Abstract
A human’s process is proposed for data based scenario understanding, by integrating two existing tools in a new way of annotation. Scenario of a patient’s hepatitis progress or recovery was obtained, by the presented process integrating a scenario map and a scenario flow diagram which are obtained from data on the patient’s blood tests. The data was first visualized by KeyGaph as a scenario map, showing the rough view of event transitions. The user then discussed looking at the visualization, and wrote scenarios his/her thought of from the map. This text was visualized, again by KeyGraph, which externalizes the relations of events in his thought. On this visual output, the user came to be enabled to pay attention to potential chances existing at the cross points of scenarios. Based on this attention, the user annotated on the scenario flow diagram presented by the Discourse Structure Visualizer (DSV), showing the details of event transitions from the same data. As a result, the obtained annotations enabled hepatic experts to understand useful and novel scenarios underlying the patient’s chronological history.
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
Greenacre, M.J.: Correspondence Analysis in Practice. Academic Press, London (1993)
Ho, T.B., et al.: Visualization support for a user-centered KDD process. In: Proceedings of the Eighth ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2002), pp. 519–524 (2002)
Ho, T.B., et al.: Mining Hepatitis Data with Temporal Abstraction. In: Proc. The Ninth ACM Int.l Conf. on Knowledge Discovery and Data Mining (KDD 2003), pp. 519–524 (2003)
Igata, N., Tsuda, H., Katayama, Y., Kozakura, F.: Semantic groupware and its application to KnowWho using RDF. In: ISWC (2nd Intl. Semantic Web Conference) Poster, Florida, USA (October 20-23, 2003)
Matsumura, N., Ohsawa, Y., Ishizuka, M.: Influence Diffusion Model in Text-Based Communication, Poster. In: The Eleventh Conf. World Wide Web (2002)
Ohsawa, Y., Usui, M.: Chance Discovery in Textile Market on Scenario Communications with Touchable KeyGraph. Readings in Chance Discovery (2005)
Ohsaki, M., et al.: A Rule Discovery Support System for Sequential Medical Data. In: The Case Study of a Chronic Hepatitis Dataset, International Workshop on Active Mining in IEES Int.l Conf. Data Mining, pp. 97–102 (2002)
Okazaki, N., Ohsawa, Y.: Polaris: An Integrated Data Miner for Chance Discovery. In: Proceedings of The Third International Workshop on Chance Discovery and Its Management, Crete, Greece (2003)
Salton, G., Buckley, C.: Term weighting approaches in automatic text retrieval. Information Processing and Management 24(5), 513–523 (1988)
Suzuki, E., Watanabe, T., Yokoi, H., Takabayashi, K.: Detecting Interesting Exceptions from Medical Test Data with Visual Summarization. In: Proc. Third IEEE International Conference on Data Mining (ICDM), pp. 315–322 (2003)
Ohsawa, Y.: Modeling the Process of Chance Discovery. In: Ohsawa, Y., McBurney, P. (eds.) Chance Discovery, pp. 2–15. 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., et al.: Mining Scenarios for Hepatitis B and C. In: Paton, R. (ed.) Multidisciplinary Approaches to Theory in Medicine (2005)
Yoshida, T., et al.: Preliminary Analysis of Interferon Therapy by Graph- Based Induction. In: Proc. International Workshop on Active Mining, Japanese Soc. AI (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ohsawa, Y. (2005). Human-Based Annotation of Data-Based Scenario Flow on Scenario Map for Understanding Hepatitis Scenarios. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_74
Download citation
DOI: https://doi.org/10.1007/11552413_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28894-7
Online ISBN: 978-3-540-31983-2
eBook Packages: Computer ScienceComputer Science (R0)