The proliferation of digitally available textual data necessitates automatic tools for analyzing large textual collections. Thus, in analogy to data mining for structured databases, text mining is defined for textual collections. A central tool in text-mining is the analysis of concept relationship, which discovers connections between different concepts, as reflected in the collection. However, discovering these relationships is not sufficient, as they also have to be presented to the user in a meaningful and manageable way. In this paper we introduce a new family of visualization tools, which we coin circle graphs, which provide means for visualizing concept relationships mined from large collections. Circle graphs allow for instant appreciation of multiple relationships gathered from the entire collection. A special type of circle-graphs, called Trend Graphs, allows tracking of the evolution of relationships over time.
|Original language||American English|
|Title of host publication||Principles of Data Mining and Knowledge Discovery - 3d European Conference, PKDD 1999, Proceedings|
|Editors||Jan M. Żytkow, Jan Rauch|
|Number of pages||6|
|ISBN (Print)||3540664904, 9783540664901|
|State||Published - 1999|
|Event||3rd European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 1999 - Prague, Czech Republic|
Duration: 15 Sep 1999 → 18 Sep 1999
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||3rd European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 1999|
|Period||15/09/99 → 18/09/99|
Bibliographical notePublisher Copyright:
© Springer-Verlag Berlin Heidelberg 1999.