Ohsawa Y., Yada K. (Eds.) Data Mining for Design and Marketing

Chapman & Hall/CRC, 2009. — 311 p. — (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series). — ISBN: 1420070193, 9781420070194.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.Yukio Ohsawa
Sensing Values in Designing Products and Markets on Data Mining and Visualizations
David Bergner and Ozgur Eris
Reframing the Data-Mining Process
Lihua Zhao, Mark D. Uncles, and Gary Gregory
The Use of Online Market Analysis Systems to Achieve Competitive Advantage
Takanobu Nakahara and Hiroyuki Morita
Chapter Finding Hierarchical Patterns in Large POS Data Using Historical Trees
Kenta Fukata, Takashi Washio, Katsutoshi Yada, and Hiroshi Motoda
A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis
Asem Omari
Data Mining for Improved Web Site Design and Enhanced Marketing
Noriko Imafuji Yasui, Xavier Llorà, and David E. Goldberg
Discourse Analysis and Creativity Support for Concept Product Design
Kenichi Horie, Yoshiharu Maeno, and Yukio Ohsawa
Data Crystallization with Human Interactions Applied for Designing New Products
Brett Bojduj
Improving and Applying Chance Discovery for Design Analysis
Renate Fruchter, Shubashri Swaminathan, Naohiro Matsumura, and Yukio Ohsawa
Mining for Influence Leaders in Global Teamwork Projects
Wataru Sunayama and Katsutoshi Yada
Analysis Framework for Knowledge Discovery Related to Persuasion Process Conversation Logs
Wenxue Huang, Milorad Krneta, Limin Lin, and Jianhong Wu
Association Bundle-Based Market Basket Analysis
Radim Belohlavek and Vilem Vychodil
Formal Concept Analysis with Attribute Priorities
Lukáš Pichl, Manabu Suzuki, Masaki Murata, Daiji Kato, Izumi Murakami, and Akira Sasaki
Literature Categorization System for Automated Database Retrieval of Scientific Articles Based on Dedicated Taxonomy
Timothy Maciag, Dominik Ślęzak, Daryl H. Hepting, and Robert J. Hilderman
A Data-Mining Framework for Designing Personalized E-Commerce Support Tools
Bin Shi and Kuiyu Chang
An Adjacency Matrix Approach for Extracting User Sentiments
Yukio Ohsawa, Takuma Hosoda, and Takeshi Ui
Visualizing RFID Tag Data in a Library for Detecting Latent Interest of Users
Appendix A: KeyGraph and Pictorial KeyGraph
Appendix B: A Maximal Cliques Enumeration Algorithm for MBA Transaction Data