Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews
Due to the large amount of opinions available on the websites, tourists are often overwhelmed with information and find it extremely difficult to use the available information to make a decision about the tourist places to visit. A number of opinion mining methods have been proposed in the past to i...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2016/6965725 |
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| _version_ | 1832558121431597056 |
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| author | Muhammad Afzaal Muhammad Usman A. C. M. Fong Simon Fong Yan Zhuang |
| author_facet | Muhammad Afzaal Muhammad Usman A. C. M. Fong Simon Fong Yan Zhuang |
| author_sort | Muhammad Afzaal |
| collection | DOAJ |
| description | Due to the large amount of opinions available on the websites, tourists are often overwhelmed with information and find it extremely difficult to use the available information to make a decision about the tourist places to visit. A number of opinion mining methods have been proposed in the past to identify and classify an opinion into positive or negative. Recently, aspect based opinion mining has been introduced which targets the various aspects present in the opinion text. A number of existing aspect based opinion classification methods are available in the literature but very limited research work has targeted the automatic aspect identification and extraction of implicit, infrequent, and coreferential aspects. Aspect based classification suffers from the presence of irrelevant sentences in a typical user review. Such sentences make the data noisy and degrade the classification accuracy of the machine learning algorithms. This paper presents a fuzzy aspect based opinion classification system which efficiently extracts aspects from user opinions and perform near to accurate classification. We conducted experiments on real world datasets to evaluate the effectiveness of our proposed system. Experimental results prove that the proposed system not only is effective in aspect extraction but also improves the classification accuracy. |
| format | Article |
| id | doaj-art-a5f335bd86594bca8baf8e26f8a78fb2 |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-a5f335bd86594bca8baf8e26f8a78fb22025-02-03T01:33:11ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2016-01-01201610.1155/2016/69657256965725Fuzzy Aspect Based Opinion Classification System for Mining Tourist ReviewsMuhammad Afzaal0Muhammad Usman1A. C. M. Fong2Simon Fong3Yan Zhuang4Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, PakistanShaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, PakistanUniversity of Glasgow, Glasgow, UKUniversity of Macau, MacauUniversity of Macau, MacauDue to the large amount of opinions available on the websites, tourists are often overwhelmed with information and find it extremely difficult to use the available information to make a decision about the tourist places to visit. A number of opinion mining methods have been proposed in the past to identify and classify an opinion into positive or negative. Recently, aspect based opinion mining has been introduced which targets the various aspects present in the opinion text. A number of existing aspect based opinion classification methods are available in the literature but very limited research work has targeted the automatic aspect identification and extraction of implicit, infrequent, and coreferential aspects. Aspect based classification suffers from the presence of irrelevant sentences in a typical user review. Such sentences make the data noisy and degrade the classification accuracy of the machine learning algorithms. This paper presents a fuzzy aspect based opinion classification system which efficiently extracts aspects from user opinions and perform near to accurate classification. We conducted experiments on real world datasets to evaluate the effectiveness of our proposed system. Experimental results prove that the proposed system not only is effective in aspect extraction but also improves the classification accuracy.http://dx.doi.org/10.1155/2016/6965725 |
| spellingShingle | Muhammad Afzaal Muhammad Usman A. C. M. Fong Simon Fong Yan Zhuang Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews Advances in Fuzzy Systems |
| title | Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews |
| title_full | Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews |
| title_fullStr | Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews |
| title_full_unstemmed | Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews |
| title_short | Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews |
| title_sort | fuzzy aspect based opinion classification system for mining tourist reviews |
| url | http://dx.doi.org/10.1155/2016/6965725 |
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