Shortest Path Edit Distance for detecting duplicate biological entities

Alex Rudniy; Min Song; James Geller

doi:10.1145/1854776.1854851

Shortest Path Edit Distance for detecting duplicate biological entities

Alex Rudniy, Min Song, James Geller

Department of Library and Information Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

This paper presents a novel and context-sensitive Shortest Path Edit Distance (SPED) applied to duplicate entity detection in biological data. SPED is an extension of Markov Random Field-based Edit Distance. It transforms the edit distance computational problem to the calculation of the shortest path among two selected vertices of a graph. The experimental results show that SPED produces competitive outcomes. Soft-SPED, the combination of SPED with TFIDF, achieves superior performance in most cases.

Original language	English
Title of host publication	2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
Pages	442-444
Number of pages	3
DOIs	https://doi.org/10.1145/1854776.1854851
Publication status	Published - 2010
Event	2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 - Niagara Falls, NY, United States Duration: 2010 Aug 2 → 2010 Aug 4

Publication series

Name	2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010

Other

Other	2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
Country	United States
City	Niagara Falls, NY
Period	10/8/2 → 10/8/4

All Science Journal Classification (ASJC) codes

Biomedical Engineering
Health Information Management

Access to Document

10.1145/1854776.1854851

Cite this

@inproceedings{9db041c153034a9eb8a2cb97156e5131,

title = "Shortest Path Edit Distance for detecting duplicate biological entities",

abstract = "This paper presents a novel and context-sensitive Shortest Path Edit Distance (SPED) applied to duplicate entity detection in biological data. SPED is an extension of Markov Random Field-based Edit Distance. It transforms the edit distance computational problem to the calculation of the shortest path among two selected vertices of a graph. The experimental results show that SPED produces competitive outcomes. Soft-SPED, the combination of SPED with TFIDF, achieves superior performance in most cases.",

author = "Alex Rudniy and Min Song and James Geller",

note = "Copyright: Copyright 2010 Elsevier B.V., All rights reserved.; 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 ; Conference date: 02-08-2010 Through 04-08-2010",

year = "2010",

doi = "10.1145/1854776.1854851",

language = "English",

isbn = "9781450304382",

series = "2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010",

pages = "442--444",

booktitle = "2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010",

}

Rudniy, A, Song, M & Geller, J 2010, Shortest Path Edit Distance for detecting duplicate biological entities. in 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010. 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010, pp. 442-444, 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010, Niagara Falls, NY, United States, 10/8/2. https://doi.org/10.1145/1854776.1854851

Shortest Path Edit Distance for detecting duplicate biological entities. / Rudniy, Alex; Song, Min; Geller, James.

2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010. 2010. p. 442-444 (2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - This paper presents a novel and context-sensitive Shortest Path Edit Distance (SPED) applied to duplicate entity detection in biological data. SPED is an extension of Markov Random Field-based Edit Distance. It transforms the edit distance computational problem to the calculation of the shortest path among two selected vertices of a graph. The experimental results show that SPED produces competitive outcomes. Soft-SPED, the combination of SPED with TFIDF, achieves superior performance in most cases.

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