Interactive Document Clustering System Based on Coordinated Multiple Views

Author:

Takama Yasufumi, ,Tonegawa Takuma

Abstract

This paper proposes an interactive document clustering system, which is designed based on the concept of CMV (coordinated multiple views). An interactive document clustering is used by a user to obtain a set of document groups from a document collection in interactive manner. It is expected to be useful for various tasks such as text mining and document retrieval. As the result of document clustering consists of multiple objects such as clusters (document groups), documents, and words, each of those should be presented to users in different ways. Based on this consideration, the proposed system employs multiple views, each of which is designed for specific object such as document and keyword. A prototype system is implemented on TETDM (Total Environment for Text Data Mining), which is one of environments for developing text data mining tools. As it can provide the mechanism of coordination between modules, we decided to use it for developing the prototype system. The proposed system classifies information to be presented into 4 levels: clusters, document, bag of words, and word, each of which is displayed with different views. Experimental results with test participants show the effectiveness of the proposed system.

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

Reference18 articles.

1.  Y. Takama and R. Miyake, “Proposal of Interactive Clustering System Employing Grouping-based Pairwise Constraint Generation,” PacificVis2014, Poster Session, pp. 11-12, 2014.

2.  J. C. Roberts, “State of the art: Coordinated & multiple views in exploratory visualization,” Int. Conf. on Coordinated and Multiple Views in Exploratory, pp. 61-71, 2007.

3.  M. Scherr, “Multiple and Coordinated Views in Information Visualization,” The Media Informatics Advanced Seminar on Information Visualization, 2008/2009.

4.  W. Sunayama, “Knowledge Emergence using Total Environment for Text Data Mining,” SCIS&ISIS2014, pp. 1506-1511, 2014.

5.  Y. Takama and T. Tonegawa, “Development of Interactive Document Clustering System based on Coordinated Multiple Views,” IWACIII Part 2 2015, S1-4, 2015.

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