He, Yulan and Hui, Siu Cheung
(2002).
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(Version of Record)
Due to publisher licensing restrictions, this file is not available for public download |
| DOI (Digital Object Identifier) Link: | https://doi.org/10.1016/S0306-4573(01)00046-2 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
Author co-citation analysis (ACA) has been widely used in bibliometrics as an analytical method in analyzing the intellectual structure of science studies. It can be used to identify authors from the same or similar research fields. However, such analysis method relies heavily on statistical tools to perform the analysis and requires human interpretation. Web Citation Database is a data warehouse used for storing citation indices of Web publications. In this paper, we propose a mining process to automate the ACA based on the Web Citation Database. The mining process uses agglomerative hierarchical clustering (AHC) as the mining technique for author clustering and multidimensional scaling (MDS) for displaying author cluster maps. The clustering results and author cluster map have been incorporated into a citation-based retrieval system known as PubSearch to support author retrieval of Web publications.
| Item Type: | Journal Item |
|---|---|
| Copyright Holders: | 2002 Elsevier Science Ltd |
| ISSN: | 0306-4573 |
| Keywords: | author co-citation analysis; data mining; web citation database; intelligent information retrieval |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Research Group: | Centre for Research in Computing (CRC) |
| Item ID: | 23782 |
| Depositing User: | Kay Dave |
| Date Deposited: | 29 Mar 2011 12:20 |
| Last Modified: | 27 Jun 2020 06:29 |
| URI: | http://oro.open.ac.uk/id/eprint/23782 |
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