A Novel Video Game Recommender System using Content Based Filtering -Vidya
Krishna Chythanya. N1, Krishna Bhargavi. Y2, A. B. Rohan3
1Krishna Chythanya N*, Asst. Prof., CSE, GRIET-Hyderabad-India.
2Krishna Bhargavi Y, Asst. Prof. CSE, GRIET-Hyderabad-India.
3A. B. Rohan, IV Year, CSE, GRIET-Hyderabad-India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 536-541 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7251118419/2019©BEIESP | DOI: 10.35940/ijrte.D7251.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This work is aimed at building an application that takes input from the user in the form of a few initial games and then proceeds to give recommendations to the user which they will tend to like. Recommendation systems position themselves to fill the gap caused by the presence of voluminous content and the lack of time .This will be done by building a substantial data backend, from which insight similarity will be generated upon processing. Natural Language Processing will be used to gauge the genre, plot and gameplay similarities, Key traits about the games have been extracted and used to fuel the recommendation process. The result was presented to the user in the form of an interactive web application, where they can pick-and-choose their preferred games among the system provided suggestions. The application performance is satisfactory based on Normalized Mutual Information (NMI) score we achieved. The work is applicable to recommend interesting games for the user.
Keywords: Game, Recommendation, Content Dased Filtering, NMI
Scope of the Article: IoT Applied for Digital Contents.