Artificial intelligence
The algorithm design manual
Web-based customer decision support systems
Communications of the ACM
Communications of the ACM - Robots: intelligence, versatility, adaptivity
Re-Wiring Business: Uniting Management and the Web
Re-Wiring Business: Uniting Management and the Web
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Mining customer product ratings for personalized marketing
Decision Support Systems - Special issue: Web data mining
Sentiment analysis: capturing favorability using natural language processing
Proceedings of the 2nd international conference on Knowledge capture
Fast Polyhedral Adaptive Conjoint Estimation
Marketing Science
Recommending as personalized teaching: towards credible needs-based ecommerce recommender systems
Designing personalized user experiences in eCommerce
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Communications of the ACM
Red Opal: product-feature scoring from reviews
Proceedings of the 8th ACM conference on Electronic commerce
Research Note: User Design of Customized Products
Marketing Science
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Proceedings of the 2012 Joint EDBT/ICDT Workshops
Identifying helpful online reviews: A product designer's perspective
Computer-Aided Design
| Hi-index | 0.00 |
Needs-based analysis lies at the intersection of product marketing and new product development. It is the study of why consumers purchase and what they do with those purchases. In a world of mass-customization and one-to-one marketing, anticipating the customer's needs is a key competitive advantage. In this paper, we consider a new approach to supplement traditional methods for assessing rapidly changing user needs. We model the knowledgebase of online customer reviews as a matrix of reviews relating customer needs to product attributes. In a hierarchical two-stage process, we first use association rules to cluster related attributes and needs into hyper-edges. In a second application of association rule mining, we search for hyper-rules relating hyperedges. The method is demonstrated on 10,500 customer reviews over two unrelated product domains, digital cameras and vacuum cleaners.