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21. A KNOWLEDGE BASED MATHEMATICAL MODEL FOR PERSONALIZED CLOTH RECOMMENDER SYSTEM by Akanbi C.O. and Oyetayo T. T. Volume 50 (March, 2019 Issue)
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A KNOWLEDGE BASED MATHEMATICAL MODEL FOR PERSONALIZED CLOTH RECOMMENDER SYSTEM 

Akanbi C.O. and Oyetayo T. T.

Department of Information and Communication Technology, Osun State University, 

Osogbo, Osun State Nigeria.


Abstract


Clothing is very valuable in human life. Manual method of selecting clothes for different occasions is very tedious and inefficient, so, people spend ample time thinking of what to wear. The decision on the clothes to wear could be based on an event, the state of mind, recommendation or instinct. One of the technologies to provide a solution to this problem is the Recommender/ Recommendation System. Recommendation Systems are used in solving many practical problems in different areas such as education, web search content, e-commerce, music and so on. In this paper, we adopted the knowledge - based recommendation approach that recommends items based on knowledge of how item characteristics meet users' needs and preferences. The system design framework was presented using a mathematical modelling approach. The wardrobe clothe dataset for five different users were categorized based on religious activities, social life, academics or office work and casual clothe.  Mathematical model was developed for Recommender system proposed and was implemented using Origin Lab 2018 software to generate the graphical analysis. The hierarchical semantic similarity based on conservative, moderate and literal metrics was applied on each wardrobe for different users based on conservative, moderate and literal. The result shows that recommender system selected 1 cloth for each of the five users in their wardrobe based on religious activities, recommends 2 to 4 clothes for social life, 4 to 7 for academics or office work and 9 to 18 for casual clothes. The system shows how mathematical modelling approach (AMPL) could be used to model   a  cloth  recommender system.


Keywords: Cloth, Knowledge base, Mathematical Modelling and Recommender System

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