Klink-2: integrating multiple web sources to generate semantic topic networks
- Submitting institution
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The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1587404
- Type
- E - Conference contribution
- DOI
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10.1007/978-3-319-25007-6_24
- Title of conference / published proceedings
- Lecture Notes in Computer Science
- First page
- 408
- Volume
- 9366
- Issue
- -
- ISSN
- 0302-9743
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2015
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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1
- Research group(s)
-
-
- Citation count
- 18
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper introduces Klink-2, an innovative approach to automatically generating large-scale ontologies of research topics. Klink-2’s approach is unique in its use of diachronic relationships between topics and fusion of multiple sources of evidence. Formally demonstrated, this hybrid approach optimizes output quality. Klink-2 has been used to generate the Computer Science Ontology (CSO), the most comprehensive taxonomy of topics in Computer Science. CSO has been used in academia to support topic modelling (Beck et al., 2020) and, since 2016, has been adopted by Springer Nature (Editorial Director, LNCS and Computer Science Proceedings) to annotate all their Computer Science proceedings.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -