An Enhanced Opinion Retrieval Approach on Arabic Text for Customer Requirements Expansion
| Autor: | Ahmed Sharaf Eldin Ahmed, Sarah Saad Eldin, Ammar Mohammed, Hesham A. Hefny |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Conditional random field
Information retrieval General Computer Science Point (typography) Computer science Arabic media_common.quotation_subject Rank (computer programming) Sentiment analysis 020206 networking & telecommunications 02 engineering and technology lcsh:QA75.5-76.95 language.human_language Task (project management) Opinion mining Opinion relevance model 0202 electrical engineering electronic engineering information engineering language Product features extraction 020201 artificial intelligence & image processing Quality (business) lcsh:Electronic computers. Computer science Opinion retrieval Heuristics media_common |
| Zdroj: | Journal of King Saud University: Computer and Information Sciences, Vol 33, Iss 3, Pp 351-363 (2021) |
| ISSN: | 1319-1578 |
| Popis: | Recently, most companies market their products on the web to recognize their customers’ requirements and to improve their services’ quality according to the customers’ feedback and opinions. A huge amount of reviews and opinions are posted daily on products. Obtaining and quickly analyzing these opinions become a difficult task. These opinions might lead to a tendency or disinclination to a specific point of view. To represent the products’ opinions from customers’ perspectives, opinion retrieval becomes a demanding and essential task for automatically extracting, analyzing, and summarizing customers’ reviews. Usually, online products are offered by several suppliers in e-commerce. Therefore, to keep up the competitiveness among suppliers, the need for innovative requirements is required. This paper proposed an enhanced opinion retrieval approach depending on the explicit feature based opinion mining. The proposed approach expands the initial products’ requirements using extended heuristics and linguistic patterns of the Arabic opinions. Besides the relevant score, several factors, like features’ weight, the opinion importance, and the sentiment polarity are used to rank the retrieved results. The experimental results show the capability of the proposed approach to automatically extract more innovative features compared to the conditional random field (CRF) results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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