Recommendation System by Considering Real Time Information

Authors

  • Chandrakant D. Kokane  Nutan Maharashtra institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India
  • Arjun Haghwane  Nutan Maharashtra institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India
  • Vinay Ippili  Nutan Maharashtra institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India
  • Mithilesh Jogale  Nutan Maharashtra institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India
  • Vilas V. Deotare  

Keywords:

Collaborative Filtering ,Machine Learning, Reviews, Management

Abstract

The Recommendation system is the unavoidable thing for whatever we buy or go to the new place. Restaurants also need recommendation systems in terms of attracting more customers in the management5 side and tasting favourite, famous food in the restaurant in customers side. With addition to that we build the review based model for recommending restaurants to the customers with the help of collaborative filtering6 which is a Machine Learning7 Algorithm .The output of the model may be recommending most popular restaurants and most popular food items served by the appropriate restaurant. The model is improved with the review8 system as the review increases the recommended results are prioritized.

References

  1. HengSong Tan ,HongWu Ye , “A Collaborative filtering Recommendation Algorithm based on Item Classification ” , IEEE Pacific Asia Conference on Circuits , Communication and System , 2009 , pp 694-697.
  2. Yagnesh Patel, Vishal Patel, “A Survey on Various Techniques of Recommendation System in Web Mining”, International Journal of Engineering Development and Research Volume 3, Issue 4, 2015, pp 696- 700
  3. Rui Jiang, “A Customized Real Time Restaurant Recommendation System”, A Thesis in Computer Science and Engineering ”10(2) special 2015.
  4. Anusha Jayasimhan,parikshith Rai, Yash Parekh, Ojas Patwardhan, “Restaurant Recommendation System” International Journal of Computer Applications, Vol.-6, 2017.
  5. Yifan gao, Wenzhe Yu, Pingfu Chao, Rong Zhang, “A Restuarant Recommendation System by Analyzing Ratings and Aspects in Reviews”, 20th International Conference, DASFAA 2015, Hanoi, vietnam, 2015.
  6. Kokane, Chandrakant D., and Sachin D. Babar. "Supervised word sense disambiguation with recurrent neural network model." Int. J. Eng. Adv. Technol.(IJEAT) 9.2 (2019).
  7. Kokane, Chandrakant D., Sachin D. Babar, and Parikshit N. Mahalle. "Word Sense Disambiguation for Large Documents Using Neural Network Model." 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2021.
  8. Kokane, Chandrakant D., Sachin D. Babar, and Parikshit N. Mahalle. "An adaptive algorithm for lexical ambiguity in word sense disambiguation." Proceeding of First Doctoral Symposium on Natural Computing Research: DSNCR 2020. Springer Singapore, 2021.
  9. Kokane, Chandrakant, et al. "Word Sense Disambiguation: A Supervised Semantic Similarity based Complex Network Approach." International Journal of Intelligent Systems and Applications in Engineering 10.1s (2022): 90-94.
  10. Kokane, Chandrakant D., et al. "Machine Learning Approach for Intelligent Transport System in IOV-Based Vehicular Network Traffic for Smart Cities." International Journal of Intelligent Systems and Applications in Engineering 11.11s (2023): 06-16.
  11. Kokane, Chandrakant D., et al. "Word Sense Disambiguation: Adaptive Word Embedding with Adaptive-Lexical Resource." International Conference on Data Analytics and Insights. Singapore: Springer Nature Singapore, 2023.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-10-30

Issue

Volume 9, Issue 10, September-October-2023

Section

Research Articles

License

Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Chandrakant D. Kokane, Arjun Haghwane, Vinay Ippili, Mithilesh Jogale, Vilas V. Deotare, " Recommendation System by Considering Real Time Information" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 10, pp.223-227, September-October-2023.