A Hybrid System for Subjectivity Analysis
We suggested different structured hybrid systems for the sentence-level subjectivity analysis based on three supervised machine learning algorithms, namely, Hidden Markov Model, Fuzzy Control System, and Adaptive Neuro-Fuzzy Inference System. The suggested feature extraction algorithm in our experim...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2018/2371621 |
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| _version_ | 1832545490732843008 |
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| author | Samir Rustamov |
| author_facet | Samir Rustamov |
| author_sort | Samir Rustamov |
| collection | DOAJ |
| description | We suggested different structured hybrid systems for the sentence-level subjectivity analysis based on three supervised machine learning algorithms, namely, Hidden Markov Model, Fuzzy Control System, and Adaptive Neuro-Fuzzy Inference System. The suggested feature extraction algorithm in our experiment computes a feature vector using statistical textual terms frequencies in a training dataset not having the use of any lexical knowledge except tokenization. Taking into consideration this fact, the above-mentioned methods may be employed in other languages as these methods do not utilize the morphological, syntactical, and lexical analysis in the classification problems. |
| format | Article |
| id | doaj-art-2b8d56f8ce8e4787a838bb678a4af8f7 |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-2b8d56f8ce8e4787a838bb678a4af8f72025-02-03T07:25:39ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2018-01-01201810.1155/2018/23716212371621A Hybrid System for Subjectivity AnalysisSamir Rustamov0ADA University, Ahmadbey Aghaoglu Street 11, Bakı AZ1008, Baku, AzerbaijanWe suggested different structured hybrid systems for the sentence-level subjectivity analysis based on three supervised machine learning algorithms, namely, Hidden Markov Model, Fuzzy Control System, and Adaptive Neuro-Fuzzy Inference System. The suggested feature extraction algorithm in our experiment computes a feature vector using statistical textual terms frequencies in a training dataset not having the use of any lexical knowledge except tokenization. Taking into consideration this fact, the above-mentioned methods may be employed in other languages as these methods do not utilize the morphological, syntactical, and lexical analysis in the classification problems.http://dx.doi.org/10.1155/2018/2371621 |
| spellingShingle | Samir Rustamov A Hybrid System for Subjectivity Analysis Advances in Fuzzy Systems |
| title | A Hybrid System for Subjectivity Analysis |
| title_full | A Hybrid System for Subjectivity Analysis |
| title_fullStr | A Hybrid System for Subjectivity Analysis |
| title_full_unstemmed | A Hybrid System for Subjectivity Analysis |
| title_short | A Hybrid System for Subjectivity Analysis |
| title_sort | hybrid system for subjectivity analysis |
| url | http://dx.doi.org/10.1155/2018/2371621 |
| work_keys_str_mv | AT samirrustamov ahybridsystemforsubjectivityanalysis AT samirrustamov hybridsystemforsubjectivityanalysis |