Enhancing a core journal collection for digital libraries

Enhancing a core journal collection for digital libraries Purpose – This paper aims to address the problem of enhancing the selection of titles offered by a digital library, by analysing the differences in these titles when they are cited by local authors in their publications and when they are listed in the digital library offer. Design/methodology/approach – Text mining techniques were used to identify duplicate references. Moreover, the process of identifying syntactically different data was improved with the automated discovery of thesauri from correctly matched data, and the generated thesaurus was further used in semantic clustering. The results were effectively visually represented. Findings – The paper finds that the function based on the Jaro‐Winkler algorithm may be efficiently used in the de‐duplication process. A generated thesaurus that utilises domain‐specific knowledge can also be used in the semantic clustering of references. It was shown that semantic clustering may be most useful in partitioning data, which is particularly significant when dealing with large amounts of data, which is usually the case. Moreover, those references that have the same or similar scores may be considered as candidate matches in the further de‐duplication process. Finally, it proved to be a more efficient way of visually representing the results. Originality/value – This function can be implemented to enhance the selection of titles to be offered by a digital library, in terms of making that offer more compliant with what the library users frequently cite. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Program: electronic library and information systems Emerald Publishing

Enhancing a core journal collection for digital libraries

Loading next page...
 
/lp/emerald-publishing/enhancing-a-core-journal-collection-for-digital-libraries-np5FWO49Cp
Publisher
Emerald Publishing
Copyright
Copyright © 2010 Emerald Group Publishing Limited. All rights reserved.
ISSN
0033-0337
D.O.I.
10.1108/00330331011039490
Publisher site
See Article on Publisher Site

Abstract

Purpose – This paper aims to address the problem of enhancing the selection of titles offered by a digital library, by analysing the differences in these titles when they are cited by local authors in their publications and when they are listed in the digital library offer. Design/methodology/approach – Text mining techniques were used to identify duplicate references. Moreover, the process of identifying syntactically different data was improved with the automated discovery of thesauri from correctly matched data, and the generated thesaurus was further used in semantic clustering. The results were effectively visually represented. Findings – The paper finds that the function based on the Jaro‐Winkler algorithm may be efficiently used in the de‐duplication process. A generated thesaurus that utilises domain‐specific knowledge can also be used in the semantic clustering of references. It was shown that semantic clustering may be most useful in partitioning data, which is particularly significant when dealing with large amounts of data, which is usually the case. Moreover, those references that have the same or similar scores may be considered as candidate matches in the further de‐duplication process. Finally, it proved to be a more efficient way of visually representing the results. Originality/value – This function can be implemented to enhance the selection of titles to be offered by a digital library, in terms of making that offer more compliant with what the library users frequently cite.

Journal

Program: electronic library and information systemsEmerald Publishing

Published: Apr 27, 2010

Keywords: Digital libraries; Data collection; Semantics; Databases; Serbia

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off