The Experts below are selected from a list of 2637 Experts worldwide ranked by ideXlab platform
P.-a. Larson - One of the best experts on this subject based on the ideXlab platform.
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Speeding up heterogeneous data access by converting and pushing down String Comparisons
Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337), 1999Co-Authors: W. Zhang, P.-a. LarsonAbstract:Pushing down predicates to an external data source is critical to the performance for querying heterogeneous data sources. However, predicate-containing String Comparisons cannot be pushed down unchanged if the external data source uses a different collating sequence. We describe a table-driven technique for rewriting such predicates to account for the differences in collation. In addition to precise conversion, we also consider imprecise conversion.
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ICDE - Speeding up heterogeneous data access by converting and pushing down String Comparisons
Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337), 1999Co-Authors: W. Zhang, P.-a. LarsonAbstract:Pushing down predicates to an external data source is critical to the performance for querying heterogeneous data sources. However, predicate-containing String Comparisons cannot be pushed down unchanged if the external data source uses a different collating sequence. We describe a table-driven technique for rewriting such predicates to account for the differences in collation. In addition to precise conversion, we also consider imprecise conversion.
W. Zhang - One of the best experts on this subject based on the ideXlab platform.
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Speeding up heterogeneous data access by converting and pushing down String Comparisons
Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337), 1999Co-Authors: W. Zhang, P.-a. LarsonAbstract:Pushing down predicates to an external data source is critical to the performance for querying heterogeneous data sources. However, predicate-containing String Comparisons cannot be pushed down unchanged if the external data source uses a different collating sequence. We describe a table-driven technique for rewriting such predicates to account for the differences in collation. In addition to precise conversion, we also consider imprecise conversion.
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ICDE - Speeding up heterogeneous data access by converting and pushing down String Comparisons
Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337), 1999Co-Authors: W. Zhang, P.-a. LarsonAbstract:Pushing down predicates to an external data source is critical to the performance for querying heterogeneous data sources. However, predicate-containing String Comparisons cannot be pushed down unchanged if the external data source uses a different collating sequence. We describe a table-driven technique for rewriting such predicates to account for the differences in collation. In addition to precise conversion, we also consider imprecise conversion.
Tugkan Batu - One of the best experts on this subject based on the ideXlab platform.
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locally consistent parsing and applications to approximate String Comparisons
Developments in Language Theory, 2005Co-Authors: Tugkan Batu, Cenk S SahinalpAbstract:Locally consistent parsing (LCP) is a context sensitive partitioning method which achieves partition consistency in (almost) linear time. When iteratively applied, LCP followed by consistent block labeling provides a powerful tool for processing Strings for a multitude of problems. In this paper we summarize applications of LCP in approximating well known distance measures between pairs of Strings in (almost) linear time.
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Developments in Language Theory - Locally consistent parsing and applications to approximate String Comparisons
Developments in Language Theory, 2005Co-Authors: Tugkan Batu, S. Cenk SahinalpAbstract:Locally consistent parsing (LCP) is a context sensitive partitioning method which achieves partition consistency in (almost) linear time. When iteratively applied, LCP followed by consistent block labeling provides a powerful tool for processing Strings for a multitude of problems. In this paper we summarize applications of LCP in approximating well known distance measures between pairs of Strings in (almost) linear time.
Moon-kyun Kim - One of the best experts on this subject based on the ideXlab platform.
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Plagiarism Detection Using the Levenshtein Distance and Smith-Waterman Algorithm
2008 3rd International Conference on Innovative Computing Information and Control, 2008Co-Authors: Byung-ryul Ahn, Ki-yol Eom, Min-koo Kang, Jin-pyung Kim, Moon-kyun KimAbstract:Plagiarism in texts is issues of increasing concern to the academic community. Now most common text plagiarism occurs by making a variety of minor alterations that include the insertion, deletion, or substitution of words. Such simple changes, however, require excessive String Comparisons. In this paper, we present a hybrid plagiarism detection method. We investigate the use of a diagonal line, which is derived from Levenshtein distance, and simplified Smith-Waterman algorithm that is a classical tool in the identification and quantification of local similarities in biological sequences, with a view to the application in the plagiarism detection. Our approach avoids globally involved String Comparisons and considers psychological factors, which can yield significant speed-up by experiment results. Based on the results, we indicate the practicality of such improvement using Levenshtein distance and Smith-Waterman algorithm and to illustrate the efficiency gains. In the future, it would be interesting to explore appropriate heuristics in the area of text comparison.
S. Cenk Sahinalp - One of the best experts on this subject based on the ideXlab platform.
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Developments in Language Theory - Locally consistent parsing and applications to approximate String Comparisons
Developments in Language Theory, 2005Co-Authors: Tugkan Batu, S. Cenk SahinalpAbstract:Locally consistent parsing (LCP) is a context sensitive partitioning method which achieves partition consistency in (almost) linear time. When iteratively applied, LCP followed by consistent block labeling provides a powerful tool for processing Strings for a multitude of problems. In this paper we summarize applications of LCP in approximating well known distance measures between pairs of Strings in (almost) linear time.
