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  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bsz:mh39-85032
UN  - http://nbn-resolving.de/urn/resolver.pl?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  - 
TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Wiegand, Michael
A1  - Klakow, Dietrich
ED  - Angelova, Galia
ED  - Bontcheva, Kalina
ED  - Mitkov, Ruslan
ED  - Nikolov, Nikolai
T1  - Prototypical Opinion Holders: What We can Learn from Experts and Analysts
T2  - Proceedings of the International Conference on Recent Advances in Natural Language Processing 2011, Hissar, Bulgaria, 12-14 September, 2011
N2  - In order to automatically extract opinion holders, we propose to harness the contexts of prototypical opinion holders, i.e. common nouns, such as experts or analysts, that describe particular groups of people whose profession or occupation is to form and express opinions towards specific items. We assess their effectiveness in supervised learning where these contexts are regarded as labelled training data and in rule-based classification which uses predicates that frequently co-occur with mentions of the prototypical opinion holders. Finally, we also examine in how far knowledge gained from these contexts can compensate the lack of large amounts of labeled training data in supervised learning by considering various amounts of actually labeled training sets.
KW  - Computerlinguistik
KW  - Maschinelles Lernen
KW  - Text Mining
KW  - Information Extraction
KW  - Sentimentanalyse
KW  - Expertenmeinung
Y1  - 2011
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bsz:mh39-84674
UN  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bsz:mh39-84674
UR  - https://aclanthology.info/papers/R11-1039/r11-1039
SN  - 1313-8502
SS  - 1313-8502
SP  - 282
EP  - 288
PB  - Incoma Ltd.
CY  - Shoumen
ER  -