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Learning theories for noun-phrase sentiment composition
- Source :
- Petrakis, S; Klenner, M (2011). Learning theories for noun-phrase sentiment composition. In: 8th International NLPCS Workshop, Kopenhagen, 20 August 2011 - 21 August 2011. Samfundslitteratur, 179-188.
- Publication Year :
- 2011
-
Abstract
- The work presented here is an approach to Sentiment Analy- sis from a rule-based, compositional perspective. The proposed approach is characterized by three major points: (a) rules are automatically learned from annotated corpora using Inductive Logic Programming and represented as Prolog sets of clauses, (b) the focus is on the noun-phrase (NP) level, and (c) learning is performed on deep-parsed structures. We describe the process of annotating a collection of some 3000 German NPs of medium to quite complex structure, as well as the empirical evaluation of our implementation, in comparison with commonly used classifiers and a handcrafted rule-based system.
Details
- Database :
- OAIster
- Journal :
- Petrakis, S; Klenner, M (2011). Learning theories for noun-phrase sentiment composition. In: 8th International NLPCS Workshop, Kopenhagen, 20 August 2011 - 21 August 2011. Samfundslitteratur, 179-188.
- Notes :
- application/pdf, info:doi/10.5167/uzh-53322, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.ocn781834451
- Document Type :
- Electronic Resource