Association Analytics for Network Connectivity in a Bibliographic and Expertise Dataset

Association Analytics for Network Connectivity in a Bibliographic and Expertise Dataset

Boanerges Aleman-Meza (University of Georgia, USA)
Copyright: © 2009 |Pages: 20
DOI: 10.4018/978-1-60566-112-4.ch008

Abstract

This chapter highlights the benefits of semantics for analysis of the collaboration network in a bibliography dataset. Metadata of publications was used for extracting keywords and terms, which can be the starting point towards building a taxonomy of topics. The aggregated effect of the topics over all publications of an author can be used to determine his/her areas of expertise. We also highlight the value of using a taxonomy of topics in searching experts on a given topic.
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Background

Bibliography datasets have been used to measure how authors are connected, publication output, citations, etc. The motivation of such analysis typically is gaining insight of how a community evolves and the characteristics of the social or collaborative interactions among authors. Many techniques for analysis of bibliography data have their roots or are related to social networks analysis, which focuses on the analysis of patterns of relationships among people, organizations, states and such social entities.

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