Intelligent and Integrated Book Recommendation and Best Price Identifier System Using Machine Learning

  • Akanksha Goel
  • Divanshu Khandelwal
  • Jayant Mundhra
  • Ritu Tiwari
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 695)


When one wants to read something, it is tough to decide the just perfect one book that one would want to read. And, given such a system is conceived and the reader can find the book he/she wishes to read, how does he/she decide where to buy that book from? Again, there are a plethora of vendors selling the same book at different prices. Thus, this paper proposes a dynamic recommendation system by extracting the relevant data from different E-portals and applying Hybrid Filtering Approach (collaborative and content-based filtering) on the collected data to recommend the books. This system makes use of user-based collaborative filtering approach using cosine similarity rule and is optimized with bee algorithm, and the results are refined by applying natural language processing on the reviews. The paper also intends to solve cold start problem by extracting available user preferences from Facebook API.


Data analysis Nature-inspired algorithms Natural language processing Data scrapping Recommendation system 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Akanksha Goel
    • 1
  • Divanshu Khandelwal
    • 1
  • Jayant Mundhra
    • 1
  • Ritu Tiwari
    • 1
  1. 1.Robotics and Intelligent System Design LabABV-IIITM GwaliorGwaliorIndia

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