Abstract
Chance discovery has achieved much success in discovering events that, though rare, are important to human decision making. Since humans are able to efficiently interact with graphical representations of data, it is useful to use visualizations for chance discovery. KeyGraph enables efficient visualization of data for chance discovery, but does not have provisions for adding domain-specific constraints. This contribution extends the concepts of KeyGraph to a visualization method based on the target sociogram. As the target sociogram is hierarchical in nature, it allows hierarchical constraints to be embedded in visualizations for chance discovery. The details of the hierarchical visualization method are presented and a class of problems is defined for its use. An example from software requirements engineering illustrates the efficacy of our approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ohsawa, Y.: Data crystallization: chance discovery extended for dealing with unobservable events. New mathematics and natural science 1(3), 373–392 (2005)
Ohsawa, Y.: Chance discoveries for making decisions in complex real world. New Generation Computing 20, 143–163 (2002)
Ohsawa, Y.: Modelling the process of chance discovery. In: Ohsawa, Y., McBurney, P. (eds.) Chance Discovery, pp. 2–15. Springer, Heidelberg (2003)
Larkin, J., Simon, H.: Why a diagram is (sometimes) worth ten thousand words. Cognitive Science 11, 65–99 (1987)
Matsumura, N.: Topic diffusion in a community. In: Ohsawa, Y., McBurney, P. (eds.) Chance Discovery, pp. 84–97. Springer, Heidelberg (2003)
Ohsawa, Y.: Keygraph: Visualized structure among event clusters. In: Ohsawa, Y., McBurney, P. (eds.) Chance Discovery, pp. 262–275. Springer, Heidelberg (2003)
Ohsawa, Y.: Detection of earthquake risks with keygraph. In: Ohsawa, Y., McBurney, P. (eds.) Chance Discovery, pp. 339–350. Springer, Heidelberg (2003)
Fukuda, H.: Application to understanding consumers’ latent desires. In: Ohsawa, Y., McBurney, P. (eds.) Chance Discovery, pp. 383–396. Springer, Heidelberg (2003)
Northway, M.: A method for depicting social relationships obtained by sociometric testing. Sociometry 3(2), 144–150 (1940)
Northway, M.L.: A Primer of Sociometry. University of Toronto Press (1967)
Shimojima, A.: Operational constraints in diagrammatic reasoning. In: Allwein, Barwise (eds.) Logical Reasoning with Diagrams, pp. 27–48. Oxford University Press, Oxford (1996)
Dey, A., Abowd, G.: Towards a Better Understanding of Context and Context-Awareness. In: CHI 2000 Workshop on the What, Who, Where, When, and How of Context-Awareness (2000)
Weber, B., Bojduj, B.: Tabu search for military supply distribution. In: InterSymp-2006, Focus Symposium on Advances in Intelligent Software Systems, Baden-Baden, Germany, August, 2006, pp. 87–91 (2006)
Geraci, A.: IEEE Standard Computer Dictionary: Compilation of IEEE Standard Computer Glossaries. Institute of Electrical and Electronics Engineers Inc. (1991)
Zave, P.: Classification of research efforts in requirements engineering. ACM Comput. Surv. 29(4), 315–321 (1997)
Jackson, M.: Software requirements and specifications. ACM Press, New York (1995)
Welty, C.A., Selfridge, P.: Artificial intelligence and software engineering: Breaking the toy mold. Automated Software Engineering 4(3), 255–270 (1997)
Gibson, V.R., Senn, J.A.: System structure and software maintenance performance. Commun. ACM 32(3), 347–358 (1989)
Bohner, S., Arnold, R.: An introduction to software change impact analysis. In: Bohner, S., Arnold, R. (eds.) Software Change Impact Analysis, pp. 1–26. IEEE Computer Society Press, Los Alamitos (1996)
Leveson, N., Turner, C.: An investigation of the therac-25 accidents. IEEE Computer 26(7), 18–41 (1993)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Bojduj, B., Turner, C.S. (2007). Hierarchical Visualization for Chance Discovery. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_78
Download citation
DOI: https://doi.org/10.1007/978-3-540-73325-6_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73322-5
Online ISBN: 978-3-540-73325-6
eBook Packages: Computer ScienceComputer Science (R0)