2021
DOI: 10.3390/s21020636
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SEOpinion: Summarization and Exploration of Opinion from E-Commerce Websites

Abstract: Recently, it has been found that e-commerce (EC) websites provide a large amount of useful information that exceed the human cognitive processing capacity. In order to help customers in comparing alternatives when buying a product, previous research authors have designed opinion summarization systems based on customer reviews. They ignored the template information provided by manufacturers, although its descriptive information has the most useful product characteristics and texts are linguistically correct, un… Show more

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Cited by 21 publications
(17 citation statements)
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“…Due to the importance of the product feature and opinion extraction to review summarization, Nyaung and Thein [35] refer the task of review summarization to relating the opinion words with respect to a certain feature. Mabrouk et al [36] proposed a methodology to summarize aspects and spot opinions regarding them using a combination of template information with customer reviews in two main phases. Recently, some deep neural models have been used in review summarization.…”
Section: Review Summarizationmentioning
confidence: 99%
“…Due to the importance of the product feature and opinion extraction to review summarization, Nyaung and Thein [35] refer the task of review summarization to relating the opinion words with respect to a certain feature. Mabrouk et al [36] proposed a methodology to summarize aspects and spot opinions regarding them using a combination of template information with customer reviews in two main phases. Recently, some deep neural models have been used in review summarization.…”
Section: Review Summarizationmentioning
confidence: 99%
“…To enhance accuracy, TL is essential to have the most suggestive contextual and exclusionary capacity in the feature extraction stage for many fields [17]. For example, online scraping [18], social media [19], sentiment classification [20], and medical image classification [17]. Therefore, this paper applies TL approaches to improve diagnostic reliability and reduce time-consuming decisions for clinicians.…”
Section: Introductionmentioning
confidence: 99%
“…Informative material is frequently overshadowed by unrelated and needless noise in most social media postings. Some prior study aims to obtain effective content utilizing text classifiers to process and translate these large amounts of social media data into corporate data [5]. Previous work specifically on event detection was centered on developing domain text classifiers [6].…”
Section: Introductionmentioning
confidence: 99%