| Autor: |
Younis Umair, Asghar Muhammad Zubair, Khan Adil, Khan Alamsher, Iqbal Javed, Jillani Nosheen |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Open Computer Science, Vol 10, Iss 1, Pp 461-477 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2299-1093 |
| DOI: |
10.1515/comp-2020-0148 |
| Popis: |
In recent times, comparative opinion mining applications have attracted both individuals and business organizations to compare the strengths and weakness of products. Prior works on comparative opinion mining have focused on applying a single classifier, limited comparative opinion labels, and limited dataset of product reviews, resulting in degraded performance for classifying comparative reviews. In this work, we perform multi-class comparative opinion mining by applying multiple machine learning classifiers using an increased number of comparative opinion labels (9 classes) on 4 datasets of comparative product reviews. The experimental results show that Random Forest classifier has outperformed the comparing algorithms in terms of improved accuracy, precision, recall and f-measure. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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