{"title":"Opinion based book recommendation using Naive Bayes classifier","authors":"Anand Shanker Tewari, T. S. Ansari, A. Barman","doi":"10.1109/IC3I.2014.7019672","DOIUrl":null,"url":null,"abstract":"In the rapidly increasing field of E-commerce, buyer is surrounded by many product information. However, search engines like Google, Baidu, can't satisfy the demands of buyer because the information about the product that the users want can't be obtain quickly, easily and correctly. So buyer has to spend lots of time in removing the unnecessary information. Many e-commerce website often request buyers to review products that they have already purchased. As the popularity of e-commerce is increasing day by day, the reviews from customers about the product receives also increasing heavily. As a result of this it is difficult for a buyer to read all the reviews to make a decision about the product purchase. In this paper, we extracted, summarize and categorize all the customer reviews of a book. This paper proposes a book recommendation technique based on opinion mining and Naïve Bayes classifier to recommend top ranking books to buyers. This paper also considered the important factor like price of the book while recommendation and presented a novel tabular efficient method for recommending books to the buyer, especially when the buyer is coming first time to the website.","PeriodicalId":430848,"journal":{"name":"2014 International Conference on Contemporary Computing and Informatics (IC3I)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Contemporary Computing and Informatics (IC3I)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3I.2014.7019672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In the rapidly increasing field of E-commerce, buyer is surrounded by many product information. However, search engines like Google, Baidu, can't satisfy the demands of buyer because the information about the product that the users want can't be obtain quickly, easily and correctly. So buyer has to spend lots of time in removing the unnecessary information. Many e-commerce website often request buyers to review products that they have already purchased. As the popularity of e-commerce is increasing day by day, the reviews from customers about the product receives also increasing heavily. As a result of this it is difficult for a buyer to read all the reviews to make a decision about the product purchase. In this paper, we extracted, summarize and categorize all the customer reviews of a book. This paper proposes a book recommendation technique based on opinion mining and Naïve Bayes classifier to recommend top ranking books to buyers. This paper also considered the important factor like price of the book while recommendation and presented a novel tabular efficient method for recommending books to the buyer, especially when the buyer is coming first time to the website.