Piyush Anil Bodhankar, Rajesh K. Nasare, G. Yenurkar
{"title":"Designing a Sales Prediction Model in Tourism Industry and Hotel Recommendation Based on Hybrid Recommendation","authors":"Piyush Anil Bodhankar, Rajesh K. Nasare, G. Yenurkar","doi":"10.1109/ICCMC.2019.8819792","DOIUrl":null,"url":null,"abstract":"As the trend of e-commerce and online shopping is increasing day by day, we need a method which can be helpful to decide whether to buy the product or not. Here the opinions of the other customers and rating for that product can be used as a considerably good parameter for designing such a system. With the development of new technologies we have a possible solution in the form of recommendation system. Recommendation system gives an important help in providing the necessary information to user based on personalized and practical services. The most vital technique in this field is which plays a crucial role is Collaborative filtering. In this paper we present a recommendations system for tourism and hotel based on enhanced Collaborative filtering approach.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCMC.2019.8819792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
As the trend of e-commerce and online shopping is increasing day by day, we need a method which can be helpful to decide whether to buy the product or not. Here the opinions of the other customers and rating for that product can be used as a considerably good parameter for designing such a system. With the development of new technologies we have a possible solution in the form of recommendation system. Recommendation system gives an important help in providing the necessary information to user based on personalized and practical services. The most vital technique in this field is which plays a crucial role is Collaborative filtering. In this paper we present a recommendations system for tourism and hotel based on enhanced Collaborative filtering approach.