Book ChapterDOI
Developing an Improvised E-Menu Recommendation System for Customer
Rajendra Pawar,Shashikant Ghumbre,Ratnadeep R. Deshmukh +2 more
- pp 333-343
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TLDR
The proposed recommender system uses wireless technology and menu recommender to build improvised E-Menu Recommendation System for customer-centric service and can build e-reputation of restaurant and customer community in live.Citations
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Journal ArticleDOI
Factors Affecting Consumer Acceptance of E-Menu in The Klang Valley Restaurant Sector in Malaysia
TL;DR: In this article , the authors present factors affecting consumer acceptance of E-Menu in the Klang Valley Restaurant Sector in Malaysia, focusing on the following three categories: consumer acceptance, acceptance, and acceptance.
References
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Book
Data Mining: Concepts and Techniques
TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Journal ArticleDOI
Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty
TL;DR: A new procedure, based on expanded RFM model by including one additional parameter, joining WRFM-based method to K-means algorithm applied in DM with K-optimum according to Davies-Bouldin Index is proposed, which has been implemented for SAPCO Co. in Iran.
Posted Content
Customer Segments as Moving Targets: Integrating Customer Value Dynamism into Segment Instability Logic
TL;DR: In this article, the authors draw focus to segment instability in business-to-business markets by conceptually exploring its theoretical underpinnings and integrating related theory on customer value change to propose an agenda for future research.
Journal ArticleDOI
Customer segments as moving targets: Integrating customer value dynamism into segment instability logic
TL;DR: In this article, the authors draw focus to segment instability in business-to-business markets by conceptually exploring its theoretical underpinnings and integrating related theory on customer value change to propose an agenda for future research.
Journal ArticleDOI
A case study of applying data mining techniques in an outfitter's customer value analysis
TL;DR: This study concludes that bagged clustering algorithm outperforms the other two methods in the analysis of customer value for an outfitter in Taipei, Taiwan and suggests marketing strategies for each cluster based on the results generated by bagged clusters technique.