Detecting duplicate biological entities using Shortest Path Edit Distance

作者：Rudniy Alex^*; Song Min; Geller James

来源：International Journal of Data Mining and Bioinformatics, 2010, 4(4): 395-410.

DOI：10.1504/IJDMB.2010.034196

• biological entity matching
• SPED
• shortest path edit distance
• histogram matching
• duplicate record detection
• text mining
• Levenshtein

Duplicate entity detection in biological data is an important research task. In this paper, we propose a novel and context-sensitive Shortest Path Edit Distance (SPED) extending and supplementing our previous work on Markov Random Field-based Edit Distance (MRFED). SPED transforms the edit distance computational problem to the calculation of the shortest path among two selected vertices of a graph. We produce several modifications of SPED by applying Levenshtein, arithmetic mean, histogram difference and TFIDF techniques to solve subtasks. We compare SPED performance to other well-known distance algorithms for biological entity matching. The experimental results show that SPED produces competitive outcomes.

• 出版日期2010