Mining the web data for classifying and predicting users' requests

Title

Mining the web data for classifying and predicting users' requests

Creator

Girish S.; Ramamurthy B.; Senthilnathan T.

Description

Consumers are the most important asset of any organization. The commercial activity of an organization booms with the presence of a loyal customer who is visibly content with the product and services being offered. In a dynamic market, understanding variations in client?s behavior can help executives establish operative promotional campaigns. A good number of new consumers are frequently picked up by traders during promotions. Though, several of these engrossed consumers are one-time deal seekers, the promotions undeniably leave a positive impact on sales. It is crucial for traders to identify who can be converted to loyal consumer and then have them patronize products and services to reduce the promotion cost and increase the return on investments. This study integrates a classifier that allows prediction of the type of purchase that a customer would make, as well as the number of visits that he/she would make during a year. The proposed model also creates outlines of users and brands or items used by them. These outlines may not be useful only for this particular prediction task, but could also be used for other important tasks in e-commerce, such as client segmentation, product recommendation and client base growth for brands. Copyright 2018 Institute of Advanced Engineering and Science. All rights reserved.

Source

International Journal of Electrical and Computer Engineering, Vol-8, No. 4, pp. 2390-2398.

Date

2018-01-01

Publisher

Institute of Advanced Engineering and Science

Subject

Classification; Customer; E-commerce; Prediction; Product Recommendation; Segmentation; Trend

Coverage

Girish S., Department of Computer Science, Christ University, Hosur Road, Bengaluru, Karnataka, India; Ramamurthy B., Department of Computer Science, Christ University, Hosur Road, Bengaluru, Karnataka, India; Senthilnathan T., Department of Computer Science, Christ University, Hosur Road, Bengaluru, Karnataka, India

Rights

All Open Access; Green Open Access; Hybrid Gold Open Access

Relation

ISSN: 20888708

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.11591/ijece.v8i4.pp2390-2398

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049571427&doi=10.11591%2fijece.v8i4.pp2390-2398&partnerID=40&md5=1a91b08884f0e6b1ef3f2be356ef3aab