weak opinion clauses. In: AAAI, pp. 761–769. San Jose (2004). 13. : Effects of adjective orientation and gradability on sentence subjectivity. COLING. Saarbrücken, In (2000) 14. : Learning subjective language. Comput. Linguist. 30(3) (2004). 15. : Exploiting subjectivity classification to improve information extraction. AAAI. Pittsburgh, In (2005) 16.

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Learning subjective language. Comput. Linguist. 30(3) (2004). 15. : Exploiting subjectivity classification to improve information extraction. AAAI. Pittsburgh, In (2005) 16. : Learning to classify documents according to genre. J. Am. Soc. Inf. Sci. Technol. 7(5) (2006). 17. : Variation across Speech and Writing. Cambridge University Press, Cambridge (1988) 18. : Applied Bayesian and Classical Inference: The Case of the Federalist Papers. Springer, Berlin (1984) 19. : Style-based text categorization: What newspaper am i reading?.

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