{"title":"基于模糊集的数字印度方案意见挖掘","authors":"P. Manoharan, L. Agilandeeswari, M. S. Praneeth","doi":"10.1504/IJSCCPS.2017.10005811","DOIUrl":null,"url":null,"abstract":"In this paper, we describe the development of opinion mining for digital India (OMDI) scheme using fuzzy sets. According to people's opinions and reviews, the sentiment classifier will classify the emotion and polarity levels of the review. In this modern world, majority of the people will provide their feedback or opinions on the product that has been increased. The opinion mining results will be useful for the users to make better decision. For the classification of sentiment Naive Bayes and fuzzy logic (intuitionistic fuzzy sets) is utilised. By using these algorithms, we defined the polarity levels of the opinions such as positive, negative and neutral. In general, the sentiment classification will be done by utilising NLP, machine learning, statistical approach and classification methods. By mining powerful reasoning potential of fuzzy logics, we have accredited the polarities to the people's reviews according to their usage. Fuzzy logic deals with the vagueness by accrediting the continuous membership values to opinion words according to their usage in substance.","PeriodicalId":220482,"journal":{"name":"Int. J. Soc. Comput. Cyber Phys. Syst.","volume":"181 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Opinion mining for digital India scheme using fuzzy sets\",\"authors\":\"P. Manoharan, L. Agilandeeswari, M. S. Praneeth\",\"doi\":\"10.1504/IJSCCPS.2017.10005811\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we describe the development of opinion mining for digital India (OMDI) scheme using fuzzy sets. According to people's opinions and reviews, the sentiment classifier will classify the emotion and polarity levels of the review. In this modern world, majority of the people will provide their feedback or opinions on the product that has been increased. The opinion mining results will be useful for the users to make better decision. For the classification of sentiment Naive Bayes and fuzzy logic (intuitionistic fuzzy sets) is utilised. By using these algorithms, we defined the polarity levels of the opinions such as positive, negative and neutral. In general, the sentiment classification will be done by utilising NLP, machine learning, statistical approach and classification methods. By mining powerful reasoning potential of fuzzy logics, we have accredited the polarities to the people's reviews according to their usage. Fuzzy logic deals with the vagueness by accrediting the continuous membership values to opinion words according to their usage in substance.\",\"PeriodicalId\":220482,\"journal\":{\"name\":\"Int. J. Soc. Comput. Cyber Phys. Syst.\",\"volume\":\"181 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Soc. Comput. Cyber Phys. Syst.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJSCCPS.2017.10005811\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Soc. Comput. Cyber Phys. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJSCCPS.2017.10005811","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Opinion mining for digital India scheme using fuzzy sets
In this paper, we describe the development of opinion mining for digital India (OMDI) scheme using fuzzy sets. According to people's opinions and reviews, the sentiment classifier will classify the emotion and polarity levels of the review. In this modern world, majority of the people will provide their feedback or opinions on the product that has been increased. The opinion mining results will be useful for the users to make better decision. For the classification of sentiment Naive Bayes and fuzzy logic (intuitionistic fuzzy sets) is utilised. By using these algorithms, we defined the polarity levels of the opinions such as positive, negative and neutral. In general, the sentiment classification will be done by utilising NLP, machine learning, statistical approach and classification methods. By mining powerful reasoning potential of fuzzy logics, we have accredited the polarities to the people's reviews according to their usage. Fuzzy logic deals with the vagueness by accrediting the continuous membership values to opinion words according to their usage in substance.