Theory identity: A machine-learning approach
Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Cyfraniad i Gynhadledd
Fersiynau electronig
Dangosydd eitem ddigidol (DOI)
Theory identity is a fundamental problem for researchers seeking to determine theory quality, create theory ontologies and taxonomies, or perform focused theory-specific reviews and meta-analyses. We demonstrate a novel machine-learning approach to theory identification based on citation data and article features. The multi-disciplinary ecosystem of articles which cite a theory's originating paper is created and refined into the network of papers predicted to contribute to, and thus identify, a specific theory. We provide a 'proof-of-concept' for a highly-cited theory. Implications for cross-disciplinary theory integration and the identification of theories for a rapidly expanding scientific literature are discussed.
| Iaith wreiddiol | Saesneg |
|---|---|
| Teitl | Proceedings of the 47th Annual Hawaii International Conference on System Sciences, HICSS 2014 |
| Man cyhoeddi | United States |
| Cyhoeddwr | IEEE Computer Society Press |
| Tudalennau | 4639-4648 |
| Nifer y tudalennau | 10 |
| ISBN (Argraffiad) | 9781479925049 |
| Dynodwyr Gwrthrych Digidol (DOIs) | |
| Statws | Cyhoeddwyd - 2014 |
| Cyhoeddwyd yn allanol | Ie |