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Text Retrieval: Theory and Practice
 In 12th IFIP World Computer Congress, volume I
, 1992
"... We present the state of the art of the main component of text retrieval systems: the searching engine. We outline the main lines of research and issues involved. We survey recently published results for text searching and we explore the gap between theoretical vs. practical algorithms. The main obse ..."
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Cited by 46 (14 self)
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We present the state of the art of the main component of text retrieval systems: the searching engine. We outline the main lines of research and issues involved. We survey recently published results for text searching and we explore the gap between theoretical vs. practical algorithms. The main observation is that simpler ideas are better in practice. 1597 Shaks. Lover's Compl. 2 From off a hill whose concaue wombe reworded A plaintfull story from a sistring vale. OED2, reword, sistering 1 1 Introduction Full text retrieval systems are becoming a popular way of providing support for online text. Their main advantage is that they avoid the complicated and expensive process of semantic indexing. From the enduser point of view, full text searching of online documents is appealing because a valid query is just any word or sentence of the document. However, when the desired answer cannot be obtained with a simple query, the user must perform his/her own semantic processing to guess w...
Fast String Correction with LevenshteinAutomata
 INTERNATIONAL JOURNAL OF DOCUMENT ANALYSIS AND RECOGNITION
, 2002
"... The Levenshteindistance between two words is the minimal number of insertions, deletions or substitutions that are needed to transform one word into the other. Levenshteinautomata of degree n for a word W are defined as finite state automata that regognize the set of all words V where the Levensht ..."
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Cited by 28 (5 self)
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The Levenshteindistance between two words is the minimal number of insertions, deletions or substitutions that are needed to transform one word into the other. Levenshteinautomata of degree n for a word W are defined as finite state automata that regognize the set of all words V where the Levenshteindistance between V and W does not exceed n. We show how to compute, for any fixed bound n and any input word W , a deterministic Levenshteinautomaton of degree n for W in time linear in the length of W . Given an electronic dictionary that is implemented in the form of a trie or a finite state automaton, the Levenshteinautomaton for W can be used to control search in the lexicon in such a way that exactly the lexical words V are generated where the Levenshteindistance between V and W does not exceed the given bound. This leads to a very fast method for correcting corrupted input words of unrestricted text using large electronic dictionaries. We then introduce a second method that avoids the explicit computation of Levenshteinautomata and leads to even improved eciency. We also describe how to extend both methods to variants of the Levenshteindistance where further primitive edit operations (transpositions, merges and splits) may be used.
Two Approaches to Handling Noisy Variation in Text Mining
 In Papers from the Nineteenth International Conference on Machine Learning (ICML2002) Workshop on Text Learning
, 2002
"... Variation and noise in textual database entries can prevent text mining algorithms from discovering important regularities. We present two novel methods to cope with this problem: (1) an adaptive approach to "hardening" noisy databases by identifying duplicate records, and (2) mining "soft" associat ..."
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Cited by 24 (2 self)
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Variation and noise in textual database entries can prevent text mining algorithms from discovering important regularities. We present two novel methods to cope with this problem: (1) an adaptive approach to "hardening" noisy databases by identifying duplicate records, and (2) mining "soft" association rules. For identifying approximately duplicate records, we present a domainindependent twolevel method for improving duplicate detection accuracy based on machine learning. For mining soft matching rules, we introduce an algorithm that discovers association rules by allowing partial matching of items based on a textual similarity metric such as edit distance or cosine similarity. Experimental results on real and synthetic datasets show that our methods outperform traditional techniques for noisy textual databases.
Fast Approximate Search in Large Dictionaries
 COMPUTATIONAL LINGUISTICS
, 2004
"... The need to correct garbled strings arises in many areas of natural language processing. If a dictionary is available that covers all possible input tokens, a natural set of candidates for correcting an erroneous input P is the set of all words in the dictionary for which the Levenshtein distance to ..."
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Cited by 14 (4 self)
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The need to correct garbled strings arises in many areas of natural language processing. If a dictionary is available that covers all possible input tokens, a natural set of candidates for correcting an erroneous input P is the set of all words in the dictionary for which the Levenshtein distance to P does not exceed a given (small) bound k. In this article we describe methods for efficiently selecting such candidate sets. After introducing as a starting point a basic correction method based on the concept of a "universal Levenshtein automaton," we show how two filtering methods known from the field of approximate text search can be used to improve the basic procedure in a significant way. The first method, which uses standard dictionaries plus dictionaries with reversed words, leads to very short correction times for most classes of input strings. Our evaluation results demonstrate that correction times for fixeddistance bounds depend on the expected number of correction candidates, which decreases for longer input words. Similarly the choice of an optimal filtering method depends on the length of the input words.
Comparison of Exact String Matching Algorithms for Biological Sequences ⋆
"... Abstract. Exact matching of single patterns in DNA and amino acid sequences is studied. We performed an extensive experimental comparison of algorithms presented in the literature. In addition, we introduce new variations of earlier algorithms. The results of the comparison show that the new algorit ..."
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Cited by 3 (1 self)
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Abstract. Exact matching of single patterns in DNA and amino acid sequences is studied. We performed an extensive experimental comparison of algorithms presented in the literature. In addition, we introduce new variations of earlier algorithms. The results of the comparison show that the new algorithms are efficient in practice. 1
Text Searching: Theory and Practice
"... We present the state of the art of the main component of text retrieval systems: the search engine. We outline the main lines of research and issues involved. We survey the relevant techniques in use today for text searching and explore the gap between theoretical and practical algorithms. The main ..."
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Cited by 1 (0 self)
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We present the state of the art of the main component of text retrieval systems: the search engine. We outline the main lines of research and issues involved. We survey the relevant techniques in use today for text searching and explore the gap between theoretical and practical algorithms. The main observation is that simpler ideas are better in practice.