期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2005
卷号：28
期号：04
出版社：IEEE Computer Society
摘要：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 mea-
sures 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.
