A multi-faceted method for science classification schemes (SCSs) mapping in networking scientific resources

Wei Du (), Raymond Yiu Keung Lau, Jian Ma and Wei Xu
Additional contact information
Wei Du: City University of Hong Kong
Raymond Yiu Keung Lau: City University of Hong Kong
Jian Ma: City University of Hong Kong
Wei Xu: Renmin University of China

Scientometrics, 2015, vol. 105, issue 3, No 36, 2035-2056

Abstract: Abstract Science classification schemes (SCSs) are built to categorize scientific resources (e.g. research publications and research projects) into disciplines for effective research analytics and management. With the explosive growth of the number of scientific resources in distributed research institutions in recent years, effectively mapping different SCSs, especially heterogeneous SCSs that categorize different kinds of scientific resources, is becoming an increasingly challenging problem for facilitating information interoperability and networking scientific resources. To effectively realize the heterogeneous SCSs mapping, we design a novel multi-faceted method to measure the similarity between two classes based on three important facets, namely descriptors, individuals, and semantic neighborhood. Particularly, the proposed approach leverages a hybrid method combining statistical learning, semantic analysis and structure analysis for effective measurement with the exploitation of symmetric Tversky’s index, WordNet dictionary and the Hungarian Algorithm. The method has been evaluated based on two main SCSs that need mapping for information management and policy-making in NSFC, and shown satisfying results. The interoperability among heterogeneous SCSs is resolved to enhance the access to heterogeneous scientific resources and the development of appropriate research analytics policies.

Keywords: Science classification scheme (SCS); Multi-faceted mapping; Semantic analysis; Research management (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-015-1742-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:105:y:2015:i:3:d:10.1007_s11192-015-1742-z

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-015-1742-z

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().