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409
SimilarityBased Queries for Time Series Data
 Proc. 1997 ACMSIGMOD Conf
, 1997
"... We study a set of linear transformations on the Fourier series representation of a sequence that can be used as the basis for similarity queries on timeseries data. We show that our set of transformations is rich enough to formulate operations such as moving average and time warping. We present a q ..."
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Cited by 136 (7 self)
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We study a set of linear transformations on the Fourier series representation of a sequence that can be used as the basis for similarity queries on timeseries data. We show that our set of transformations is rich enough to formulate operations such as moving average and time warping. We present a query processing algorithm that uses the underlying Rtree index of a multidimensional data set to answer similarity queries efficiently. Our experiments show that the performance of this algorithm is competitive to that of processing ordinary (exact match) queries using the index, and much faster than sequential scanning. We relate our transformations to the general framework for similarity queries of Jagadish et al. 1
A Probabilistic Framework for Matching Temporal Trajectories: CondensationBased . . .
, 1998
"... The recognition of human gestures and facial expressions in image sequences is an important and challenging problem that enables a host of humancomputer interaction applications. This paper describes a framework for incremental recognition of human motion that extends the "Condensation&quo ..."
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Cited by 108 (4 self)
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The recognition of human gestures and facial expressions in image sequences is an important and challenging problem that enables a host of humancomputer interaction applications. This paper describes a framework for incremental recognition of human motion that extends the "Condensation" algorithm proposed by Isard and Blake (ECCV'96). Humnan motions are
Word Image Matching Using Dynamic Time Warping
, 2002
"... Libraries and other institutions are interested in providing access to scanned versions of their large collections of handwritten historical manuscripts on electronic media. Convenient access to a collection requires an index, which is manually created at great labour and expense. Since current hand ..."
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Cited by 100 (13 self)
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Libraries and other institutions are interested in providing access to scanned versions of their large collections of handwritten historical manuscripts on electronic media. Convenient access to a collection requires an index, which is manually created at great labour and expense. Since current handwriting recognizers do not perform well on historical documents, a technique called word spotting has been developed: clusters with occurrences of the same word in a collection are established using image matching. By annotating "interesting" clusters, an index can be built automatically. We present an algorithm for matching handwritten words in noisy historical documents. The segmented word images are preprocessed to create sets of 1dimensional features, which are then compared using dynamic time warping. We present experimental results on two different data sets from the George Washington collection. Our experiments show that this algorithm performs better and is faster than competing matching techniques.
Creating HighLevel Components with a Generative Representation for BodyBrain Evolution
, 2002
"... One of the main limitations of scalability in bodybrain evolution systems is the representation chosen for encoding creatures. This paper defines a class of representations called generative representations, which are identified by their ability to reuse elements of the genotype in the translatio ..."
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Cited by 96 (19 self)
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One of the main limitations of scalability in bodybrain evolution systems is the representation chosen for encoding creatures. This paper defines a class of representations called generative representations, which are identified by their ability to reuse elements of the genotype in the translation to the phenotype. This paper presents an example of a generative representation for the concurrent evolution of the morphology and neural controller of simulated robots, and also introduces GENRE, an evolutionary system for evolving designs using this representation. Applying GENRE to the task of evolving robots for locomotion and comparing it against a nongenerative (direct) representation shows that the generative representation system rapidly produces robots with significantly greater fitness. Analyzing these results shows
Finding Similar Time Series
 In Proceedings of the Conference on Principles of Knowledge Discovery and Data Mining
, 1997
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Structure Comparison and Structure Patterns
 JOURNAL OF COMPUTATIONAL BIOLOGY
, 1999
"... This article investigate different aspects regarding pairwise and multiple structure comparison, and the problem of automatically discover common patterns in a set of structures. Descriptions and representation of structures and patterns are investigated, as well as scoring and algorithms for com ..."
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Cited by 83 (2 self)
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This article investigate different aspects regarding pairwise and multiple structure comparison, and the problem of automatically discover common patterns in a set of structures. Descriptions and representation of structures and patterns are investigated, as well as scoring and algorithms for comparison and discovery. A framework and nomenclature is developed, and a lot of methods are reviewed and placed into this framework.
Dzung T: Searching Genetic Databases on SPLASH 2
 In Proc. Workshop on FPGAs for Custom Computing Machines
, 1993
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On the Learnability and Usage of Acyclic Probabilistic Finite Automata
 JOURNAL OF COMPUTER AND SYSTEM SCIENCES
, 1995
"... We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishability property of the automata's states. Though hardness results are known for learning distributions generated by ge ..."
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Cited by 71 (3 self)
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We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishability property of the automata's states. Though hardness results are known for learning distributions generated by general APFAs, we prove that our algorithm can efficiently learn distributions generated by the subclass of APFAs we consider. In particular, we show that the KLdivergence between the distribution generated by the target source and the distribution generated by our hypothesis can be made arbitrarily small with high confidence in polynomial time. We present two applications of our algorithm. In the first, we show how to model cursively written letters. The resulting models are part of a complete cursive handwriting recognition system. In the second application we demonstrate how APFAs can be used to build multiplepronunciation models for spoken words. We evaluate the APFA based pronunciation models...
The String Edit Distance Matching Problems with Moves
, 2006
"... The edit distance between two strings S and R is defined to be the minimum number of character inserts, deletes and changes needed to convert R to S. Given a text string t of length n, and a pattern string p of length m, informally, the string edit distance matching problem is to compute the smalles ..."
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Cited by 60 (3 self)
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The edit distance between two strings S and R is defined to be the minimum number of character inserts, deletes and changes needed to convert R to S. Given a text string t of length n, and a pattern string p of length m, informally, the string edit distance matching problem is to compute the smallest edit distance between p and substrings of t. We relax the problem so that (a) we allow an additional operation, namely, substring moves, and (b) we allow approximation of this string edit distance. Our result is a near linear time deterministic algorithm to produce a factor of O(log n log ∗ n) approximation to the string edit distance with moves. This is the first known significantly subquadratic algorithm for a string edit distance problem in which the distance involves nontrivial alignments. Our results are obtained by embedding strings into L1 vector space using a simplified parsing technique we call Edit