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Adaptive Feedback System for Websites based on User Classification

by Garric Mathias, Naina Bharadwaj, Falguni Bharadwaj
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 149 - Number 5
Year of Publication: 2016
Authors: Garric Mathias, Naina Bharadwaj, Falguni Bharadwaj
10.5120/ijca2016911401

Garric Mathias, Naina Bharadwaj, Falguni Bharadwaj . Adaptive Feedback System for Websites based on User Classification. International Journal of Computer Applications. 149, 5 ( Sep 2016), 28-34. DOI=10.5120/ijca2016911401

@article{ 10.5120/ijca2016911401,
author = { Garric Mathias, Naina Bharadwaj, Falguni Bharadwaj },
title = { Adaptive Feedback System for Websites based on User Classification },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2016 },
volume = { 149 },
number = { 5 },
month = { Sep },
year = { 2016 },
issn = { 0975-8887 },
pages = { 28-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume149/number5/25994-2016911401/ },
doi = { 10.5120/ijca2016911401 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:53:55.571571+05:30
%A Garric Mathias
%A Naina Bharadwaj
%A Falguni Bharadwaj
%T Adaptive Feedback System for Websites based on User Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 149
%N 5
%P 28-34
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a feedback system for websites has been proposed which adapts according to user’s familiarity of the website thus helping in understanding areas of improvement from those users who use these features most, using the example of an e-commerce website. The feedback of users is analyzed by classifying them into discrete levels from 1 to 5 based on their interaction with the website and the Pareto Principle is used to reason this classification. Every questionnaire is based on the complexity of the level in which the user has been classified. An algorithm has been proposed for user classification based on factors such as how many services the user has availed and how active he is on the website. This system is adaptive in nature as the feedback form adapts itself to the user levels thus extracting relevant information.

References
  1. Gabriella Pasi, “Implicit feedback through user-system interactions for defining user models in personalized search”, 6th International Conference on Intelligent Human Computer Interaction, IHCI 2014
  2. Yi Zhu Li He, Xiaojun Wang, “User Interest Modeling and Self-Adaptive Update Using Relevance Feedback Technology”, International Workshop on Information and Electronics Engineering, 2012
  3. Farid Aulia Tanjung, Wawan Dhewanto, “Formulation of E-Commerce Website Development Plan Using Multidimensional Approach for Web Evaluation”, The 5th Indonesia International Conference on Innovation, Entrepreneurship, and Small Business (IICIES), 2013
  4. Gerson Tontini, “Identifying opportunities for improvement in online shopping sites”, Journal of Retailing and Consumer Services, Volume 31, July 2016
  5. Qing Li, “E-commerce of Eco Bags on Basis of Pareto Improvement”, Chapter “Innovation in the High-Tech Economy”, Part of the series “Contributions to Economics”, November 2013
  6. Ronen Feldman, “Techniques and applications for sentiment analysis”, Communications of the ACM, Volume 56 Issue 4, April 2013
  7. T Prasad, V Dilip Kumar, “A New Approach for Information Collection from Web With Ontology”, International Journal of Applied Engineering Research, Volume 11 Number 9, 2016
  8. Madhuka Udantha, Surangika Ranathunga, “An Episode-based Approach to Identify Website User Access Patterns”,  International Conference on Pattern Recognition Applications and Methods, January 2016
  9. Dora Dzvonyar, Stephan Krusche, “Context-Aware User Feedback in Continuous Software Evolution”, Proceedings of the 1st International Workshop on Continuous Software Evolution and Delivery. IEEE/ACM, 2016
Index Terms

Computer Science
Information Sciences

Keywords

User Feedback Adaptive feedback Website Improvement Pareto Principle

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