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Relevant bibliographies by topics / Edit search

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Academic literature on the topic 'Edit search'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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Journal articles on the topic "Edit search"

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Boria, Nicolas, David B. Blumenthal, Sébastien Bougleux, and Luc Brun. "Improved local search for graph edit distance." Pattern Recognition Letters 129 (January 2020): 19–25. http://dx.doi.org/10.1016/j.patrec.2019.10.028.

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Rachkovskij, D. A. "Fast Similarity Search for Graphs by Edit Distance." Cybernetics and Systems Analysis 55, no. 6 (2019): 1039–51. http://dx.doi.org/10.1007/s10559-019-00213-9.

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Belazzougui, Djamal, and Rossano Venturini. "Compressed String Dictionary Search with Edit Distance One." Algorithmica 74, no. 3 (2015): 1099–122. http://dx.doi.org/10.1007/s00453-015-9990-0.

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Bringer, Julien, and Hervé Chabanne. "Embedding edit distance to enable private keyword search." Human-centric Computing and Information Sciences 2, no. 1 (2012): 2. http://dx.doi.org/10.1186/preaccept-1253053215890607.

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Yamada, Masataka, and Akihiro Inokuchi. "Similar Supergraph Search Based on Graph Edit Distance." Algorithms 14, no. 8 (2021): 225. http://dx.doi.org/10.3390/a14080225.

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Subgraph and supergraph search methods are promising techniques for the development of new drugs. For example, the chemical structure of favipiravir—an antiviral treatment for influenza—resembles the structure of some components of RNA. Represented as graphs, such compounds are similar to a subgraph of favipiravir. However, the existing supergraph search methods can only discover compounds that match exactly. We propose a novel problem, called similar supergraph search, and design an efficient algorithm to solve it. The problem is to identify all graphs in a database that are similar to any subgraph of a query graph, where similarity is defined as edit distance. Our algorithm represents the set of candidate subgraphs by a code tree, which it uses to efficiently compute edit distance. With a distance threshold of zero, our algorithm is equivalent to an existing efficient algorithm for exact supergraph search. Our experiments show that the computation time increased exponentially as the distance threshold increased, but increased sublinearly with the number of graphs in the database.

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Riesen, Kaspar, and Horst Bunke. "Improving bipartite graph edit distance approximation using various search strategies." Pattern Recognition 48, no. 4 (2015): 1349–63. http://dx.doi.org/10.1016/j.patcog.2014.11.002.

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Gouda, Karam, and Mona Arafa. "An improved global lower bound for graph edit similarity search." Pattern Recognition Letters 58 (June 2015): 8–14. http://dx.doi.org/10.1016/j.patrec.2015.02.004.

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PATHAK, SUDIPTA, SANGUTHEVAR RAJASEKARAN, and MARIUS NICOLAE. "EMS1: AN ELEGANT ALGORITHM FOR EDIT DISTANCE BASED MOTIF SEARCH." International Journal of Foundations of Computer Science 24, no. 04 (2013): 473–86. http://dx.doi.org/10.1142/s0129054113500159.

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Motifs are biologically significant patterns found in DNA/protein sequences. Given a set of biological sequences, the problem of identifying the motifs is very challenging. This problem has been well studied in computational biology. Identifying motifs through experimental processes is extremely expensive and time consuming. This is one of the factors influencing computational biologists to come up with novel computational methods to predict motifs. Several motif models have been proposed in the literature and for each model numerous algorithms have been devised. Three popular motif models are (l, d)-motif search or Planted Motif Search (PMS), Simple Motif Search (SMS), and Edit-distance based Motif Search (EMS). For PMS and SMS several algorithms have been proposed and implemented. On the other hand, even though some algorithms exist in the literature for the problem of EMS, no implementations of these algorithms are known. This is mainly because the proposed algorithms are complex. In this paper we present an elegant algorithm for EMS. We have implemented this algorithm and compared it against 14 other algorithms in terms of sensitivity and specificity. Our experimental results indicate that the new algorithm is very competitive in practice.

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Yu, Minghe, Jin Wang, Guoliang Li, Yong Zhang, Dong Deng, and Jianhua Feng. "A unified framework for string similarity search with edit-distance constraint." VLDB Journal 26, no. 2 (2016): 249–74. http://dx.doi.org/10.1007/s00778-016-0449-y.

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Lu, Wei, Xiaoyong Du, Marios Hadjieleftheriou, and Beng Chin Ooi. "Efficiently Supporting Edit Distance Based String Similarity Search Using B $^+$-Trees." IEEE Transactions on Knowledge and Data Engineering 26, no. 12 (2014): 2983–96. http://dx.doi.org/10.1109/tkde.2014.2309131.

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Dissertations / Theses on the topic "Edit search"

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Samuelsson, Axel. "Weighting Edit Distance to Improve Spelling Correction in Music Entity Search." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210036.

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This master’s thesis project undertook investigation of whether the extant Damerau- Levenshtein edit distance measurement between two strings could be made more useful for detecting and adjusting misspellings in a search query. The idea was to use the knowledge that many users type their queries using the QWERTY keyboard layout, and weighting the edit distance in a manner that makes it cheaper to correct misspellings caused by confusion of nearer keys. Two different weighting approaches were tested, one with a linear spread from 2/9 to 2 depending on the keyboard distance, and the other had neighbors preferred over non-neighbors (either with half the cost or no cost at all). They were tested against an unweighted baseline as well as inverted versions of themselves (nearer keys more expensive to replace) against a dataset of 1,162,145 searches. No significant improvement in the retrieval of search results were observed when compared to the baseline. However, each of the weightings performed better than its corresponding inversion on a p < 0.05 significance level. This means that while the weighted edit distance did not outperform the baseline, the data still clearly points toward a correlation between the physical position of keys on the keyboard, and what spelling mistakes are made.<br>Detta examensarbete åtog sig att undersöka om det etablerade Damerau-Levenshtein-avståndet som mäter avståndet kan anpassas för att bättre hitta och korrigera stavningsfel i sökfrågor. Tanken var att använda det faktum att många användare skriver sina sökfrågor på ett tangentbord med QWERTY-layout, och att vikta ändrings- avståndet så att det blir billigare att korrigera stavfel orsakade av hopblandning av två knappar som är närmare varandra. Två olika viktningar testades, en hade vikterna utspridda linjärt mellan 2/9 och 2, och den andra föredrog grannar över icke-grannar (antingen halva kostnaden eller ingen alls). De testades mot ett oviktat referensavstånd samt inversen av sig själva (så att närmare knappar blev dyrare att byta ut) mot ett dataset bestående av 1 162 145 sökningar. Ingen signifikant förbättring uppmättes gentemot referensen. Däremot presterade var och en av viktningarna bättre än sin inverterade motpart på konfidensnivå p < 0,05. Det innebär att trots att de viktade distansavstånden inte presterade bättre än referensen så pekar datan tydligt mot en korrelation mellan den fysiska positioneringen av knapparna på tangentbordet och vilka stavningsmisstag som begås.

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Darwiche, Mostafa. "When operations research meets structural pattern recognition : on the solution of error-tolerant graph matching problems." Thesis, Tours, 2018. http://www.theses.fr/2018TOUR4022/document.

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Cette thèse se situe à l’intersection de deux domaines de recherche scientifique la Reconnaissance d’Objets Structurels (ROS) et la Recherche Opérationnelle (RO). Le premier consiste à rendre la machine plus intelligente et à reconnaître les objets, en particulier ceux basés sur les graphes. Alors que le second se focalise sur la résolution de problèmes d’optimisation combinatoire difficiles. L’idée principale de cette thèse est de combiner les connaissances de ces deux domaines. Parmi les problèmes difficiles existants en ROS, le problème de la distance d’édition entre graphes (DEG) a été sélectionné comme le cœur de ce travail. Les contributions portent sur la conception de méthodes adoptées du domaine RO pour la résolution du problème de DEG. Explicitement, des nouveaux modèles linéaires en nombre entiers et des matheuristiques ont été développé à cet effet et de très bons résultats ont été obtenus par rapport à des approches existantes<br>This thesis is focused on Graph Matching (GM) problems and in particular the Graph Edit Distance (GED) problems. There is a growing interest in these problems due to their numerous applications in different research domains, e.g. biology, chemistry, computer vision, etc. However, these problems are known to be complex and hard to solve, as the GED is a NP-hard problem. The main objectives sought in this thesis, are to develop methods for solving GED problems to optimality and/or heuristically. Operations Research (OR) field offers a wide range of exact and heuristic algorithms that have accomplished very good results when solving optimization problems. So, basically all the contributions presented in thesis are methods inspired from OR field. The exact methods are designed based on deep analysis and understanding of the problem, and are presented as Mixed Integer Linear Program (MILP) formulations. The proposed heuristic approaches are adapted versions of existing MILP-based heuristics (also known as matheuristics), by considering problem-dependent information to improve their performances and accuracy

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Harris, Elizabeth. "'The earth-haunted mind' : the search for reconnection with nature, place and the environment in the poetry of Edward Thomas, T.S. Eliot, Edith Sitwell and Charlotte Mew." Thesis, Manchester Metropolitan University, 2013. http://e-space.mmu.ac.uk/315672/.

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This thesis examines the relationship between modernist poetry and nature, place and the environment. Challenging reductive notions of modernism as predominantly anthropocentric in character and urban in focus, it argues that within British modernist poetry there is a clear and sustained interest in the natural world and environmental issues. The poets studied in this thesis were writing during a period of significant changes in human/nature relations following the disruptive experience of war and modernity. This thesis considers how each poet responds to these changes and examines the various poetic techniques and approaches employed in order to achieve physical, psychological and artistic reconnection with the non-human world. An ecocritical approach is used to show the importance of nature in the work of Edward Thomas, T. S. Eliot, Edith Sitwell and Charlotte Mew. This approach focuses on the poetic treatment of nature and involves: examining representations of non-human life in both rural and urban environments, identifying the poetic techniques and approaches used to modernise poetic descriptions of the natural world, and charting the growth of an environmental consciousness in each poet. This thesis reveals the importance of nature, place and the environment to British modernist poetry and in doing so contributes to knowledge of an under-examined aspect of the movement. It shows the ability of ecocriticism to provide valuable insights into areas of literature not immediately associated with environmental issues and produces original readings of each poet’s work.

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Meng, Na. "Automating program transformations based on examples of systematic edits." Thesis, 2014. http://hdl.handle.net/2152/28059.

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Programmers make systematic edits—similar, but not identical changes to multiple places during software development and maintenance in order to add features and fix bugs. Finding all the correct locations and making the ed- its correctly is a tedious and error-prone process. Existing tools for automating systematic edits are limited because they do not create general purpose edit scripts or suggest edit locations, except for specialized or trivial edits. Since many similar changes occur in similar contexts (in code with similar surrounding dependent relations and syntactic structures), there is an opportunity to automate program transformations based on examples of systematic edits. By inferring systematic edits and relevant context from one or more exemplar changes, automated approaches can (1) apply similar changes to other loca- tions, (2) locate code that requires similar changes, and (3) refactor code which undergoes systematic edits. This thesis seeks to improve programmer produc- tivity and software correctness by automating parts of systematic editing and refactoring. Applying similar, but not identical code changes, to multiple locations with similar contexts requires (1) understanding and relating common program context—a program’s syntactic structure, control, and data flow—relevant to the edits in order to propagate code changes from one location to oth- ers, and (2) recognizing differences between locations in order to customize code changes for each location. Prior approaches for propagating nontrivial, general-purpose code changes from one location to another either do not ob- serve the program context when placing edits, or do not handle the differences between locations when customizing edits, producing syntactic invalid or in- correctly modified programs. We design a novel technique and implement it in a tool called Sydit. Our approach first creates an abstract, context-aware edit script which contains a syntax subtree enclosing the exemplar edit with all concrete identifiers abstracted and a sequence of edit operations. It then applies the edit script to user-selected locations by establishing both context matching and identifier matching to correctly place and customize the edit. Although SYDIT is effective in helping developers correctly apply edits to multiple locations, programmers are still on their own to identify all the appropriate locations. When developers omit some of the locations, the edit script inferred from a single code location is not always well suited to help them find the locations. One approach to infer the edit script is encoding the concrete context. However, the resulting edit script is too specific to the source location, and therefore can only identify locations which contain syntax trees identical to the source location (false negatives). Another approach is to encode context with all identifiers abstracted, but the resulting edit script may match too many locations (false positives). To suggest edit locations, we use multiple examples to create a partially abstract, context-aware edit script, and use this edit script to both find edit locations and transform the code. Our experiments show that edit scripts from multiple examples have high precision and recall in finding edit locations and high accuracy when applying systematic edits because the extracted common context together with identified common concrete identifiers from multiple examples improves the location search without sacrificing edit application accuracy. For systematic edits which insert or update duplicated code, our systematic editing approaches may encourage developers in the bad practice of creating or evolving duplicated code. We investigate and evaluate an approach that automatically refactors cloned code based on the extent of systematic edits by factoring out common code and parameterizing any differences between them. Our investigation finds that refactoring systematically edited code is not always feasible or desirable. When refactoring is desirable, systematic ed- its offer a better way to scope the refactoring as compared to whole method refactoring. Automatic clone removal refactoring cannot obviate the need for systematic editing. Developers need tool support for both automatic refactoring and systematic editing. Based on the systematic changes already made by developers for a subset of change locations, our automated approaches facilitate propagating general purpose systematic changes across large programs, identifying locations requiring systematic changes missed by developers, and refactoring code undergoing systematic edits to reduce code duplication and future repetitive code changes. The combination of these techniques opens a new way of helping developers automate tedious and error-prone tasks, when they add features, fix bugs, and maintain software. These techniques also have the potential to guide automated software development and maintenance activities based on existing code changes mined from version histories for bug fixes, feature additions, refactoring, and software migration.<br>text

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Whitmore, Margaret R. "The search for character servant-leadership in an Australian organisation /." 2004. http://portal.ecu.edu.au/adt-public/adt-ECU2006.0003.html.

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Books on the topic "Edit search"

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Hilliard, Christopher. The Perfect Witness. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198799658.003.0010.

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After a briefing from the West Sussex police, the DPP, Sir Archibald Bodkin, arranged for George Nicholls to return to Littlehampton and investigate further. Edith Swan was arrested and her house searched again. The search turned up some account books that could have supplied the paper for the recent libels. By the time her case came to trial, the Littlehampton libels had become a matter of more than local fascination. National newspapers reported the trial in detail. Swan was tried before a judge who found Swan’s performance in the witness box convincing and took the extraordinary step of cutting off the prosecution and telling the jury they should acquit. John Bull accused Nicholls of botching the case, prompting him to sue the paper for libel.

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Book chapters on the topic "Edit search"

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Ishibashi, Ken, and Kazunori Miyata. "Edit-Based Font Search." In MultiMedia Modeling. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27671-7_46.

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Nakagawa, Shunta, Tokio Sakamoto, Yoshimasa Takabatake, Tomohiro I, Kilho Shin, and Hiroshi Sakamoto. "Privacy-Preserving String Edit Distance with Moves." In Similarity Search and Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02224-2_18.

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Schwarz, Stefan, Mateusz Pawlik, and Nikolaus Augsten. "A New Perspective on the Tree Edit Distance." In Similarity Search and Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68474-1_11.

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Gouda, Karam, Mona Arafa, and Toon Calders. "BFST_ED: A Novel Upper Bound Computation Framework for the Graph Edit Distance." In Similarity Search and Applications. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46759-7_1.

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Riesen, Kaspar. "Appendix A: Experimental Evaluation of Sorted Beam Search." In Structural Pattern Recognition with Graph Edit Distance. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27252-8_8.

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Chung, Chin-Wan, Yufei Tao, and Wei Wang. "I/O-Efficient Dictionary Search with One Edit Error." In String Processing and Information Retrieval. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11918-2_19.

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Lu, Jianhua, Ningyun Lu, Sipei Ma, and Baili Zhang. "Edit Distance Based Similarity Search of Heterogeneous Information Networks." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98812-2_16.

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Darwiche, Mostafa, Donatello Conte, Romain Raveaux, and Vincent T’kindt. "Solving the Graph Edit Distance Problem with Variable Partitioning Local Search." In Graph-Based Representations in Pattern Recognition. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20081-7_7.

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Bringer, Julien, and Hervé Chabanne. "Embedding Edit Distance to Allow Private Keyword Search in Cloud Computing." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22339-6_13.

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Yamamoto, Takehiro, Satoshi Nakamura, and Katsumi Tanaka. "Reranking and Classifying Search Results Exhaustively Based on Edit-and-Propagate Operations." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03573-9_73.

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Conference papers on the topic "Edit search"

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"CDROM - Edit/Search." In 2006 IEEE International Conference on Field Programmable Technology. IEEE, 2006. http://dx.doi.org/10.1109/fpt.2006.270381.

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de la Higuera, Colin, and Luisa Micó. "A Contextual Normalised Edit Distance." In 2008 First International Workshop on Similarity Search and Applications (SISAP '08). IEEE, 2008. http://dx.doi.org/10.1109/sisap.2008.17.

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Cohen, Sara. "Indexing for subtree similarity-search using edit distance." In the 2013 international conference. ACM Press, 2013. http://dx.doi.org/10.1145/2463676.2463716.

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Audhkhasi, Kartik, and Ashish Verma. "Keyword Search using Modified Minimum Edit Distance Measure." In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.367223.

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Dong Deng, Guoliang Li, Jianhua Feng, and Wen-Syan Li. "Top-k string similarity search with edit-distance constraints." In 2013 29th IEEE International Conference on Data Engineering (ICDE 2013). IEEE, 2013. http://dx.doi.org/10.1109/icde.2013.6544886.

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Mishra, Shashwat, Tejas Gandhi, Akhil Arora, and Arnab Bhattacharya. "Efficient edit distance based string similarity search using deletion neighborhoods." In the Joint EDBT/ICDT 2013 Workshops. ACM Press, 2013. http://dx.doi.org/10.1145/2457317.2457387.

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Zhang, Haoyu, and Qin Zhang. "MinSearch: An Efficient Algorithm for Similarity Search under Edit Distance." In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 2020. http://dx.doi.org/10.1145/3394486.3403099.

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Zheng, Weiguo, Lei Zou, Xiang Lian, Dong Wang, and Dongyan Zhao. "Graph similarity search with edit distance constraint in large graph databases." In the 22nd ACM international conference. ACM Press, 2013. http://dx.doi.org/10.1145/2505515.2505723.

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Yang, Lei, and Lei Zou. "Noah: Neural-optimized A* Search Algorithm for Graph Edit Distance Computation." In 2021 IEEE 37th International Conference on Data Engineering (ICDE). IEEE, 2021. http://dx.doi.org/10.1109/icde51399.2021.00056.

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Wong, Chu-Pan, Priscila Santiesteban, Christian Kästner, and Claire Le Goues. "VarFix: balancing edit expressiveness and search effectiveness in automated program repair." In ESEC/FSE '21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. ACM, 2021. http://dx.doi.org/10.1145/3468264.3468600.

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