Journal ArticleDOI
A guided tour to approximate string matching
TLDR
This work surveys the current techniques to cope with the problem of string matching that allows errors, and focuses on online searching and mostly on edit distance, explaining the problem and its relevance, its statistical behavior, its history and current developments, and the central ideas of the algorithms.Abstract:
We survey the current techniques to cope with the problem of string matching that allows errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining the problem and its relevance, its statistical behavior, its history and current developments, and the central ideas of the algorithms and their complexities. We present a number of experiments to compare the performance of the different algorithms and show which are the best choices. We conclude with some directions for future work and open problems.read more
Citations
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Supervised Sequence Labelling with Recurrent Neural Networks
TL;DR: A new type of output layer that allows recurrent networks to be trained directly for sequence labelling tasks where the alignment between the inputs and the labels is unknown, and an extension of the long short-term memory network architecture to multidimensional data, such as images and video sequences.
Journal ArticleDOI
Duplicate Record Detection: A Survey
Elmagarmid,Ipeirotis,Verykios +2 more
TL;DR: This paper presents an extensive set of duplicate detection algorithms that can detect approximately duplicate records in a database and covers similarity metrics that are commonly used to detect similar field entries.
Journal ArticleDOI
Duplicate Record Detection: A Survey
TL;DR: This paper presents an extensive set of duplicate detection algorithms that can detect approximately duplicate records in a database and covers similarity metrics that are commonly used to detect similar field entries.
Journal ArticleDOI
Efficient query evaluation on probabilistic databases
Nilesh Dalvi,Dan Suciu +1 more
TL;DR: It is shown that the data complexity of some queries is #P-complete, which implies that these queries do not admit any efficient evaluation methods, and an optimization algorithm is described that can compute efficiently most queries.
References
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Journal ArticleDOI
Basic Local Alignment Search Tool
TL;DR: A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score.
Book
Introduction to Algorithms
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Book
Introduction to Automata Theory, Languages, and Computation
TL;DR: This book is a rigorous exposition of formal languages and models of computation, with an introduction to computational complexity, appropriate for upper-level computer science undergraduates who are comfortable with mathematical arguments.
Journal ArticleDOI
A general method applicable to the search for similarities in the amino acid sequence of two proteins
TL;DR: A computer adaptable method for finding similarities in the amino acid sequences of two proteins has been developed and it is possible to determine whether significant homology exists between the proteins to trace their possible evolutionary development.
Book
Modern Information Retrieval
TL;DR: In this article, the authors present a rigorous and complete textbook for a first course on information retrieval from the computer science (as opposed to a user-centred) perspective, which provides an up-to-date student oriented treatment of the subject.