Online Product Recommendation System Using Multi Scenario Demographic Hybrid (MDH) Approach
In: IFIP Advances in Information and Communication Technology ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS) ; https://hal.inria.fr/hal-03434788 ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS), Feb 2020, Chennai, India. pp.248-260, ⟨10.1007/978-3-030-63467-4_20⟩, 2020
Online
Konferenz
Zugriff:
Part 3: Data Science ; International audience ; The recommendation system plays very important role in the ecommerce domain to recommend the relevant products/services based on end user preference or interest. This helps end users to easily make the buying decision from a vast range of product and brands are available in the market. A lot of research is done in recommendation system, aim to provide the relevant product to the end user by referring end user past purchase history, transaction details etc. In our Multi scenario demographic hybrid (MDH) approach, important demographic influence factors like the user age group and located area are considered. The products are also ranked with associated age group category. The experimental results of the proposed recommendation system have proven that it is better than the existing systems in terms of prediction accuracy of relevant products.
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Online Product Recommendation System Using Multi Scenario Demographic Hybrid (MDH) Approach
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Autor/in / Beteiligte Person: | Karthik, R. ; Ganapathy, Sannasi ; Vellore Institute of Technology (VIT) ; Chandrabose, Aravindan ; Furbach, Ulrich ; Ghosh, Ashish ; Anand Kumar M. ; 12, TC |
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Zeitschrift: | IFIP Advances in Information and Communication Technology ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS) ; https://hal.inria.fr/hal-03434788 ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS), Feb 2020, Chennai, India. pp.248-260, ⟨10.1007/978-3-030-63467-4_20⟩, 2020 |
Veröffentlichung: | HAL CCSD ; Springer International Publishing, 2020 |
Medientyp: | Konferenz |
DOI: | 10.1007/978-3-030-63467-4_20 |
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