Evaluating Publication Similarity Measures.

Abstract

Publication searching based on keywords provided by users is traditional in digital libraries. While useful in many circumstances, the success of locating related publications via keyword-based searching paradigm is influenced by how users choose their keywords. Example-based searching, where user provides an example publication to locate similar publications, is also becoming commonplace in digital libraries. Existing publication similarity measures, needed for example-based searching, fall into two classes, namely, text-based similarity measures from Information Retrieval, and citation-based similarity measures based on bibliographic coupling and/or co-citation. In this paper, we list a number of publication similarity measures, and extend and evaluate them in terms of their accuracy, separability, and independence. For evaluation, we use the ACM SIGMOD Anthology, a digital library of about 15,000 publications. 1