DC Field | Value | Language |
---|---|---|
dc.contributor.author | Divyesh Gohel, Dr. Pratik Vanjara | - |
dc.date.accessioned | 2024-11-22T05:19:10Z | - |
dc.date.available | 2024-11-22T05:19:10Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://10.9.150.37:8080/dspace//handle/atmiyauni/1900 | - |
dc.description.abstract | There are several benefits of e-commerce websites that include cost effectiveness, convenience, flexibility, fast delivery, increase in income, etc. With these benefits, there is crucial role of e-commerce websites in business and users. However, e-commerce websites produce an overload of data, hence, Recommender Systems (RSs) provides a solution for the data overload problem. The present study, reviews different types of RSs and its pros and cons. Then, it does comparative study of different types of RSs. After the review, it’s concluded that collaborating filtering technique used more than all other ones in e-commerce websites. There are problems with almost all techniques including the collaborative filtering technique too. However there is a novel model proposed that fixes the collaborative filtering technique of ‘cold start’ at its best. | en_US |
dc.language.iso | en | en_US |
dc.subject | Recommender system | en_US |
dc.subject | Data collection | en_US |
dc.subject | Content-based | en_US |
dc.subject | collaborative | en_US |
dc.subject | and Hybrid filtration systems | en_US |
dc.title | Recommender System: Techniques, Comparison & Solutions | en_US |
dc.type | Article | en_US |
Appears in Collections: | 01. Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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305) 22079_Pratik Anilkumar Vanjara.pdf | 1.93 MB | Adobe PDF | View/Open |
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