Apparel Recommendation System using Content-Based Filtering
Sagar Yeruva1, Addi Sathvika2, Damera Sruthi3, Duggasani Yaswanth Reddy4, Gogineni Gopi Krishna5
1Sagar Yeruva, Department of Computer Science and Engineering, (AIML and IoT), VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
2Addi Sathvika, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
3Damera Sruthi, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
4Duggasani Yaswanth Reddy, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
5Gogineni Gopi Krishna, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
Manuscript received on 25 October 2022 | Revised Manuscript received on 31 October 2022 | Manuscript Accepted on 15 November 2022 | Manuscript published on 30 November 2022 | PP: 46-51 | Volume-11 Issue-4, November 2022 | Retrieval Number: 100.1/ijrte.D73311111422 | DOI: 10.35940/ijrte.D7331.1111422
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Abstract: Nowadays, people are constantly moving towards various fashion products as a result the e-commerce market for garments is growing rapidly. Online stores must update their features according to user requirements and preferences. However, there are too many options for users to select from these online stores which may leave them in a dilemma to identify the correct outfit, save the user time, and increase sales, efficient recommendation systems are becoming a necessity for online retailers. In this paper, we proposed an Apparel Recommendation System that generates recommendations for users based on their input. We used a real-world data set taken from the online market giant Amazon using Amazon’s Product Advertising API. We aim to use keywords like brand, color, size, etc., to recommend. Data exploration to get detailed information about our dataset, Data Cleaning(pre-processing) to remove invalid sections, Model selection (We have compared different feature extraction techniques like bag of words, TF-IDF, and word2vec model) to find out efficient techniques and Deployment of the model that could facilitate recommendation system to simplify the task of apparel recommendation system. The accuracy of the model is identified using the response time and content matching.
Keywords: Apparel, Recommendation, TF-IDF, Bag-of-Words, Content-Based-Filtering
Scope of the Article: e-commerce