Prediction Of Service Rating By Exploring Behavior Of User

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@article{1700569,
      author = {Mohammad Athiqur Raheman, Nallagorla Jagadeesh, Pentayala Viswa Teja, Ramireddy Siva Krishna, Shaik Wasim Akram },
      title = {Prediction Of Service Rating By Exploring Behavior Of User},
      journal = {Iconic Research And Engineering Journals},
      year = {2018},
      volume = {1},
      number = {10},
      pages = {37-41},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1700569.pdf},
      abstract = {With the huge usage of social media large amount of data is generating through this website, so a user cannot predict alone on any kind of service or item either the nature of service or ratings on product that user wants to buy in future. So, a user needs a temporary platform to get the useful information on what user is in need.So,with the help of these data available on this platform one can predict user service rating by determining the social users rating behavior. The data is important for new users to estimate whether these predictions meet their necessities previously sharing. In this paper, we propose a user benefit rating prediction approach by estimating social users' rating behavior. In our opinion, the rating behavior in recommender system could be derived in these aspects: 1) when user rated the item, what the rating is, 2) what the item is, 3) what the user interest that we could dig from his/her rating records is, and 4) how the user?s rating behavior diffuses among his/her social friends. Therefore, we propose a concept of the rating schedule to represent users? daily rating behaviors. Finally, through this proposed work any user can get universal predicted data on any kind of services and products that are available on this platform.},
      keywords = {Data mining, recommender system, social user behavior, social networks.},
      month = {April},
  }