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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Movie recommendation system using Collaborative filtering and Content filtering |
| Authors Name: | BAIBHAV KUMAR , RAJAT TIWARI , SAURABH BHALLA , Dr. P.A. JADHAV |
| Unique Id: | IJSDR2009030 |
| Published In: | Volume 5 Issue 9, September-2020 |
| Abstract: | A recommendation system uses various algorithms for giving the most preferable and relevant items to users. The system checks the past behavior of a person and gives similar results that might be likely preferable to users. Suppose a new user visits an e-commerce site, it doesn’t have any past history of the user, so in this scenario how will not show any recommendation to a new user? In this case, the site can recommend the best-selling product, I e. the product which is high in demand. Another conceivable arrangement could be to prescribe the items which would carry the greatest benefit to the business. Three main approaches are used for our recommender systems. One is Content-based i.e they offer generalized recommendations to each and every user, based on movie popularity and/or genre. The System recommends the same movies to users with similar content features. Since each user is different, this approach is considered to be too simple. The basic idea behind this system is that movies that are more popular and critically acclaimed will have a higher probability of being liked by the average audience. Second is Knowledge-based filtering, where we try to profile the user’s interests using information collected, and recommend items based on that profile. The other is collaborative filtering, where we try to group similar users together and use information about the group to make recommendations to the user. |
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| Cite Article: | "Movie recommendation system using Collaborative filtering and Content filtering", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 9, page no.179 - 182, September-2020, Available :http://www.ijsdr.org/papers/IJSDR2009030.pdf |
| Downloads: | 000337209 |
| Publication Details: | Published Paper ID: IJSDR2009030 Registration ID:192441 Published In: Volume 5 Issue 9, September-2020 DOI (Digital Object Identifier): Page No: 179 - 182 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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