Tang, J., Fong, A.C.M., Wang, B. and Zhang, J. (2012) A unified probabilistic framework for name disambiguation in digital library. IEEE Transactions on Knowledge and Data Engineering, 24(6), pp. 957-987. (doi: 10.1109/TKDE.2011.13)
Full text not currently available from Enlighten.
Abstract
Despite years of research, the name ambiguity problem remains largely unresolved. Outstanding issues include how to capture all information for name disambiguation in a unified approach, and how to determine the number of people K in the disambiguation process. In this paper, we formalize the problem in a unified probabilistic framework, which incorporates both attributes and relationships. Specifically, we define a disambiguation objective function for the problem and propose a two-step parameter estimation algorithm. We also investigate a dynamic approach for estimating the number of people K. Experiments show that our proposed framework significantly outperforms four baseline methods of using clustering algorithms and two other previous methods. Experiments also indicate that the number K automatically found by our method is close to the actual number.
Item Type: | Articles |
---|---|
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Fong, Dr Alvis Cheuk Min |
Authors: | Tang, J., Fong, A.C.M., Wang, B., and Zhang, J. |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
College/School: | College of Science and Engineering > School of Computing Science |
Journal Name: | IEEE Transactions on Knowledge and Data Engineering |
ISSN: | 1041-4347 |
ISSN (Online): | 1558-2191 |
University Staff: Request a correction | Enlighten Editors: Update this record