Aspect extraction performance with POS tag pattern of dependency relation in aspect-based sentiment analysis
The most important task in aspect-based sentiment analysis (ABSA) is the aspect and sentiment word extraction. It is a challenge to identify and extract each aspect and it specific associated sentiment word correctly in the review sentence that consists of multiple aspects with various polarities ex...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2018
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| Online Access: | http://psasir.upm.edu.my/id/eprint/68799/ http://psasir.upm.edu.my/id/eprint/68799/1/Aspect%20extraction%20performance%20with%20POS%20tag%20pattern%20of%20dependency%20relation%20in%20aspect-based%20sentiment%20analysis.pdf |
| _version_ | 1848856229499109376 |
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| author | Shafie, Ana Salwa Mohd Sharef, Nurfadhlina Azmi Murad, Masrah Azrifah Azman, Azreen |
| author_facet | Shafie, Ana Salwa Mohd Sharef, Nurfadhlina Azmi Murad, Masrah Azrifah Azman, Azreen |
| author_sort | Shafie, Ana Salwa |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The most important task in aspect-based sentiment analysis (ABSA) is the aspect and sentiment word extraction. It is a challenge to identify and extract each aspect and it specific associated sentiment word correctly in the review sentence that consists of multiple aspects with various polarities expressed for multiple sentiments. By exploiting the dependency relation between words in a review, the multiple aspects and its corresponding sentiment can be identified. However, not all types of dependency relation patterns are able to extract candidate aspect and sentiment word pairs. In this paper, a preliminary study was performed on the performance of different type of dependency relation with different POS tag patterns in pre-extracting candidate aspect from customer review. The result contributes to the identification of the specific type dependency relation with it POS tag pattern that lead to high aspect extraction performance. The combination of these dependency relations offers a solution for single aspect single sentiment and multi aspect multi sentiment cases. |
| first_indexed | 2025-11-15T11:38:20Z |
| format | Conference or Workshop Item |
| id | upm-68799 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:38:20Z |
| publishDate | 2018 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-687992020-05-25T01:52:32Z http://psasir.upm.edu.my/id/eprint/68799/ Aspect extraction performance with POS tag pattern of dependency relation in aspect-based sentiment analysis Shafie, Ana Salwa Mohd Sharef, Nurfadhlina Azmi Murad, Masrah Azrifah Azman, Azreen The most important task in aspect-based sentiment analysis (ABSA) is the aspect and sentiment word extraction. It is a challenge to identify and extract each aspect and it specific associated sentiment word correctly in the review sentence that consists of multiple aspects with various polarities expressed for multiple sentiments. By exploiting the dependency relation between words in a review, the multiple aspects and its corresponding sentiment can be identified. However, not all types of dependency relation patterns are able to extract candidate aspect and sentiment word pairs. In this paper, a preliminary study was performed on the performance of different type of dependency relation with different POS tag patterns in pre-extracting candidate aspect from customer review. The result contributes to the identification of the specific type dependency relation with it POS tag pattern that lead to high aspect extraction performance. The combination of these dependency relations offers a solution for single aspect single sentiment and multi aspect multi sentiment cases. IEEE 2018 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/68799/1/Aspect%20extraction%20performance%20with%20POS%20tag%20pattern%20of%20dependency%20relation%20in%20aspect-based%20sentiment%20analysis.pdf Shafie, Ana Salwa and Mohd Sharef, Nurfadhlina and Azmi Murad, Masrah Azrifah and Azman, Azreen (2018) Aspect extraction performance with POS tag pattern of dependency relation in aspect-based sentiment analysis. In: 2018 Fourth International Conference on Information Retrieval and Knowledge Management (CAMP'18), 26-28 Mar. 2018, Le Méridien Kota Kinabalu, Sabah, Malaysia. (pp. 107-112). 10.1109/INFRKM.2018.8464692 |
| spellingShingle | Shafie, Ana Salwa Mohd Sharef, Nurfadhlina Azmi Murad, Masrah Azrifah Azman, Azreen Aspect extraction performance with POS tag pattern of dependency relation in aspect-based sentiment analysis |
| title | Aspect extraction performance with POS tag pattern of dependency relation in aspect-based sentiment analysis |
| title_full | Aspect extraction performance with POS tag pattern of dependency relation in aspect-based sentiment analysis |
| title_fullStr | Aspect extraction performance with POS tag pattern of dependency relation in aspect-based sentiment analysis |
| title_full_unstemmed | Aspect extraction performance with POS tag pattern of dependency relation in aspect-based sentiment analysis |
| title_short | Aspect extraction performance with POS tag pattern of dependency relation in aspect-based sentiment analysis |
| title_sort | aspect extraction performance with pos tag pattern of dependency relation in aspect-based sentiment analysis |
| url | http://psasir.upm.edu.my/id/eprint/68799/ http://psasir.upm.edu.my/id/eprint/68799/ http://psasir.upm.edu.my/id/eprint/68799/1/Aspect%20extraction%20performance%20with%20POS%20tag%20pattern%20of%20dependency%20relation%20in%20aspect-based%20sentiment%20analysis.pdf |