{"title":"基于统计方法的网络挖掘情感分析","authors":"K. Sanjay, A. Danti","doi":"10.1109/ICPCSI.2017.8391818","DOIUrl":null,"url":null,"abstract":"Opinion mining or sentimental analysis plays important role in the data mining process. In the proposed method, opinions are classified using various statistical measures to provide ratings to help the sentimental analysis of big data. Experimental results demonstrate the efficiency of the proposed method to help in analysis of quality of product, marketers evaluation of success of a new product launched, determine which versions of a product or service are popular and identify demographics like or dislike of product features, etc.","PeriodicalId":6589,"journal":{"name":"2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI)","volume":"21 1","pages":"767-771"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Sentimental analysis on web mining using statistical measures\",\"authors\":\"K. Sanjay, A. Danti\",\"doi\":\"10.1109/ICPCSI.2017.8391818\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Opinion mining or sentimental analysis plays important role in the data mining process. In the proposed method, opinions are classified using various statistical measures to provide ratings to help the sentimental analysis of big data. Experimental results demonstrate the efficiency of the proposed method to help in analysis of quality of product, marketers evaluation of success of a new product launched, determine which versions of a product or service are popular and identify demographics like or dislike of product features, etc.\",\"PeriodicalId\":6589,\"journal\":{\"name\":\"2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI)\",\"volume\":\"21 1\",\"pages\":\"767-771\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPCSI.2017.8391818\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPCSI.2017.8391818","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sentimental analysis on web mining using statistical measures
Opinion mining or sentimental analysis plays important role in the data mining process. In the proposed method, opinions are classified using various statistical measures to provide ratings to help the sentimental analysis of big data. Experimental results demonstrate the efficiency of the proposed method to help in analysis of quality of product, marketers evaluation of success of a new product launched, determine which versions of a product or service are popular and identify demographics like or dislike of product features, etc.