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Title: Automation and Personalization of E-Commerce Field
Authors: Wickramasinghe, S.
Asurasinghe, H.
Subhani, D.
Gunathilaka, T.
Samarasinghe, R.
Keywords: K-Means Clustering
Naïve Bayes Theorem
Data Extraction
User Profiling
Natural Language Processing
Social Media Data Analysis
Issue Date: 2016
Publisher: SLIIT
Abstract: This research article will be focusing on how e-commerce websites can be enhanced by providing automated advertisements extraction, advertisements categorization and target right customers for the products and services by implementing efficient and accurate personalization. Furthermore the article will be discussing the ways of using algorithms such as Clustering algorithms and Naive Bayes algorithms in its best practice as a tool to achieve this task. The process flow used in the design shows clearly the methodology used in advertisement extraction, categorization, and personalization and publishing them on user’s computer screen. The information such as user’s navigation data and social media data are brought together and analyze them to make e-commerce process more convenient for users and administrators alike.
Appears in Collections:SLIIT Student Research -2016

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