Information Retrieval by Semantic Analysis and Visualization of the Concept Space of D-Lib Magazine

Abstract

In this article we present a method for retrieving documents from a digital library through a visual interf based on automatically generated concepts. We used a vocabulary generation algorithm to generate a se concepts for the digital library and a technique called the max-min distance technique to cluster them. Additionally, the concepts were visualized in a spring embedding graph layout to depict the semantic relationship among them. The resulting graph layout serves as an aid to users for retrieving documents. online archive containing the contents of D-Lib Magazine from July 1995 to May 2002 was used to test utility of an implemented retrieval and visualization system. We believe that the method developed and tested can be applied to many different domains to help users get a better understanding of online document collections and to minimize users' cognitive load during execution of search tasks.

DOI: 10.1045/october2002-zhang

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Cite this paper

@article{Zhang2002InformationRB, title={Information Retrieval by Semantic Analysis and Visualization of the Concept Space of D-Lib Magazine}, author={Junliang Zhang and Javed Mostafa and Himansu Tripathy}, journal={D-Lib Magazine}, year={2002}, volume={8} }