Data Mining for Design and Marketing
Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

Data Mining for Design and Marketing shows how to design and integrate data mining tools into human thinking processes in order to make better business decisions, especially in designing and marketing products and systems.

The expert contributors discuss how data mining can identify valuable consumer patterns, which aid marketers and designers in detecting consumers? needs. They also explore visualization tools based on the computational methods of data mining. Discourse analysis, chance discovery, knowledge discovery, formal concept analysis, and an adjacency matrix are just some of the novel approaches covered. The book explains how these methods can be applied to website design, the retrieval of scientific articles from a database, personalized e-commerce support tools, and more.

Through the techniques of data mining, this book demonstrates how to effectively design business processes and develop competitive products and services. By embracing data mining tools, businesses can better understand the behavior and needs of their customers.

Sensing Values in Designing Products and Markets on Data Mining and Visualizations. Reframing the Data Mining Process. The Use of Online Market Analysis Systems to Achieve Competitive Advantage. Finding Hierarchical Patterns in Large POS Data Using Historical Trees. A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis. Data Mining for Improved Website Design and Enhanced Marketing. Discourse Analysis and Creativity Support for Concept Product Design. Data Crystallization with Human Interactions Applied for Designing New Products. Improving and Applying Chance Discovery for Design Analysis. Mining for Influence Leaders in Global Teamwork Projects. Analysis Framework for Knowledge Discovery Related to Persuasion Process Conversation Logs. Association Bundle-Based Market Basket Analysis. Formal Concept Analysis with Attribute Priorities. Literature Categorization System for Automated Database Retrieval of Scientific Articles Based on Dedicated Taxonomy. A Data Mining Framework for Designing Personalized E-Commerce Support Tools. An Adjacency Matrix Approach for Extracting User Sentiments from Sentences. Visualizing RFID Tag Data in a Library for Detecting Latent Interest of Users. Appendices. Index.