Approximate string matching

About: Approximate string matching is a research topic. Over the lifetime, 1903 publications have been published within this topic receiving 62352 citations. The topic is also known as: fuzzy string-searching algorithm & fuzzy string-matching algorithm.

Parallel construction of a suffix tree with applications

Abstract: Many string manipulations can be performed efficiently on suffix trees. In this paper a CRCW parallel RAM algorithm is presented that constructs the suffix tree associated with a string ofn symbols inO(logn) time withn processors. The algorithm requires ź(n2) space. However, the space needed can be reduced toO(n1+ź) for any 0< ź ≤1, with a corresponding slow-down proportional to 1/ź. Efficient parallel procedures are also given for some string problems that can be solved with suffix trees.

Bed-tree: an all-purpose index structure for string similarity search based on edit distance

Abstract: Strings are ubiquitous in computer systems and hence string processing has attracted extensive research effort from computer scientists in diverse areas. One of the most important problems in string processing is to efficiently evaluate the similarity between two strings based on a specified similarity measure. String similarity search is a fundamental problem in information retrieval, database cleaning, biological sequence analysis, and more. While a large number of dissimilarity measures on strings have been proposed, edit distance is the most popular choice in a wide spectrum of applications. Existing indexing techniques for similarity search queries based on edit distance, e.g., approximate selection and join queries, rely mostly on n-gram signatures coupled with inverted list structures. These techniques are tailored for specific query types only, and their performance remains unsatisfactory especially in scenarios with strict memory constraints or frequent data updates. In this paper we propose the Bed-tree, a B+-tree based index structure for evaluating all types of similarity queries on edit distance and normalized edit distance. We identify the necessary properties of a mapping from the string space to the integer space for supporting searching and pruning for these queries. Three transformations are proposed that capture different aspects of information inherent in strings, enabling efficient pruning during the search process on the tree. Compared to state-of-the-art methods on string similarity search, the Bed-tree is a complete solution that meets the requirements of all applications, providing high scalability and fast response time.

Fast-join: An efficient method for fuzzy token matching based string similarity join

Abstract: String similarity join that finds similar string pairs between two string sets is an essential operation in many applications, and has attracted significant attention recently in the database community. A significant challenge in similarity join is to implement an effective fuzzy match operation to find all similar string pairs which may not match exactly. In this paper, we propose a new similarity metrics, called “fuzzy token matching based similarity”, which extends token-based similarity functions (e.g., Jaccard similarity and Cosine similarity) by allowing fuzzy match between two tokens. We study the problem of similarity join using this new similarity metrics and present a signature-based method to address this problem. We propose new signature schemes and develop effective pruning techniques to improve the performance. Experimental results show that our approach achieves high efficiency and result quality, and significantly outperforms state-of-the-art methods.

Bounds for the String Editing Problem

Abstract: The string editing problem is to determine the distance between two strings as measured by the minimal cost sequence of deletions, insertions, and changes of symbols needed to transform one string into the other. The longest common subsequence problem can be viewed as a special case. Wagner and Fischer proposed an algorithm that runs in time O(nm), where n, m are the lengths of the two strings. In the present paper, it is shown that if the operations on symbols of the strings are restricted to tests of equality, then O(nm) operations are necessary (and sufficient) to compute the distance.