@inproceedings{5204d7df489d494fa2c0e355bf164628,

title = "Bounded occurrence edit distance: A new metric for string similarity joins with edit distance constraints",

abstract = "Given two sets of strings and a similarity function on strings, similarity joins attempt to find all similar pairs of strings from each respective set. In this paper, we focus on similarity joins with respect to the edit distance, and propose a new metric called the bounded occurrence edit distance and a filter based on the metric. Using the filter, we can reduce the total time required to solve similarity joins because the metric can be computed faster than the edit distance by bitwise operations. We demonstrate the effectiveness of the filter through experiments.",

keywords = "Data integration, Edit distance, Similarity join problem, Similarity search",

author = "Tomoki Komatsu and Ryosuke Okuta and Kazuyuki Narisawa and Ayumi Shinohara",

note = "Copyright: Copyright 2016 Elsevier B.V., All rights reserved.; 40th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2014 ; Conference date: 26-01-2014 Through 29-01-2014",

year = "2014",

doi = "10.1007/978-3-319-04298-5_32",

language = "English",

isbn = "9783319042978",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "363--374",

booktitle = "SOFSEM 2014",

}