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Social media reviews based hotel recommendation system using collaborative filtering and big data

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Abstract

To eliminate the concerns of cold-start and scalability within the filtering, collaborative recommendation system for a hotel under the ranking list for the customer; this study proposed an extensive data analysis for such an application. Alongside, the application is very user-friendly. Technology keeps growing daily and is also very helpful in the future. This paper brings out the innovation. This approach configures the latest variant of CNN termed as Capsule Network (CapsNet) to recommend the best suited hotel based on user collaboration. With the help of this application, we can make precise and accurate recommendations to the user. Besides, generally employed, the procedure adopted for the model recommended integrated with the filtering practice that includes analyzing user's preferences and making product or service recommendations through a similarity index among the ratings specified in the database. Finally, the merging technique employed in the system is discussed and evaluated on standard data sets based on the general architectural design of the recommendation system. An enhanced strategy attains fusion idea of filtering technique in collaborative to classified data for addressing this issue. To put the proposed approach to the test, we employ hotel recommendation data. Also, the outcome proved the best findings of the comprehensive list taken as the top listed hotels from which the scale has been considered through the proposed method.

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Acknowledgements

The researchers would like to acknowledge Deanship of Scientific Research, Taif University for funding this work.

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Authors and Affiliations

  1. Department of ECE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, 522302, India

    Shaik Hasane Ahammad & B. T. P. Madhav

  2. MIT Academy of Engineering, Alandi, Pune, India

    Sandeep Dwarkanath

  3. Symbiosis Institute of Technology, Pune, Symbiosis International, Pune, India

    Rahul Joshi

  4. ECE Department, Dadi Institute of Engineering and Technology, Anakapalle, Visakhapatnam, India

    P. Poorna Priya

  5. Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, 21944, Taif, Saudi Arabia

    Osama S. Faragallah

  6. Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, 21944, Taif, Saudi Arabia

    Mahmoud M. A. Eid

  7. Electronics and Electrical Communications Engineering Department, Faculty of Electronic Engineering, Menoufia University, Menouf, 32951, Egypt

    Ahmed Nabih Zaki Rashed

  8. Department of VLSI Microelectronics, Institute of Electronics and Communication Engineering, Saveetha School of Engineering, SIMATS, Chennai, 602105, Tamilnadu, India

    Ahmed Nabih Zaki Rashed

Authors
  1. Shaik Hasane Ahammad
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  2. Sandeep Dwarkanath
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  3. Rahul Joshi
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  4. B. T. P. Madhav
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  5. P. Poorna Priya
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  6. Osama S. Faragallah
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  7. Mahmoud M. A. Eid
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  8. Ahmed Nabih Zaki Rashed
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Authors contributed equally in this work.

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Correspondence to Ahmed Nabih Zaki Rashed.

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Ahammad, S.H., Dwarkanath, S., Joshi, R. et al. Social media reviews based hotel recommendation system using collaborative filtering and big data. Multimed Tools Appl 83, 29569–29582 (2024). https://doi.org/10.1007/s11042-023-16644-8

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  • DOI: https://doi.org/10.1007/s11042-023-16644-8

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