Two supervised learning approaches for name disambiguation in author citations

By Hui Han, C. Lee Giles, Hongyuan Zha, Cheng Li, Kostas Tsioutsiouliklis. Proceedings of the 2004 Joint ACM/IEEE Conference on Digital Libraries, 2004., 2004

410 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/7ea9c3c042b0e3423a2110cddbe7926f8b661bfd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Vetle I. Torvik
2. Neil R. Smalheiser
3. Jie Tang
4. Yuxiao Dong
5. Xiao Liu
6. Kuansan Wang
7. Miriam J. Metzger
8. C. Lee Giles

In Management Science and Operations Research

1. Vetle I. Torvik
2. Neil R. Smalheiser
3. Miriam J. Metzger
4. Hui Han
5. C. Lee Giles
6. Hongyuan Zha
7. Yuxiao Dong
8. Jie Tang

In Molecular Biology

1. Vetle I. Torvik
2. Neil R. Smalheiser
3. Miriam J. Metzger
4. Hongyuan Zha
5. Kuansan Wang
6. Yuxiao Dong
7. Jie Tang
8. Xiao Liu

Citations in the corpus

• Author Name Disambiguation in MEDLINE (2009, methodology): “…that groups articles by similarity [Han et al. 2005; Soler 2007; Yin et al. 2007]; (d) supervised methods that utilize manually com­piled training sets [Han et al. 2004; Reuther and Walter 2006; On et al. 2005]; and (e) methods that go beyond pairwise analysis of explicit information to analyze…”
• Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research (2007, background): “The disambiguation of authors whose names coincide and overlap in the citation indexing systems calls for methods that distinguish the contexts in which authors or individuals appear, such as cross-document co-reference resolution algorithms that use the vector space model to resolve ambiguities (Ba”
• OAG: Toward Linking Large-scale Heterogeneous Entity Graphs (2019, background): “The problem of entity linking is related to entity matching [20, 25, 36], entity resolution [2, 3], web appearance disambiguation [1, 11], name identification [16], object distinction [37], and name disambiguation [8, 30, 40], and has been extensively studied for decades by different communities.”
• Name disambiguation in author citations using a K-way spectral clustering method (2005, background): “A “canonical name” [26] includes an authorized name as a special case.”
• Disambiguating Web appearances of people in a social network (2005, neutral): “, [10]), with various supervised methods proposed for its solution.”