Abstract
Opinion Question Answering (Opinion QA) is the task of enabling users to explore others opinions toward a particular service of product in order to make decisions. Arabic Opinion QA is more challenging due to its complex morphology compared to other languages and has many varieties dialects. On the other hand, there are insignificant research efforts and resources available that focus on Opinion QA in Arabic. This study aims to address the difficulties of Arabic opinion QA by proposing a hybrid method of lexicon-based approach and classification using Naïve Bayes classifier. The proposed method contains pre-processing phases such as, transformation, normalization and tokenization and exploiting auxiliary information (thesaurus). The lexicon-based approach is executed by replacing some words with its synonyms using the domain dictionary. The classification task is performed by Naïve Bayes classifier to classify the opinions based on the positive or negative sentiment polarity. The proposed method has been evaluated using the common information retrieval metrics i.e., Precision, Recall and F-measure. For comparison, three classifiers have been applied which are Naïve Bayes (NB), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). The experimental results have demonstrated that NB outperforms SVM and KNN by achieving 91% accuracy.
Highlights
IntroductionWith the dramatic expansion of the World Wide Web, the processing of investigating people’s opinions has subjective (yields opinion) or objective (yields fact) is called subjectivity classification
With the dramatic expansion of the World Wide Web, the processing of investigating people’s opinions has subjective or objective is called subjectivity classification
Subjectivity is the way that emotions and opinion can be expressed in the language while objectivity refers to the factual phrases
Summary
With the dramatic expansion of the World Wide Web, the processing of investigating people’s opinions has subjective (yields opinion) or objective (yields fact) is called subjectivity classification. Subjectivity is the way that emotions and opinion can be expressed in the language while objectivity refers to the factual phrases The problem of identifying documents whether it is subjective (yields opinion) or objective (yields fact) is called subjectivity classification. Question answering is the web facilitate the text analyzing which leads to extract the knowledge. Such process called sentiment analysis (Pang and Lee, 2008). QA is very challenging issue especially when dealing with opinion question answering which has emotions and opinion can be expressed in the language while objectivity refers to the factual phrases (Wiebe et al, 1999). The complexity of the Corresponding Author: Khalid Khalifa, Knowledge Technology Group, Center for Artificial Intelligence Technology (CAIT), Faculty of Information Science and Technology, University Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
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