Context enabled Multi-CBR based Recommendation Engine for E-commerce

Authors:
F'rashant Kumar;Srividya Gopalan;V Sridhar
Affiliations:
Applied Research Group, Satyam Computer Services Ltd.;Applied Research Group, Satyam Computer Services Ltd.;Applied Research Group, Satyam Computer Services Ltd.
Venue:
ICEBE '05 Proceedings of the IEEE International Conference on e-Business Engineering
Year:
2005

Citing 0
Cited 6

Context-information support for B2B collaboration

International Journal of Web Engineering and Technology
A rule-based CBR approach for expert finding and problem diagnosis

Expert Systems with Applications: An International Journal
Hybrid model for learner modelling and feedback prioritisation in exploratory learning

International Journal of Hybrid Intelligent Systems - CIMA-08
Context awareness by case-based reasoning in a music recommendation system

UCS'07 Proceedings of the 4th international conference on Ubiquitous computing systems
Music for my mood: a music recommendation system based on context reasoning

EuroSSC'06 Proceedings of the First European conference on Smart Sensing and Context
User behaviour-driven group formation through case-based reasoning and clustering

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Electronic commerce is steadily becoming more important in changing the way people buyhell products and services. Case-Based Reasoning (CBR) has been used in various E-Commerce applications for product recommendations. The appropriateness of the use of CBR in E-commerce applications is enhanced by introducing context-sensitive information related to E-commerce as cases in CBR. Usage of context leads to providing the right level of information to users in assisting them to take right decisions quickly. In this paper, we have proposed a Context enabled Multi- CBR approach comprising of two CBRs (User context CBR and Product context CBR) to aid the Recommendation engine (RE) in retrieving appropriate information for E-commerce applications. The RE further derives personalized negotiation and presentation strategies based on contextual information and ontology.