{"title":"通过整合多个知识来源来量化客户评论","authors":"Yuanchao Liu, Xinping Li, Mingjiang Wang","doi":"10.1145/3318299.3318309","DOIUrl":null,"url":null,"abstract":"The recent emergence of a large volume of customer reviews on e--commerce web sites has raised concerns on the provision of intuitive and comprehensive reputation comparisons of feature dimensions. In this paper, we propose and implement a product reputation mining prototype system. A multiple-knowledge based F-O pair extraction model, which is the center piece of our work, is presented for conducting analyses toward deeper sentence-level comprehension of sentiments in customer reviews. Experimental results demonstrate the effectiveness of the proposed method.","PeriodicalId":164987,"journal":{"name":"International Conference on Machine Learning and Computing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantifying Customer Review by Integrating Multiple Source of Knowledge\",\"authors\":\"Yuanchao Liu, Xinping Li, Mingjiang Wang\",\"doi\":\"10.1145/3318299.3318309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recent emergence of a large volume of customer reviews on e--commerce web sites has raised concerns on the provision of intuitive and comprehensive reputation comparisons of feature dimensions. In this paper, we propose and implement a product reputation mining prototype system. A multiple-knowledge based F-O pair extraction model, which is the center piece of our work, is presented for conducting analyses toward deeper sentence-level comprehension of sentiments in customer reviews. Experimental results demonstrate the effectiveness of the proposed method.\",\"PeriodicalId\":164987,\"journal\":{\"name\":\"International Conference on Machine Learning and Computing\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Machine Learning and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3318299.3318309\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Machine Learning and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3318299.3318309","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantifying Customer Review by Integrating Multiple Source of Knowledge
The recent emergence of a large volume of customer reviews on e--commerce web sites has raised concerns on the provision of intuitive and comprehensive reputation comparisons of feature dimensions. In this paper, we propose and implement a product reputation mining prototype system. A multiple-knowledge based F-O pair extraction model, which is the center piece of our work, is presented for conducting analyses toward deeper sentence-level comprehension of sentiments in customer reviews. Experimental results demonstrate the effectiveness of the proposed method.