Please use this identifier to cite or link to this item: https://idr.l3.nitk.ac.in/jspui/handle/123456789/14922
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dc.contributor.authorJain M.
dc.contributor.authorSingh S.
dc.contributor.authorChandrasekaran K.
dc.contributor.authorRathnamma M.V.
dc.contributor.authorVenkata Ramana V.
dc.date.accessioned2021-05-05T10:16:00Z-
dc.date.available2021-05-05T10:16:00Z-
dc.date.issued2020
dc.identifier.citationProceedings of 3rd International Conference on Emerging Technologies in Computer Engineering: Machine Learning and Internet of Things, ICETCE 2020 , Vol. , , p. 12 - 17en_US
dc.identifier.urihttps://doi.org/10.1109/ICETCE48199.2020.9091777
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/14922-
dc.description.abstractIn the present-day scenario, several clothing recommender systems have been developed for the online e-commerce industry. However, when it comes to recommending clothes that a person already possesses, i.e, from their personal wardrobe, there are very few systems that have been proposed to perform the task. In this paper, we tackle the latter issue, and perform experimental analysis of the various Machine Learning techniques that can be used for carrying out the task. Since the recommendations must be made from a user's personal wardrobe, the recommender system doesn't follow a traditional approach. This is explained in detail in the following sections. Further, the paper contains a complete description of the results obtained from the experiments conducted, and the best approach is specified, with appropriate justification for the same. © 2020 IEEE.en_US
dc.titleMachine Learning Models with Optimization for Clothing Recommendation from Personal Wardrobeen_US
dc.typeConference Paperen_US
Appears in Collections:2. Conference Papers

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