Abstract
Recommendation systems are playing a vital role in our day-to-day life whether it is going to explore new place, shopping avenues, tourist places, event planning, etc. It is the need of the hour to get a good recommendation system that works for everyone with minimum bias. In this work, we focus on the point of interest recommended for restaurants based on given criteria. The study reveals various constraints such as geographical, temporal, and user preference which create a significant impact on the search result. Authors categorized their study based on these factors and proposed a hybrid solution that can overcome the challenges observed during the exploration of the existing work done in this domain. The proposed model takes care of all the impact factors in parallel to harness the benefit of each one. The cold start problem from the users’ and the business perspective was also addressed.
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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Sharma, M., Patil, S., Shetty, S., Thakur, Y. (2024). PoI Recommendation System: A Blended Approach. In: Iglesias, A., Shin, J., Patel, B., Joshi, A. (eds) Proceedings of World Conference on Information Systems for Business Management. ISBM 2023. Lecture Notes in Networks and Systems, vol 833. Springer, Singapore. https://doi.org/10.1007/978-981-99-8346-9_15
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DOI: https://doi.org/10.1007/978-981-99-8346-9_15
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