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Relevant bibliographies by topics / Approximate string matching problem

Academic literature on the topic 'Approximate string matching problem'

Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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Journal articles on the topic "Approximate string matching problem"

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Liu, Bing, Dan Han, and Shuang Zhang. "Approximate Chinese String Matching Techniques Based on Pinyin Input Method." Applied Mechanics and Materials 513-517 (February 2014): 1017–20. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1017.

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String matching is one of the most typical problems in computer science. Previous studies mainly focused on accurate string matching problem. However, with the rapid development of the computer and Internet as well as the continuously rising of new issues, people find that it has very important theoretical value and practical meaning to research and design efficient approximate string matching algorithms. Approximate string matching is also called string matching that allows errors, which mainly aims to find the pattern string in the text and database and allows k differences between the pattern string and its occurring forms in the text. For the problem of approximate string matching, though a number of algorithms have been proposed, there are fewer studies which focus on large size of alphabet . Most of experts are interested in small or middle size of alphabet . For large size of , especially for Chinese characters and Asian phonetics, there are fewer efficient algorithms. For the above reasons, this paper focuses on the approximate Chinese strings matching problem based on the pinyin input method.

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BERGERON, ANNE, and SYLVIE HAMEL. "VECTOR ALGORITHMS FOR APPROXIMATE STRING MATCHING." International Journal of Foundations of Computer Science 13, no. 01 (February 2002): 53–65. http://dx.doi.org/10.1142/s0129054102000947.

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Vector algorithms allow the computation of an output vector r = r1 r2 ⋯ rm given an input vector e = e1 e2 ⋯ em in a bounded number of operations, independent of m the length of the vectors. The allowable operations are usually restricted to bit-wise operations available in processors, including shifts and binary addition with carry. These restrictions imple that the existence of a vector algorithm for a particular problem opens the way to extremely fast implementations, using the inherent parallelism of bit-wise operations. This paper presents general results on the existence and construction of vertor algorithms, with a particular focus on problems arising from computational biology. We show that efficient vector algorithms exist for the problem of approximate string matching with arbitrary weighted distances, generalizing a previous result by G. Myers. We also characterize a class of automata for which vector algorithms can be automatically derived from the transition table of the automata.

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Bertossi, A. A., F. Luccio, L. Pagli, and E. Lodi. "A Parallel Solution to the Approximate String Matching Problem." Computer Journal 35, no. 5 (October 1, 1992): 524–26. http://dx.doi.org/10.1093/comjnl/35.5.524.

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Yang, Zhenglu, Jianjun Yu, and Masaru Kitsuregawa. "Fast Algorithms for Top-k Approximate String Matching." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (July 5, 2010): 1467–73. http://dx.doi.org/10.1609/aaai.v24i1.7527.

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Top-k approximate querying on string collections is an important data analysis tool for many applications, and it has been exhaustively studied. However, the scale of the problem has increased dramatically because of the prevalence of the Web. In this paper, we aim to explore the efficient top-k similar string matching problem. Several efficient strategies are introduced, such as length aware and adaptive q-gram selection. We present a general q-gram based framework and propose two efficient algorithms based on the strategies introduced. Our techniques are experimentally evaluated on three real data sets and show a superior performance.

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Susik, Robert. "APPLYING A Q-GRAM BASED MULTIPLE STRING MATCHING ALGORITHM FOR APPROXIMATE MATCHING." Informatics Control Measurement in Economy and Environment Protection 7, no. 3 (September 30, 2017): 47–50. http://dx.doi.org/10.5604/01.3001.0010.5214.

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We consider the application of multiple pattern matching (Multi AOSO on q-Grams) algorithm for approximate pattern matching. We propose the on-line approach which translates the problem from approximate pattern matching into a multiple pattern one (called partitioning into exact search). Presented solution allows relatively fast search multiple patterns in text with given k-differences(or mismatches). This paper presents comparison of solution based on MAG algorithm, and [4]. Experiments on DNA, English, Proteins and XML texts with up to k errors show that the new proposed algorithm achieves relatively good results in practical use.

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Wang, J. F., Z. R. Li, C. Z. Cai, and Y. Z. Chen. "Assessment of approximate string matching in a biomedical text retrieval problem." Computers in Biology and Medicine 35, no. 8 (October 2005): 717–24. http://dx.doi.org/10.1016/j.compbiomed.2004.06.002.

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Sadeh, Ilan. "Universal Data Compression Algorithm Based on Approximate String Matching." Probability in the Engineering and Informational Sciences 10, no. 4 (October 1996): 465–86. http://dx.doi.org/10.1017/s0269964800004502.

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A practical source coding scheme based on approximate string matching is proposed. It is an approximate fixed-length string matching data compression combined with a block-coder based on the empirical distribution. A lemma on approximate string matching, which is an extension of the Kac Lemma, is proved. It is shown, based on the lemma, that the deterministic algorithm converts the stationary and ergodic source, u, into an output process v, and under the assumption that v is a stationary process, after the scheme has run for an infinite time, the optimal compression ratio R(D) is achieved. This reduces the problem of the universal lossy coder to the proof of stationarity of the output process ν in the proposed algorithm. The main advantages of the proposed method are the asymptotic sequential behavior of the encoder and the simplicity of the decoder.

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Ahmed, Pritom, A. S. M. Shohidull Islam, and M. Sohel Rahman. "A graph-theoretic model to solve the approximate string matching problem allowing for translocations." Journal of Discrete Algorithms 23 (November 2013): 143–56. http://dx.doi.org/10.1016/j.jda.2013.08.004.

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FREDRIKSSON, KIMMO, VELI MÄKINEN, and GONZALO NAVARRO. "FLEXIBLE MUSIC RETRIEVAL IN SUBLINEAR TIME." International Journal of Foundations of Computer Science 17, no. 06 (December 2006): 1345–64. http://dx.doi.org/10.1142/s0129054106004455.

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Music sequences can be treated as texts in order to perform music retrieval tasks on them. However, the text search problems that result from this modeling are unique to music retrieval. Up to date, several approaches derived from classical string matching have been proposed to cope with the new search problems, yet each problem had its own algorithms. In this paper we show that a technique recently developed for multipattern approximate string matching is flexible enough to be successfully extended to solve many different music retrieval problems, as well as combinations thereof not addressed before. We show that the resulting algorithms are average-optimal in many cases and close to average-optimal otherwise. Empirically, they are much better than existing approaches in many practical cases.

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ŠIMŮNEK, MARTIN, and BOŘIVOJ MELICHAR. "BORDERS AND FINITE AUTOMATA." International Journal of Foundations of Computer Science 18, no. 04 (August 2007): 859–71. http://dx.doi.org/10.1142/s0129054107005029.

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A border of a string is a prefix of the string that is simultaneously its suffix. It is one of the basic stringology keystones used as a part of many algorithms in pattern matching, molecular biology, computer-assisted music analysis and others. The paper offers the automata-theoretical description of Iliopoulos's ALL_BORDERS algorithm. The algorithm finds all borders of a string with don't care symbols. We show that ALL_BORDERS algorithm is an implementation of a finite state transducer of specific form. We describe how such a transducer can be constructed and what should be the input string like. The described transducer finds a set of lengths of all borders. Last but not least, we define approximate borders and show how to find all approximate borders of a string when we concern Hamming distance definition. Our solution of this problem is based on transducers again. This allows us to use analogy with automata-based pattern matching methods. Finally we discuss conditions under which the same principle can be used for other distance measures.

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Dissertations / Theses on the topic "Approximate string matching problem"

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Cheng, Lok-lam, and 鄭樂霖. "Approximate string matching in DNA sequences." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29350591.

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Nguyen, Hong-Thinh. "Approximate string matching distance for image classification." Thesis, Saint-Etienne, 2014. http://www.theses.fr/2014STET4029/document.

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L'augmentation exponentielle du nombre d'images nécessite des moyens efficaces pour les classer en fonction de leur contenu visuel. Le sac de mot visuel (Bag-Of-visual-Words, BOW), en raison de sa simplicité et de sa robustesse, devient l'approche la plus populaire. Malheureusement, cette approche ne prend pas en compte de l'information spatiale, ce qui joue un rôle important dans les catégories de modélisation d'image. Récemment, Lazebnik ont introduit la représentation pyramidale spatiale (Spatial Pyramid Representation, SPR) qui a incorporé avec succès l'information spatiale dans le modèle BOW. Néanmoins, ce système de correspondance rigide empêche la SPR de gérer les variations et les transformations d'image. L'objectif principal de cette thèse est d'étudier un modèle de chaîne de correspondance plus souple qui prend l'avantage d'histogrammes de BOW locaux et se rapproche de la correspondance de la chaîne. Notre première contribution est basée sur une représentation en chaîne et une nouvelle distance d'édition (String Matching Distance, SMD) bien adapté pour les chaînes de l'histogramme qui peut calculer efficacement par programmation dynamique. Un noyau d'édition correspondant comprenant à la fois d'une pondération et d'un système pyramidal est également dérivée. La seconde contribution est une version étendue de SMD qui remplace les opérations d'insertion et de suppression par les opérations de fusion entre les symboles successifs, ce qui apporte de la souplesse labours et correspond aux images. Toutes les distances proposées sont évaluées sur plusieurs jeux de données tâche de classification et sont comparés avec plusieurs approches concurrentes
The exponential increasing of the number of images requires efficient ways to classify them based on their visual content. The most successful and popular approach is the Bag of visual Word (BoW) representation due to its simplicity and robustness. Unfortunately, this approach fails to capture the spatial image layout, which plays an important roles in modeling image categories. Recently, Lazebnik et al (2006) introduced the Spatial Pyramid Representation (SPR) which successfully incorporated spatial information into the BoW model. The idea of their approach is to split the image into a pyramidal grid and to represent each grid cell as a BoW. Assuming that images belonging to the same class have similar spatial distributions, it is possible to use a pairwise matching as similarity measurement. However, this rigid matching scheme prevents SPR to cope with image variations and transformations. The main objective of this dissertation is to study a more flexible string matching model. Keeping the idea of local BoW histograms, we introduce a new class of edit distance to compare strings of local histograms. Our first contribution is a string based image representation model and a new edit distance (called SMD for String Matching Distance) well suited for strings composed of symbols which are local BoWs. The new distance benefits from an efficient Dynamic Programming algorithm. A corresponding edit kernel including both a weighting and a pyramidal scheme is also derived. The performance is evaluated on classification tasks and compared to the standard method and several related methods. The new method outperforms other methods thanks to its ability to detect and ignore identical successive regions inside images. Our second contribution is to propose an extended version of SMD replacing insertion and deletion operations by merging operations between successive symbols. In this approach, the number of sub regions ie. the grid divisions may vary according to the visual content. We describe two algorithms to compute this merge-based distance. The first one is a greedy version which is efficient but can produce a non optimal edit script. The other one is an optimal version but it requires a 4th degree polynomial complexity. All the proposed distances are evaluated on several datasets and are shown to outperform comparable existing methods

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Marco-Sola, Santiago. "Efficient approximate string matching techniques for sequence alignment." Doctoral thesis, Universitat Politècnica de Catalunya, 2017. http://hdl.handle.net/10803/460835.

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One of the outstanding milestones achieved in recent years in the field of biotechnology research has been the development of high-throughput sequencing (HTS). Due to the fact that at the moment it is technically impossible to decode the genome as a whole, HTS technologies read billions of relatively short chunks of a genome at random locations. Such reads then need to be located within a reference for the species being studied (that is aligned or mapped to the genome): for each read one identifies in the reference regions that share a large sequence similarity with it, therefore indicating what the read¿s point or points of origin may be. HTS technologies are able to re-sequence a human individual (i.e. to establish the differences between his/her individual genome and the reference genome for the human species) in a very short period of time. They have also paved the way for the development of a number of new protocols and methods, leading to novel insights in genomics and biology in general. However, HTS technologies also pose a challenge to traditional data analysis methods; this is due to the sheer amount of data to be processed and the need for improved alignment algorithms that can generate accurate results quickly. This thesis tackles the problem of sequence alignment as a step within the analysis of HTS data. Its contributions focus on both the methodological aspects and the algorithmic challenges towards efficient, scalable, and accurate HTS mapping. From a methodological standpoint, this thesis strives to establish a comprehensive framework able to assess the quality of HTS mapping results. In order to be able to do so one has to understand the source and nature of mapping conflicts, and explore the accuracy limits inherent in how sequence alignment is performed for current HTS technologies. From an algorithmic standpoint, this work introduces state-of-the-art index structures and approximate string matching algorithms. They contribute novel insights that can be used in practical applications towards efficient and accurate read mapping. More in detail, first we present methods able to reduce the storage space taken by indexes for genome-scale references, while still providing fast query access in order to support effective search algorithms. Second, we describe novel filtering techniques that vastly reduce the computational requirements of sequence mapping, but are nonetheless capable of giving strict algorithmic guarantees on the completeness of the results. Finally, this thesis presents new incremental algorithmic techniques able to combine several approximate string matching algorithms; this leads to efficient and flexible search algorithms allowing the user to reach arbitrary search depths. All algorithms and methodological contributions of this thesis have been implemented as components of a production aligner, the GEM-mapper, which is publicly available, widely used worldwide and cited by a sizeable body of literature. It offers flexible and accurate sequence mapping while outperforming other HTS mappers both as to running time and to the quality of the results it produces.
Uno de los avances más importantes de los últimos años en el campo de la biotecnología ha sido el desarrollo de las llamadas técnicas de secuenciación de alto rendimiento (high-throughput sequencing, HTS). Debido a las limitaciones técnicas para secuenciar un genoma, las técnicas de alto rendimiento secuencian individualmente billones de pequeñas partes del genoma provenientes de regiones aleatorias. Posteriormente, estas pequeñas secuencias han de ser localizadas en el genoma de referencia del organismo en cuestión. Este proceso se denomina alineamiento - o mapeado - y consiste en identificar aquellas regiones del genoma de referencia que comparten una alta similaridad con las lecturas producidas por el secuenciador. De esta manera, en cuestión de horas, la secuenciación de alto rendimiento puede secuenciar un individuo y establecer las diferencias de este con el resto de la especie. En última instancia, estas tecnologías han potenciado nuevos protocolos y metodologías de investigación con un profundo impacto en el campo de la genómica, la medicina y la biología en general. La secuenciación alto rendimiento, sin embargo, supone un reto para los procesos tradicionales de análisis de datos. Debido a la elevada cantidad de datos a analizar, se necesitan nuevas y mejoradas técnicas algorítmicas que puedan escalar con el volumen de datos y producir resultados precisos. Esta tesis aborda dicho problema. Las contribuciones que en ella se realizan se enfocan desde una perspectiva metodológica y otra algorítmica que propone el desarrollo de nuevos algoritmos y técnicas que permitan alinear secuencias de manera eficiente, precisa y escalable. Desde el punto de vista metodológico, esta tesis analiza y propone un marco de referencia para evaluar la calidad de los resultados del alineamiento de secuencias. Para ello, se analiza el origen de los conflictos durante la alineación de secuencias y se exploran los límites alcanzables en calidad con las tecnologías de secuenciación de alto rendimiento. Desde el punto de vista algorítmico, en el contexto de la búsqueda aproximada de patrones, esta tesis propone nuevas técnicas algorítmicas y de diseño de índices con el objetivo de mejorar la calidad y el desempeño de las herramientas dedicadas a alinear secuencias. En concreto, esta tesis presenta técnicas de diseño de índices genómicos enfocados a obtener un acceso más eficiente y escalable. También se presentan nuevas técnicas algorítmicas de filtrado con el fin de reducir el tiempo de ejecución necesario para alinear secuencias. Y, por último, se proponen algoritmos incrementales y técnicas híbridas para combinar métodos de alineamiento y mejorar el rendimiento en búsquedas donde el error esperado es alto. Todo ello sin degradar la calidad de los resultados y con garantías formales de precisión. Para concluir, es preciso apuntar que todos los algoritmos y metodologías propuestos en esta tesis están implementados y forman parte del alineador GEM. Este versátil alineador ofrece resultados de alta calidad en entornos de producción siendo varias veces más rápido que otros alineadores. En la actualidad este software se ofrece gratuitamente, tiene una amplia comunidad de usuarios y ha sido citado en numerosas publicaciones científicas.

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Mäkinen, Veli. "Parameterized approximate string matching and local-similarity-based point-pattern matching." Helsinki : University of Helsinki, 2003. http://ethesis.helsinki.fi/julkaisut/mat/tieto/vk/makinen/.

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Siragusa, Enrico [Verfasser]. "Approximate string matching for high-throughput sequencing / Enrico Siragusa." Berlin : Freie Universität Berlin, 2015. http://d-nb.info/1074404882/34.

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Keng, Leng Hui. "Approximate String Matching With Dynamic Programming and Suffix Trees." UNF Digital Commons, 2006. http://digitalcommons.unf.edu/etd/196.

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The importance and the contribution of string matching algorithms to the modern society cannot be overstated. From basic search algorithms such as spell checking and data querying, to advanced algorithms such as DNA sequencing, trend analysis and signal processing, string matching algorithms form the foundation of many aspects in computing that have been pivotal in technological advancement. In general, string matching algorithms can be divided into the categories of exact string matching and approximate string matching. We study each area and examine some of the well known algorithms. We probe into one of the most intriguing data structure in string algorithms, the suffix tree. The lowest common ancestor extension of the suffix tree is the key to many advanced string matching algorithms. With these tools, we are able to solve string problems that were, until recently, thought intractable by many. Another interesting and relatively new data structure in string algorithms is the suffix array, which has significant breakthroughs in its linear time construction in recent years. Primarily, this thesis focuses on approximate string matching using dynamic programming and hybrid dynamic programming with suffix tree. We study both approaches in detail and see how the merger of exact string matching and approximate string matching algorithms can yield synergistic results in our experiments.

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Smith, David. "Parallel approximate string matching applied to occluded object recognition." PDXScholar, 1987. https://pdxscholar.library.pdx.edu/open_access_etds/3724.

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This thesis develops an algorithm for approximate string matching and applies it to the problem of partially occluded object recognition. The algorithm measures the similarity of differing strings by scanning for matching substrings between strings. The length and number of matching substrings determines the amount of similarity. A classification algorithm is developed using the approximate string matching algorithm for the identification and classification of objects. A previously developed method of shape description is used for object representation.

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Dubois, Simon. "Offline Approximate String Matching forInformation Retrieval : An experiment on technical documentation." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH. Forskningsmiljö Informationsteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-22566.

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Approximate string matching consists in identifying strings as similar even ifthere is a number of mismatch between them. This technique is one of thesolutions to reduce the exact matching strictness in data comparison. In manycases it is useful to identify stream variation (e.g. audio) or word declension (e.g.prefix, suffix, plural). Approximate string matching can be used to score terms in InformationRetrieval (IR) systems. The benefit is to return results even if query terms doesnot exactly match indexed terms. However, as approximate string matchingalgorithms only consider characters (nor context neither meaning), there is noguarantee that additional matches are relevant matches. This paper presents the effects of some approximate string matchingalgorithms on search results in IR systems. An experimental research design hasbeen conducting to evaluate such effects from two perspectives. First, resultrelevance is analysed with precision and recall. Second, performance is measuredthanks to the execution time required to compute matches. Six approximate string matching algorithms are studied. Levenshtein andDamerau-Levenshtein computes edit distance between two terms. Soundex andMetaphone index terms based on their pronunciation. Jaccard similarity calculatesthe overlap coefficient between two strings. Tests are performed through IR scenarios regarding to different context,information need and search query designed to query on a technicaldocumentation related to software development (man pages from Ubuntu). Apurposive sample is selected to assess document relevance to IR scenarios andcompute IR metrics (precision, recall, F-Measure). Experiments reveal that all tested approximate matching methods increaserecall on average, but, except Metaphone, they also decrease precision. Soundexand Jaccard Similarity are not advised because they fail on too many IR scenarios.Highest recall is obtained by edit distance algorithms that are also the most timeconsuming. Because Levenshtein-Damerau has no significant improvementcompared to Levenshtein but costs much more time, the last one is recommendedfor use with a specialised documentation. Finally some other related recommendations are given to practitioners toimplement IR systems on technical documentation.

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Pockrandt, Christopher Maximilian [Verfasser]. "Approximate String Matching : Improving Data Structures and Algorithms / Christopher Maximilian Pockrandt." Berlin : Freie Universität Berlin, 2019. http://d-nb.info/1183675879/34.

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Richter, Christoph Jan [Verfasser]. "Über die Vermeidung redundanter Betrachtungen beim Approximate String Matching / Christoph Jan Richter." Dortmund : Universitätsbibliothek Technische Universität Dortmund, 2005. http://d-nb.info/1011533499/34.

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Books on the topic "Approximate string matching problem"

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Landau, Gad M. Efficient parallel and serial approximate string matching. New York: Courant Institute of Mathematical Sciences, New York University, 1986.

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Vishkin, U., and Gad M. Landau. Efficient Parallel and Serial Approximate String Matching. Creative Media Partners, LLC, 2018.

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Book chapters on the topic "Approximate string matching problem"

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Ahmed, Pritom, A. S. M. Shohidull Islam, and M. Sohel Rahman. "A Graph Theoretic Model to Solve the Approximate String Matching Problem Allowing for Translocations." In Lecture Notes in Computer Science, 169–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35926-2_20.

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Navarro, Gonzalo. "Approximate String Matching." In Encyclopedia of Algorithms, 102–6. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-2864-4_363.

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Navarro, Gonzalo. "Approximate String Matching." In Encyclopedia of Algorithms, 1–5. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-3-642-27848-8_363-2.

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Muth, Robert, and Udi Manber. "Approximate multiple string search." In Combinatorial Pattern Matching, 75–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61258-0_7.

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Baeza-Yates, Ricardo, and Gonzalo Navarro. "Multiple approximate string matching." In Lecture Notes in Computer Science, 174–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63307-3_57.

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Sung, Wing-Kin. "Indexed Approximate String Matching." In Encyclopedia of Algorithms, 964–68. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-2864-4_188.

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Sung, Wing-Kin. "Indexed Approximate String Matching." In Encyclopedia of Algorithms, 1–6. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-3-642-27848-8_188-2.

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Sung, Wing-Kin. "Indexed Approximate String Matching." In Encyclopedia of Algorithms, 408–11. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_188.

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Navarro, Gonzalo. "Sequential Approximate String Matching." In Encyclopedia of Algorithms, 818–20. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_363.

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Russo, Luís M. S., Gonzalo Navarro, and Arlindo L. Oliveira. "Indexed Hierarchical Approximate String Matching." In String Processing and Information Retrieval, 144–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89097-3_15.

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Conference papers on the topic "Approximate string matching problem"

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Katsumata, Akifumi, and Takao Miura. "Spatial Approximate String Matching." In 2009 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PacRim). IEEE, 2009. http://dx.doi.org/10.1109/pacrim.2009.5291387.

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"Approximate String Matching Techniques." In 16th International Conference on Enterprise Information Systems. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004892802170224.

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Katsumata, A., T. Miura, and I. Shioya. "Approximate String Matching Using Markovian Distance." In Third International Symposium on Parallel Architectures, Algorithms and Programming (PAAP 2010). IEEE, 2010. http://dx.doi.org/10.1109/paap.2010.11.

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Korotkov, Alexander. "Database Index for Approximate String Matching." In Spring/Summer Young Researchers' Colloquium on Software Engineering. Institute for System Programming of the Russian Academy of Sciences, 2010. http://dx.doi.org/10.15514/syrcose-2010-4-27.

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Alba, A., M. Rodriguez-Kessler, E. R. Arce-Santana, and M. O. Mendez. "Approximate string matching using phase correlation." In 2012 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2012. http://dx.doi.org/10.1109/embc.2012.6347436.

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Hrbek, Lukas, and Jan Holub. "Approximate String Matching for Self-Indexes." In 2016 Data Compression Conference (DCC). IEEE, 2016. http://dx.doi.org/10.1109/dcc.2016.25.

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Lok-Lam Cheng, D. W. Cheung, and Siu-Ming Yiu. "Approximate string matching in DNA sequences." In Proceedings Eighth International Conference on Database Systems for Advanced Applications (DASFAA 2003). IEEE, 2003. http://dx.doi.org/10.1109/dasfaa.2003.1192395.

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Abraham, Dona, and Nisha S. Raj. "Approximate string matching algorithm for phishing detection." In 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2014. http://dx.doi.org/10.1109/icacci.2014.6968578.

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Patil, Manish, Xuanting Cai, Sharma V. Thankachan, Rahul Shah, Seung-Jong Park, and David Foltz. "Approximate string matching by position restricted alignment." In the Joint EDBT/ICDT 2013 Workshops. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2457317.2457388.

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Montgomery, Justin B., and Francis M. O'Sullivan. "Measuring Drilling Standardization Using Approximate String Matching." In SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, 2014. http://dx.doi.org/10.2118/170820-ms.

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Reports on the topic "Approximate string matching problem"

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Smith, David. Parallel approximate string matching applied to occluded object recognition. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.5608.

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