Apparel Recommendation System Using Descriptive Textual Similarity of Products
AUTHORS
Rahul Shrivastava,Department of Computer Science and Engineering National Institute of Technology, Raipur, India
ABSTRACT
E-commerce applications like Amazon adapting various techniques to recommend relevant product to the customer. The process of recommendation may evolve around two basic attribute one is textual description of product and other is visual description of product such as image. The main objective of this research is to develop a product recommendation using Bag of Words and Term Frequency-Inverse Document Frequency technique of text-based product similarity.In this research data acquired through Amazon product advertising API after Data cleaning and text preprocessing the content based product recommendation have been performed using text description of products. Algorithms for text-based product recommendation have been presented which describes the method to create Bag-of –Words vectorization and TF-IDF based vectorization and then Euclidean distance used to measure the similarity of product through n-Dimensional Vector.
KEYWORDS
Bag of Words, TF-IDF, Euclidean Distance.
REFERENCES
[1] L. I. Hui, S. H. I. Jun, S. Zhang, and H. Yun, “Implementation of Intelligent Recommendation System for Learning Resources,” no. Iccse, (2017).
[2] X. Shen, B. Yi, Z. Zhang, J. Shu, and H. Liu, “Automatic Recommendation Technology for Learning Resources with Convolutional Neural Network,” 2016 Int. Symp. Educ. Technol., pp. 30–34,( 2016).(CrossRef)(Google Scholar)
[3] T. Badriyah, E. T. Wijayanto, I. Syarif, and P. Kristalina, “A Hybrid Recommendation System for E-Commerce based on Product Description and User Profile,” no. Intech, pp. 95–100, (2017).
[4] A. K. Uysal and Y. L. Murphey, “Sentiment Classification: Feature Selection Based Approaches Versus Deep Learning,” 2017 IEEE Int. Conf. Comput. Inf. Technol., pp. 23–30, (2017).(CrossRef)(Google Scholar)
[5] Chen Jian, Yin Jian, and Huang Jin, “Automatic Content-Based Recommendation in e-Commerce,” 2005 IEEE Int. Conf. e-Technology, e-Commerce e-Service, pp. 748–753.(CrossRef)(Google Scholar)
[6] P. Bafna, D. Pramod, and A. Vaidya, “Document clustering: TF-IDF approach,” Int. Conf. Electr. Electron. Optim. Tech. ICEEOT 2016, pp. 61–66, (2016).(CrossRef)(Google Scholar)
[7] D. Kiela and L. Bottou, “Learning Image Embeddings using Convolutional Neural Networks for Improved Multi-Modal Semantics,” Proc. 2014 Conf. Empir. Methods Nat. Lang. Process., pp. 36–45, (2014).
[8] Wang, S. , et al. "An automated CNN recommendation system for image classification tasks." 2017 IEEE International Conference on Multimedia and Expo (ICME) IEEE Computer Society, (2017).(CrossRef)(Google Scholar)
[9] Wu, Ho Chung , et al. "Interpreting TF-IDF term weights as making relevance decisions." ACM TRANSACTIONS ON INFORMATION SYSTEMS 26.3(2008):1-37. (CrossRef)(Google Scholar)
[10] Y. Zhang, R. Jin, Z.H. Zhau “Understanding bag-of-words model : a statistical framework,” International Journal of Machine Learning and Cybernetics Vol.1-4, pp 43–52, (2010).(CrossRef)(Google Scholar)
[11] G. Domeniconi, “A Study on Term Weighting for Text Categorization : A Novel Supervised Variant of tf . idf A Study on Term Weighting for Text Categorization : a Novel Supervised,” no. July (2015).
[12] Chang CY, Lee SJ, Lai CC (2017) Sighted word2vec based on the distance of words. In: 2017 international conference on machine learning and cybernetics (ICMLC). IEEE, vol 2, pp 563–568
[13] P. Sukumar, L. Robert, and S. Yuvaraj, “Review on modern Data Preprocessing techniques in Web usage mining (WUM),” 2016 Int. Conf. Comput. Syst. Inf. Technol. Sustain. Solut. CSITSS 2016, pp. 64–69, (2016).(CrossRef)(Google Scholar)
[14] L. Yan, “Personalized Recommendation Method for E-Commerce Platform Based on Data Mining Technology,” 2017 Int. Conf. Smart Grid Electr. Autom., pp. 514–517, (2017).(CrossRef)(Google Scholar)
[15] W. W. Song, C. Lin, A. Forsman, A. Avdic, and L. Åkerblom, “An Euclidean similarity measurement approach for hotel rating data analysis,” 2017 2nd IEEE Int. Conf. Cloud Comput. Big Data Anal. ICCCBDA 2017, pp. 293–298, (2017).(CrossRef)(Google Scholar)
[16] N. Zhang, A. Guo, and T. Sun, “Research on Data Cleaning Method Based on SNM Algorithm,” IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), pp. 2639–2643, (2017).
[17] Chekuri Srikanth Varma, “Applied AI Course - It is a great platform for Machine Learning online courses,” 2017. [Online]. Available: https://www.appliedaicourse.com/. [Accessed: 17-Nov-2017].
[18] S. K. Dwivedi and B. Rawat, “A review paper on data preprocessing: A critical phase in web usage mining process,” 2015 Int. Conf. Green Comput. Internet Things, pp. 506–510, (2015).(CrossRef)(Google Scholar)
[19] A. Mishra and S. Vishwakarma, “Analysis of TF-IDF Model and its Variant for Document Retrieval,” Proc. - 2015 Int. Conf. Comput. Intell. Commun. Networks, CICN 2015, pp. 772–776, (2016).(CrossRef)(Google Scholar)
[20] X. Rong, “word2vec Parameter Learning Explained,” ArXiv, 1411, online, pp. 1–21, June (2014).