TY - CHAP U1 - Konferenzveröffentlichung A1 - Wiegand, Michael A1 - Klakow, Dietrich ED - Sandford Pedersen, Bolette ED - Nešpore, Gunta ED - Skadiņa, Inguna T1 - Convolution Kernels for Subjectivity Detection T2 - Proceedings of the 18th Nordic Conference of Computational Linguistics (NODALIDA 2011), May 11-13, 2011, Riga, Latvia N2 - In this paper, we explore different linguistic structures encoded as convolution kernels for the detection of subjective expressions. The advantage of convolution kernels is that complex structures can be directly provided to a classifier without deriving explicit features. The feature design for the detection of subjective expressions is fairly difficult and there currently exists no commonly accepted feature set. We consider various structures, such as constituency parse structures, dependency parse structures, and predicate-argument structures. In order to generalize from lexical information, we additionally augment these structures with clustering information and the task-specific knowledge of subjective words. The convolution kernels will be compared with a standard vector kernel. T3 - NEALT Proceedings Series - 11 KW - Computerlinguistik KW - Natürliche Sprache KW - Subjektivität KW - Maschinelles Lernen KW - Text Mining KW - Sentimentanalyse Y1 - 2011 U6 - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-85032 UN - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-85032 SN - 1736-6305 SS - 1736-6305 SP - 254 EP - 261 PB - Northern European Association for Language Technology CY - Uppsala ER -