Inventing discovery tools: Combining information visualization with data mining

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2226, Issue , 2001, Pages 17-28

  Shneiderman, Ben ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA VISUALIZATION; INFORMATION SYSTEMS; INFORMATION USE; MACHINE LEARNING; VISUALIZATION;

DATA DISTRIBUTION; DATA MINING ALGORITHM; EXPLORATORY DATA ANALYSIS; HYPOTHESIS TESTING; INFORMATION VISUALIZATION; STATISTICAL ALGORITHM; USER CONTROL; VISUAL DATA;

DATA MINING;

EID: 84943247371     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45650-3_4     Document Type: Conference Paper

References (19)

1. Ahlberg, C. and Shneiderman, B., Visual Information Seeking: Tight coupling of dynamic query filters with starfield displays, Proc. of ACM CHI’94 Human Factors in Computing Systems, ACM Press, NewYork (April 1994), 313-317 + color plates.
2. Ankerst, M., Ester, M., and Kriegel, H.-P., Towards an effective cooperation of the user and the computer for classification, Proc. 6th ACM SIGKDD International Conf. on Knowledge Discovery and Data Mining, ACM, NewYork (2000), 179-188
3. Barnett, Vic, and Lewis, Toby, Outliers in Statistical Data, JohnWiley & Son Ltd; 3rd edition (April 1994).
4. Bradley, E., Time-series analysis, In Berthold, M. and Hand, E. (Editors), Intelligent Data Analysis: An Introduction, Springer (1999)
5. Card, S., Mackinlay, J, and Shneiderman, B. (Editors), Readings in InformationVisualization: Using Vision to Think, Morgan Kaufmann Publishers, San Francisco, CA (1999)
6. Fayyad, U., Piatetsky-Shapiro, G., Smyth, P., and Uthurusamy, R., (Editors), Advances in Knowledge Discovery and Data Mining. MIT Press, Cambridge, MA (1996)
7. Fisher, R.A., The Design of Experiments, Oliver and Boyd, Edinburgh (1935). 9th edition, Macmillan, NewYork (1971)
8. Han, Jiawei and Kamber, Micheline, Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers, San Francisco (2000).
9. Hochheiser, H. and Shneiderman, B., Interactive exploration of time-series data, In Proc. Discovery Science, Springer (2001)
10. Hinneburg, A., Keim, D., and Wawryniuk, M., HD-Eye: Visual mining of high-dimensional data, IEEE Computer Graphics and Applications 19, 5 (Sept/Oct 1999), 22-31
11. Koenemann, J. and Belkin, N., A case for interaction: A study of interactive information retrieval behavior and effectiveness, Proc. CHI’96 Human Factors in Computing Systems, ACM Press, NewYork (1996), 205-212
12. Montgomery, D., Design and Analysis of Experiments, 3rd ed,Wiley, NewYork (1991)
13. Spence, Robert, Information Visualization, Addison-Wesley, Essex, England (2001)
14. Tukey, John, The technical tools of statistics, American Statistician 19 (1965), 23-28.Available at: http://stat.bell-labs.com/who/tukey/memo/techtools.html
15. Ware, M., Frank, E., Homes, F., Hall, M., and Witten, I. H., Interactive machine learning: Letting users build classifiers, International Journal of Human-Computer Studies (2001, in press)
16. Weizenbaum, Joseph, Computer Power and Human Reason: From Judgment to Calculation, W. H. Freeman and Co., San Francisco, CA, (1976)
17. Westphal, Christopher and Blaxton, Teresa, Data Mining Solutions: Methods and Tools for Solving Real-World Problems, JohnWiley & Sons (1999)
18. Williamson, Christopher, and Shneiderman, Ben, The Dynamic HomeFinder: Evaluating dynamic queries in a real-estate information exploration system, Proc.ACM SIGIR’92 Conference, ACM Press (1992), 338-346
19. Witten, Ian, and Frank, Eibe, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, Morgan Kaufmann Publishers, San Francisco (2000).