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Recommender Systems in E-Commerce

Lopamudra Mohanty, Laxmi Saraswat, Puneet Garg, Sonia Lamba

20222022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT)34 citationsDOI

Abstract

Recommendations as a social process play an important role when people rely on external knowledge to make decisions about the artifact of interest. A recommendation system is an intelligent program that generates a high-quality list of items that a user may be interested in. Today, there are a huge variety of different methods and algorithms for filtering data and providing recommendations. Recommendations can be divided into three main categories: Collaborative Sorting, Content-Based Recommendations and Integrated Recommendations. This paper compares and describes these methods and discusses their limitations by describing the problems plagued by recommendations.E-commerce platform makes easy to sell and buy products on a large customer base. Customers now search on Google instead of directly going certain e-commerce site. E-commerce website helps customers to narrow down their comprehensive ideas and be able to complete the product.

Topics & Concepts

Computer scienceRecommender systemArtifact (error)Variety (cybernetics)Process (computing)E-commerceCollaborative filteringQuality (philosophy)Product (mathematics)SortingWorld Wide WebArtificial intelligenceGeometryProgramming languageEpistemologyMathematicsPhilosophyOperating systemRecommender Systems and TechniquesImage Retrieval and Classification TechniquesCaching and Content Delivery
Recommender Systems in E-Commerce | Litcius