A SURVEY ON CUSTOMER SEGMENTATION IN CLIENT STRUCTURED WEB DOMAIN USING MACHINE LEARNING TECHNIQUES

Authors

  • Adlin Selva Golda. V Research Scholar, Manonmaniam Sundaranar University, Tirunelveli,
  • Narayani. V Assistant Professor/Computer Science, St Xavier’s College, Tirunelveli

Keywords:

Segmentation, Web domain, Client structure, Machine learning, Performance

Abstract

Nowadays the direct communication between the users and resources are diminished which forces the online web domains to take the responsibility in order to maintain the entire business strategies.  The entire web domains are maintaining their customer’s information for the retaining purpose towards effective business development in the area of Education, Over the Top (OTT), Government services, and E-Commerce domains.  The prolonged improvements in the entire business strategies critically depend upon the classification of customer segmentation. Machine learning helps to extract customer analysis information from huge sets of data.  It is the procedure of data classification and segmentation of knowledge from customer data.  This research can be considered as an efficient data segmentation of different source of customer information web mining domains to extract the useful segments for the enhanced time and space complexities.  This paper presents a survey on customer segmentation in client structured web domain using machine learning techniques.

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Published

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How to Cite

Adlin Selva Golda. V, & Narayani. V. (2022). A SURVEY ON CUSTOMER SEGMENTATION IN CLIENT STRUCTURED WEB DOMAIN USING MACHINE LEARNING TECHNIQUES. EPRA International Journal of Multidisciplinary Research (IJMR), 8(3), 196–199. Retrieved from http://www.eprajournals.net/index.php/IJMR/article/view/201