Abstract
This paper gives the description of the TGB system submitted to the Aspect Based Sentiment Analysis Task of SemEval-2016 (Task 5). The system is built on linear binary classifiers for aspect category classification (Slot 1), on lexicon-based detection for opinion target expressions extraction (Slot 2), and on linear multi-class classifiers for sentiment polarity detection (Slot 3). We conducted several different approaches for feature selection to improve classification performance on both Slot 1 and Slot 3. Our proposed methods are easily adaptable to all languages and domains since they are built as constrained systems which do not use any additional resources other than the provided datasets and which uses standard preprocessing methods.
Original language | English |
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Title of host publication | SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 337-341 |
Number of pages | 5 |
ISBN (Electronic) | 9781941643952 |
DOIs | |
Publication status | Published - 2016 |
Event | 10th International Workshop on Semantic Evaluation, SemEval 2016 - San Diego, United States Duration: 16 Jun 2016 → 17 Jun 2016 |
Publication series
Name | SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings |
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Conference
Conference | 10th International Workshop on Semantic Evaluation, SemEval 2016 |
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Country/Territory | United States |
City | San Diego |
Period | 16/06/16 → 17/06/16 |
Bibliographical note
Publisher Copyright:© 2016 Association for Computational Linguistics.
Funding
This work is accomplished as a part of a TUBITAK-TEYDEB (The Scientific and Technological Research Council of Turkey - Technology and Innovation Funding Programs Directorate) project (grant number: 3140671) in “Turkcell Global Bilgi” Information Technology Department.
Funders | Funder number |
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Scientific and Technological Research Council of Turkey - Technology and Innovation Funding Programs Directorate | 3140671 |
TUBITAK-TEYDEB |