{"title":"使用简化情感分析的泰国食物评论文本摘要","authors":"P. Porntrakoon, Chayapol Moemeng, P. Santiprabhob","doi":"10.1109/JCSSE53117.2021.9493839","DOIUrl":null,"url":null,"abstract":"The review of a customer who had experienced using the products and services helps others make the purchasing decision. Especially in the food and beverage domain, Thai reviewers frequently write long reviews in multiple dimensions, requiring a longer time to read and understand the reviews' opinions. The Thai sentiment analysis can analyze the review's sentiment in food, environment, and service dimensions and generate the review summary accordingly. Readers can save time in reading only the review summary and perceive the sentiments in the original review. In this paper, we propose a method to analyze the sentiment in Thai food review and generate a summary with the positive and negative sentiments in the review. The results show that our proposed method can generate 1,876 review summaries from 4,000 original reviews, which is equivalent to 46.68%. The total number of words in the review summaries is only 5.13% of the original reviews, with an average accuracy of 65.25% in Type 1 and 85.05% in Type 2.","PeriodicalId":437534,"journal":{"name":"2021 18th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Text Summarization for Thai Food Reviews using Simplified Sentiment Analysis\",\"authors\":\"P. Porntrakoon, Chayapol Moemeng, P. Santiprabhob\",\"doi\":\"10.1109/JCSSE53117.2021.9493839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The review of a customer who had experienced using the products and services helps others make the purchasing decision. Especially in the food and beverage domain, Thai reviewers frequently write long reviews in multiple dimensions, requiring a longer time to read and understand the reviews' opinions. The Thai sentiment analysis can analyze the review's sentiment in food, environment, and service dimensions and generate the review summary accordingly. Readers can save time in reading only the review summary and perceive the sentiments in the original review. In this paper, we propose a method to analyze the sentiment in Thai food review and generate a summary with the positive and negative sentiments in the review. The results show that our proposed method can generate 1,876 review summaries from 4,000 original reviews, which is equivalent to 46.68%. The total number of words in the review summaries is only 5.13% of the original reviews, with an average accuracy of 65.25% in Type 1 and 85.05% in Type 2.\",\"PeriodicalId\":437534,\"journal\":{\"name\":\"2021 18th International Joint Conference on Computer Science and Software Engineering (JCSSE)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 18th International Joint Conference on Computer Science and Software Engineering (JCSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/JCSSE53117.2021.9493839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 18th International Joint Conference on Computer Science and Software Engineering (JCSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/JCSSE53117.2021.9493839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Text Summarization for Thai Food Reviews using Simplified Sentiment Analysis
The review of a customer who had experienced using the products and services helps others make the purchasing decision. Especially in the food and beverage domain, Thai reviewers frequently write long reviews in multiple dimensions, requiring a longer time to read and understand the reviews' opinions. The Thai sentiment analysis can analyze the review's sentiment in food, environment, and service dimensions and generate the review summary accordingly. Readers can save time in reading only the review summary and perceive the sentiments in the original review. In this paper, we propose a method to analyze the sentiment in Thai food review and generate a summary with the positive and negative sentiments in the review. The results show that our proposed method can generate 1,876 review summaries from 4,000 original reviews, which is equivalent to 46.68%. The total number of words in the review summaries is only 5.13% of the original reviews, with an average accuracy of 65.25% in Type 1 and 85.05% in Type 2.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
