CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Opinion Observer: Recommendation System on E-Commerce Website

by Mohammad Daoud, S.k Naqvi, Asad Ahmad
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 105 - Number 14
Year of Publication: 2014
Authors: Mohammad Daoud, S.k Naqvi, Asad Ahmad
10.5120/18449-9842

Mohammad Daoud, S.k Naqvi, Asad Ahmad . Opinion Observer: Recommendation System on E-Commerce Website. International Journal of Computer Applications. 105, 14 ( November 2014), 37-42. DOI=10.5120/18449-9842

@article{ 10.5120/18449-9842,
author = { Mohammad Daoud, S.k Naqvi, Asad Ahmad },
title = { Opinion Observer: Recommendation System on E-Commerce Website },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 105 },
number = { 14 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 37-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume105/number14/18449-9842/ },
doi = { 10.5120/18449-9842 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:37:44.522840+05:30
%A Mohammad Daoud
%A S.k Naqvi
%A Asad Ahmad
%T Opinion Observer: Recommendation System on E-Commerce Website
%J International Journal of Computer Applications
%@ 0975-8887
%V 105
%N 14
%P 37-42
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To overcome the product overload of online shoppers, a variety of recommendation methods have been developed. Recommender systems are being utilized by an ever-increasing number of E-commerce sites to help consumers discover products to buy. The most of existing system gives the recommendation based on best selling product, on demographics of the consumer, or on an analysis of the past buying behavior of the consumer. Our purposed system based on the consumer reviews and advanced multi-criteria search engine. In this paper, we used a text mining approach to mine product features, opinions and their semantic similarity from Web opinion sources. The consumer can clearly see the strengths and Weaknesses of each product in the minds of existing consumer's opinion. The system assists on-line shoppers or goal oriented shopper by suggesting the most effective navigation products for their specified criteria and preferences.

References
  1. Babin, Barry J. , William R. Darden, and Mitch Griffin. "Work and/or fun: measuring hedonic and utilitarian shopping value. " Journal of consumer research (1994): 644-656.
  2. Hoffman, Donna L. , and Thomas P. Novak. "Marketing in hypermedia computer-mediated environments: conceptual foundations. " The Journal of Marketing (1996): 50-68.
  3. Hoffman, Donna L. , Thomas P. Novak, and Ann Schlosser. "Consumer control in online environments. " Elab. vanderbilt. edu (2000).
  4. Apeh, Edward Tersoo, Bogdan Gabrys, and Amanda Schierz. "Customer profile classification using transactional data. " Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on. IEEE, 2011.
  5. Mobasher, Bamshad. "Data mining for web personalization. " The adaptive web. Springer Berlin Heidelberg, 2007. 90-135.
  6. Jakob, Niklas. "Extracting Opinion Targets from User-Generated Discourse with an Application to Recommendation Systems. " (2011).
  7. Yousefi, Ayoub, and Jie Tang. "E-commerce: Consumer Online Shopping in Canada. " Contemporary Research on E-business Technology and Strategy. Springer Berlin Heidelberg, 2012. 1-14.
  8. Gretzel, Ulrike, and Daniel R. Fesenmaier. "Persuasion in recommender systems. " International Journal of Electronic Commerce 11. 2 (2006): 81-100.
  9. Chen, Yen-Liang, et al. "Market basket analysis in a multiple store environment. " Decision support systems 40. 2 (2005): 339-354.
  10. Lin, Qi-Yuan, et al. "Mining inter-organizational retailing knowledge for an alliance formed by competitive firms. " Information & management 40. 5 (2003): 431-442.
  11. Tang, Kwei, Yen-Liang Chen, and Hsiao-Wei Hu. "Context-based market basket analysis in a multiple-store environment. " Decision Support Systems45. 1 (2008): 150-163.
  12. Chen, Yen-Liang, et al. "Discovering recency, frequency, and monetary (RFM) sequential patterns from customers' purchasing data. " Electronic Commerce Research and Applications 8. 5 (2009): 241-251.
  13. Daoud, Mohammad, S. K. Naqvi, and Alok Nikhil Jha. "Semantic Analysis of Context Aware Recommendation techniques. "
Index Terms

Computer Science
Information Sciences

Keywords

Recommender Systems e-commerce feature opinion

Powered by PhDFocusTM