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Exploiting Cascading Citations for Retrieval

Dimitris Dervos and Leonidas Klimis

ASIS&T 2008 Annual Meeting (AM08 2008)
Columbus, Ohio, October 24-29, 2008


We report on the utilization of the cascading citations indexing framework (C2IF) constructs for the identification of similarities amongst entities in a bibliographic database. More specifically, the problem of chaining forward from an individual article is addressed by considering the direct as well as the indirect bibliographic citations received. From the population of articles that cite the given article directly, those which are associated with a larger number of higher-level C2IF constructs are found to be more similar to it. Evidently, the findings come to be of value also for the mirror image problem of chaining backward from a given article to a population of referenced articles, namely: cited references for which the article in question represents/hosts a larger number of higher-level C2IF constructs are likely to be more similar to it.

As a testbed, sixty (60) highly cited computer science research publications are considered, together with their associated bibliographic links from six years (1999-2005) of Science Citation Index Expanded (SCIE) data. The dataset has been made available by Thomson Scientific ( to be used for the Cascading Citations Analysis Project (C-CAP, Similarity values are calculated by considering author-supplied as well as automatically generated keyword descriptors registered in the SCIE dataset. The purpose of this research is to develop a strategy that will improve the effectiveness of retrieval in digital libraries that incorporate bibliographic citations.

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