Citation retrieval in digital libraries

Abstract

Currently, more and more research papers are being published in the form of digital libraries on the World Wide Web. How to search them efficiently and effectively is a big challenge for researchers. With a static subject tree to index the paper and with the traditional query mechanism, many problems appear. Detail-level topics can hardly be found, emerging new areas cannot be identified, non-semantically related papers can hardly be retrieved, and the key papers in the area cannot be obviously pointed out. In order to solve these problems, this paper proposes a novel approach to map the citation retrieval problem into a graph partitioning problem. All citations in a digital library are mapped to a citation graph through their reference links. It is observed that the citation graph is not evenly connected. Highly connected sub-graphs often emerge. Different sub-graphs represent different topics, and partitioning the graph at higher levels can reveal the detail-level topics. The different connectivities can also help in finding hot topics, related topics and key citations. Since all these can be done automatically and efficiently, the user's manual effort in searching for citations is saved, but the results are more comprehensive and accurate.

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