Results 1 
4 of
4
The LikeIt Intelligent String Comparison Facility
 NEC Research Institute
, 1997
"... A highlyefficient ANSIC facility is described for intelligently comparing a query string with a series of database strings. The bipartite weighted matching approach taken tolerates ordering violations that are problematic for simple automaton or string edit distance methodsyet common in practic ..."
Abstract

Cited by 19 (0 self)
 Add to MetaCart
A highlyefficient ANSIC facility is described for intelligently comparing a query string with a series of database strings. The bipartite weighted matching approach taken tolerates ordering violations that are problematic for simple automaton or string edit distance methodsyet common in practice. The method is character and polygraph based and does not require that words are properly formed in a query. Database characters are processed at a rate of approximately 2.5 million per second using a 200MHz Pentium Pro processor. A subroutinelevel API is described along with an simple executable utility supporting both commandline and Web interfaces. An optimized Web interface is also reported consisting of a daemon that preloads multiple databases, and a corresponding CGI stub. The daemon may be initiated manually or via inetd. Keywords: String Comparison/Similarity, Text/Database Search/Retrieval, Bipartite Matching/Assignment, Edit Distance. Both authors are with the NEC Research I...
Linear and O(n log n) Time MinimumCost Matching Algorithms for Quasiconvex Tours (Extended Abstract)
"... Samuel R. Buss # Peter N. Yianilos + Abstract Let G be a complete, weighted, undirected, bipartite graph with n red nodes, n # blue nodes, and symmetric cost function c(x, y) . A maximum matching for G consists of min{n, n # edges from distinct red nodes to distinct blue nodes. Our objective is ..."
Abstract

Cited by 14 (3 self)
 Add to MetaCart
Samuel R. Buss # Peter N. Yianilos + Abstract Let G be a complete, weighted, undirected, bipartite graph with n red nodes, n # blue nodes, and symmetric cost function c(x, y) . A maximum matching for G consists of min{n, n # edges from distinct red nodes to distinct blue nodes. Our objective is to find a minimumcost maximum matching, i.e. one for which the sum of the edge costs has minimal value. This is the weighted bipartite matching problem; or as it is sometimes called, the assignment problem.
A Bipartite Matching Approach to Approximate String Comparison and Search
, 1995
"... Approximate string comparison and search is an important part of applications that range from natural language to the interpretation of DNA. This paper presents a bipartite weighted graph matching approach to these problems, based on the authors' linear time matching algorithms # . Our appro ..."
Abstract

Cited by 9 (1 self)
 Add to MetaCart
(Show Context)
Approximate string comparison and search is an important part of applications that range from natural language to the interpretation of DNA. This paper presents a bipartite weighted graph matching approach to these problems, based on the authors' linear time matching algorithms # . Our approach's tolerance to permutation of symbols or blocks, distinguishes it from the widely used edit distance and finite state machine methods. A close relationship with the earlier related `proximity comparison' method is established.
A Bipartite Matching Approach to Approximate String Comparison and Search
"... Approximate string comparison and search is an important part of applications that range from natural language to the interpretation of DNA. This paper presents a bipartite weighted graph matching approach to these problems, based on the authors ’ linear time matching algorithms ‡. Our approach’s to ..."
Abstract
 Add to MetaCart
(Show Context)
Approximate string comparison and search is an important part of applications that range from natural language to the interpretation of DNA. This paper presents a bipartite weighted graph matching approach to these problems, based on the authors ’ linear time matching algorithms ‡. Our approach’s tolerance to permutation of symbols or blocks, distinguishes it from the widely used edit distance and finite state machine methods. A close relationship with the earlier related ‘proximity comparison ’ method is established. Under the linear cost model, a simple O(1) time per position online algorithm is presented for comparing two strings given a fixed alignment. Heuristics are given for optimal alignment. In the approximate string search problem, one string advances in a fixed direction relative to the other with each time step. We introduce a new online algorithm for this setting which dynamically maintains an optimal bipartite weighted matching. We discuss the application of our algorithms to natural language text search, including prefilters to improve efficiency, and the use of polygraphic symbols to improve search quality. Our approach is used in the LikeIt text search utility now under development. Its overall design and objectives are summarized.