Data mining for design and marketing / edited by Yukio Ohsawa, Katsutoshi Yada.

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Call Number
QA76.9.D343 D3828 2009
Status
Available

Summary

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.

Contents

  • Chapter 1 Sensing Values in Designing Products and Markets on Data Mining and Visualizations p. 1 Yukio Ohsawa
  • Chapter 2 Reframing the Data-Mining Process p. 19 David Bergner and Ozgur Eris
  • Chapter 3 The Use of Online Market Analysis Systems to Achieve Competitive Advantage p. 35 Lihua Zhao and Mark D. Uncles and Gary Gregory
  • Chapter 4 Finding Hierarchical Patterns in Large POS Data Using Historical Trees p. 57 Takanobu Nakahara and Hiroyuki Morita
  • Chapter 5 A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis p. 81 Kenta Fukata and Takashi Washio and Katsutoshi Yada and Hiroshi Motoda
  • Chapter 6 Data Mining for Improved Web Site Design and Enhanced Marketing p. 95 Asem Omari
  • Chapter 7 Discourse Analysis and Creativity Support for Concept Product Design p. 107 Noriko Imafuji Yasui and Xavier Llorà and David E. Goldberg
  • Chapter 8 Data Crystallization with Human Interactions Applied for Designing New Products p. 119 Kenichi Horie and Yoshiharu Maeno and Yukio Ohsawa
  • Chapter 9 Improving and Applying Chance Discovery for Design Analysis p. 137 Brett Bojduj
  • Chapter 10 Mining for Influence Leaders in Global Teamwork Projects p. 149 Renate Fruchter and Shubashri Swaminathan and Naohiro Matsumura and Yukio Ohsawa
  • Chapter 11 Analysis Framework for Knowledge Discovery Related to Persuasion Process Conversation Logs p. 171 Wataru Sunayama and Katsutoshi Yada
  • Chapter 12 Association Bundle-Based Market Basket Analysis p. 187 Wenxue Huang and Milorad Krneta and Limin Lin and Jianhong Wu
  • Chapter 13 Formal Concept Analysis with Attribute Priorities p. 211 Radim Belohlavek and Vilem Vychodil
  • Chapter 14 Literature Categorization System for Automated Database Retrieval of Scientific Articles Based on Dedicated Taxonomy p. 223 Lukáš Pichl and Manabu Suzuki and Masaki Murata and Daiji Kato and Izumi Murakami and Akira Sasaki
  • Chapter 15 A Data-Mining Framework for Designing Personalized E-Commerce Support Tools p. 235 Timothy Maciag and Dominik Śle&ecedil;zak and Daryl H. Hepting and Robert J. Hilderman
  • Chapter 16 An Adjacency Matrix Approach for Extracting User Sentiments p. 251 Bin Shi and Kuiyu Chang
  • Chapter 17 Visualizing RFID Tag Data in a Library for Detecting Latent Interest of Users p. 277 Yukio Ohsawa and Takuma Hosoda and Takeshi Ui
  • Appendix A KeyGraph and Pictorial KeyGraph p. 295
  • Appendix B A Maximal Cliques Enumeration Algorithm for MBA Transaction Data p. 299
  • Index p. 307

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