Recommender System – An Overview

Madhurima Banerjee, Sanjana Roy, Snigdha Roy, Riddhima Shome, Asmita Majumder

Abstract


The purpose of this paper is give an overview of the concept of recommendation systems, to highlight the existence of recommender systems in various aspects of human life and how recommendation is becoming an integral part of human life. The chanllenges that the recommendation systems are facing


Keywords


Recommendation, Content based, Collaborative filtering, Knowledge based, Challenges

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References


K. Luk, 3rd February,2019, “Introduction to TWO approaches of Content-based Recommendation System”, viewed on 25th November, 2019 from https://towardsdatascience.com/introduction-to-two-approaches-of-content-based-recommendation-system-fc797460c18c.

B. Stark, et al., 2019., “A Literature Review on Medicine Recommender Systems”, in International Journal of Advanced Computer Science and Applications, Vol 10 Issue 8, pp 6 – 13.

Doulaverakis, C., Nikolaidis, G., Kleontas, A., and Kompatsiaris, I. 2012. GalenOWL: Ontology-based drug recommendations discovery, in Journal of Biomedical Semantics 3, 14

Sun, L., Liu, C., Guo, C., Xiong, H., and Xie, Y. 2016. Data-driven Automatic Treatment Regimen Development and Recommendation. KDD '16 Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1865–1874

Royce, Walker. Software Project Management: A Unified Framework. Upper Saddle River: Addison-Wesley, 1998.

D.M. Pencock, et al., , 2000, “Collaborative Filtering by Personality Diagnosis: A Hybrid Memory- and Model-Based Approach”, in UNCERTAINTY IN ARTIFICIAL INTELLIGENCE PROCEEDINGS, pp 473-479

Cowles, A. (1933). Can stock market forecasters forecast? Econometrica, 1, 309-324.

Cowles, A. (1944). Stock market forecasting. Econometrica, 12, 206-214.

Nair, B., et al., 2015, “A Stock Trading Recommender System Based on Temporal Association Rule Mining”, in SAGE.

James Bennett and Stan Lanning, ‘The netflix prize’, in Proceedings of KDD cup and workshop, volume 2007, p. 35, (2007).

Zibriczky, D., n.d., “Recommender Systems meet Finance: A literature review”, pp 3-10




DOI: https://doi.org/10.26483/ijarcs.v10i6.6482

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