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Zeitschriftenartikel zum Thema „Data structures“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 25. Juli 2025

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1

Tamassia, Roberto. "Data structures." ACM Computing Surveys 28, no. 1 (1996): 23–26. http://dx.doi.org/10.1145/234313.234323.

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2

Jarc, Duane J. "Data structures." ACM SIGCSE Bulletin 26, no. 2 (1994): 2–4. http://dx.doi.org/10.1145/181648.181651.

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3

Biswas, Ranjit. "Data structures for big data." International Journal of Computing and Optimization 1 (2014): 73–93. http://dx.doi.org/10.12988/ijco.2014.4813.

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4

Basch, Julien, Leonidas J. Guibas, and John Hershberger. "Data Structures for Mobile Data." Journal of Algorithms 31, no. 1 (1999): 1–28. http://dx.doi.org/10.1006/jagm.1998.0988.

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5

Yarosh, Svetlana, and Mark Guzdial. "Narrating data structures." Journal on Educational Resources in Computing 7, no. 4 (2008): 1–20. http://dx.doi.org/10.1145/1316450.1316456.

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6

RUUS, H. "Lexical Data Structures." Literary and Linguistic Computing 3, no. 3 (1988): 169–76. http://dx.doi.org/10.1093/llc/3.3.169.

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7

Giles, D. "Editorial - Data Structures." Computer Journal 34, no. 5 (1991): 385. http://dx.doi.org/10.1093/comjnl/34.5.385.

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8

Demaine, Erik D., John Iacono, and Stefan Langerman. "Retroactive data structures." ACM Transactions on Algorithms 3, no. 2 (2007): 13. http://dx.doi.org/10.1145/1240233.1240236.

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9

Louchard, G., Claire Kenyon, and R. Schott. "Data Structures' Maxima." SIAM Journal on Computing 26, no. 4 (1997): 1006–42. http://dx.doi.org/10.1137/s0097539791196603.

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10

Nair, Achuth Sankar S., and T. Mahalakshmi. "Conceptualizing data structures." ACM SIGCSE Bulletin 36, no. 4 (2004): 97–100. http://dx.doi.org/10.1145/1041624.1041668.

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11

Munro, Ian. "Succinct Data Structures." Electronic Notes in Theoretical Computer Science 91 (February 2004): 3. http://dx.doi.org/10.1016/j.entcs.2003.12.002.

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12

Sotvoldieva, Dildora, and Yakhyobek Mekhmonaliyev. "SPATIAL DATA STRUCTURES." Research and implementation 2, no. 2 (2024): 28–34. https://doi.org/10.5281/zenodo.10669183.

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13

Kolesnikov, Valeriy. "VISUALIZING GRAPH DATA STRUCTURES: ENHANCING UNDERSTANDING IN DATA STRUCTURES EDUCATION." Transactions of Kremenchuk Mykhailo Ostrohradskyi National University 145, no. 2 (2024): 58–62. http://dx.doi.org/10.32782/1995-0519.2024.2.7.

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14

Butaboev, Makhammadjon Tuychiyevich, and Moydinjon Abdurakhmanovich Arziyev. "ESSENCE OF BIG DATA." International Journal Of Management And Economics Fundamental 4, no. 4 (2024): 40–49. http://dx.doi.org/10.37547/ijmef/volume04issue04-06.

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In this article, we consider the rapidly developing sphere in the digital economy -big data, which in the modern world allows governments, businesses and social structures to turn tons of heterogeneous information into structured knowledge. The experience of developing the big data science in the leading countries of the world is discussed and, using their example, the possibility of implementing big data in Uzbekistan is considered.

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15

Arvind, Rishiyur S. Nikhil, and Keshav K. Pingali. "I-structures: data structures for parallel computing." ACM Transactions on Programming Languages and Systems 11, no. 4 (1989): 598–632. http://dx.doi.org/10.1145/69558.69562.

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16

Smith, N. S. "Spatial data models and data structures." Computer-Aided Design 22, no. 3 (1990): 184–90. http://dx.doi.org/10.1016/0010-4485(90)90077-p.

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17

Steenbergen, Marco R., and Bradford S. Jones. "Modeling Multilevel Data Structures." American Journal of Political Science 46, no. 1 (2002): 218. http://dx.doi.org/10.2307/3088424.

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18

Chen, Victor, Elena Grigorescu, and Ronald de Wolf. "Error-Correcting Data Structures." SIAM Journal on Computing 42, no. 1 (2013): 84–111. http://dx.doi.org/10.1137/110834949.

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19

Persch, G. "Editing IDL data structures." ACM SIGPLAN Notices 22, no. 11 (1987): 79–86. http://dx.doi.org/10.1145/39305.39313.

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20

Mäkinen, Erkki, and Markku Siermala. "Restricted universe data structures." ACM SIGCSE Bulletin 32, no. 2 (2000): 22–24. http://dx.doi.org/10.1145/355354.355365.

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21

Solar-Lezama, Armando, Christopher Grant Jones, and Rastislav Bodik. "Sketching concurrent data structures." ACM SIGPLAN Notices 43, no. 6 (2008): 136–48. http://dx.doi.org/10.1145/1379022.1375599.

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22

Smaragdakis, Yannis. "High-level data structures." Communications of the ACM 55, no. 12 (2012): 90. http://dx.doi.org/10.1145/2380656.2380676.

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23

Hartel, Pieter. "Purely functional data structures." Science of Computer Programming 34, no. 1 (1999): 75–77. http://dx.doi.org/10.1016/s0167-6423(99)00002-7.

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24

Aspnes, James, David Eisenstat, and Yitong Yin. "Low-contention data structures." Journal of Parallel and Distributed Computing 72, no. 5 (2012): 705–15. http://dx.doi.org/10.1016/j.jpdc.2011.10.018.

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25

Wallis, Peter. "Algorithms and data structures." Science of Computer Programming 12, no. 2 (1989): 157–58. http://dx.doi.org/10.1016/0167-6423(89)90040-3.

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26

Gagie, Travis. "Preface – Compact Data Structures." Journal of Discrete Algorithms 43 (March 2017): 1. http://dx.doi.org/10.1016/j.jda.2017.04.002.

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27

Xu, Guoqing. "Finding reusable data structures." ACM SIGPLAN Notices 47, no. 10 (2012): 1017–34. http://dx.doi.org/10.1145/2398857.2384690.

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28

Driscoll, James R., Neil Sarnak, Daniel D. Sleator, and Robert E. Tarjan. "Making data structures persistent." Journal of Computer and System Sciences 38, no. 1 (1989): 86–124. http://dx.doi.org/10.1016/0022-0000(89)90034-2.

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29

Miller, Andrew, Michael Hicks, Jonathan Katz, and Elaine Shi. "Authenticated data structures, generically." ACM SIGPLAN Notices 49, no. 1 (2014): 411–23. http://dx.doi.org/10.1145/2578855.2535851.

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30

Adams, Joel. "Test-driven data structures." ACM SIGCSE Bulletin 41, no. 1 (2009): 143–47. http://dx.doi.org/10.1145/1539024.1508920.

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31

Kienel, C., and S. Kimeswenger. "Covered data structures I." Astronomy and Astrophysics Supplement Series 127, no. 2 (1998): 319–25. http://dx.doi.org/10.1051/aas:1998370.

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32

Taylor, David J., and James P. Black. "Experimenting with data structures." Software: Practice and Experience 16, no. 5 (1986): 443–56. http://dx.doi.org/10.1002/spe.4380160506.

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33

Rosenberg, J. B. "Geographical Data Structures Compared: A Study of Data Structures Supporting Region Queries." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 4, no. 1 (1985): 53–67. http://dx.doi.org/10.1109/tcad.1985.1270098.

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34

tom Wörden, Henrik, Florian Spreckelsen, Stefan Luther, Ulrich Parlitz, and Alexander Schlemmer. "Mapping Hierarchical File Structures to Semantic Data Models for Efficient Data Integration into Research Data Management Systems." Data 9, no. 2 (2024): 24. http://dx.doi.org/10.3390/data9020024.

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Although other methods exist to store and manage data in modern information technology, the standard solution is file systems. Therefore, keeping well-organized file structures and file system layouts can be key to a sustainable research data management infrastructure. However, file structures alone lack several important capabilities for FAIR data management: the two most significant being insufficient visualization of data and inadequate possibilities for searching and obtaining an overview. Research data management systems (RDMSs) can fill this gap, but many do not support the simultaneous

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35

Gog, Simon, and Matthias Petri. "Optimized succinct data structures for massive data." Software: Practice and Experience 44, no. 11 (2013): 1287–314. http://dx.doi.org/10.1002/spe.2198.

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36

A Alnoshan Hessah, Ayshah. "Evaluation the Performance of Data Structures: A Comparative Approach." International Journal of Science and Research (IJSR) 12, no. 8 (2023): 880–85. http://dx.doi.org/10.21275/sr23807001651.

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37

Massart, B., Q. Guo, F. Questier, et al. "Data structures and data transformations for clustering chemical data." TrAC Trends in Analytical Chemistry 20, no. 1 (2001): 35–41. http://dx.doi.org/10.1016/s0167-2940(01)90097-4.

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38

kumar, Vinesh, Dr Amit Asthana, Sunil Kumar, and Dr Jayant Shekhar. "Data Representation in Big data via Succinct Data Structures." International Journal of Engineering Science and Technology 10, no. 1 (2018): 21–28. http://dx.doi.org/10.21817/ijest/2018/v10i1/181001013.

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39

Li, Shujie, Liang Li, Ruiying Geng, et al. "Unifying Structured Data as Graph for Data-to-Text Pre-Training." Transactions of the Association for Computational Linguistics 12 (2024): 210–28. http://dx.doi.org/10.1162/tacl_a_00641.

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Abstract Data-to-text (D2T) generation aims to transform structured data into natural language text. Data-to-text pre-training has proved to be powerful in enhancing D2T generation and yields impressive performance. However, previous pre-training methods either oversimplified structured data into a sequence without considering input structures or designed training objectives tailored for a specific data structure (e.g., table or knowledge graph). In this paper, we unify different types of structured data (i.e., table, key-value data, knowledge graph) into the graph format and cast different D2

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40

FAROKH, B. "Effect of data structures on the logical complexity of programs." Communications of the ACM 30, no. 3 (2023): 250–59. https://doi.org/10.5281/zenodo.7505078.

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The logical complexity of a program is a measure of the effort required to understand it. We hypothesize that the logical co.mplexity of a program increases with the increase in the opaqueness of the relationship between the physical data structures used in the program and their corresponding abstract data types. The results of an experiment conducted to investigate this hypothesis are reported. Documentation techniques for making programs easier to understand using complex data structures are discussed. Data structure diagrams, data structure invariants, stepwise transformation of data struct

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41

Grandin, Magnus. "Data structures and algorithms for high-dimensional structured adaptive mesh refinement." Advances in Engineering Software 82 (April 2015): 75–86. http://dx.doi.org/10.1016/j.advengsoft.2014.12.001.

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42

Donner, Klaus. "Data structures and dynamic programming background for editing highly structured texts." Annals of Operations Research 16, no. 1 (1988): 267–80. http://dx.doi.org/10.1007/bf02283748.

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43

Zheng, H., H. Y. Wang, N. D. Black, and R. J. Winder. "Data structures, coding and classification." Technology and Health Care 18, no. 1 (2010): 71–87. http://dx.doi.org/10.3233/thc-2010-0568.

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44

Janićijević, Stefana, and Vojkan Nikolić. "Graph structures for data visualizations." Serbian Journal of Engineering Management 6, no. 2 (2021): 24–31. http://dx.doi.org/10.5937/sjem2102024j.

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Networks are all around us. Graph structures are established in the core of every network system therefore it is assumed to be understood as graphs as data visualization objects. Those objects grow from abstract mathematical paradigms up to information insights and connection channels. Essential metrics in graphs were calculated such as degree centrality, closeness centrality, betweenness centrality and page rank centrality and in all of them describe communication inside the graph system. The main goal of this research is to look at the methods of visualization over the existing Big data and

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45

Manjula, V. "Graph Applications to Data Structures." Advanced Materials Research 433-440 (January 2012): 3297–301. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3297.

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This paper presents a topic on Graph theory and its application to data Structures which I consider basic and useful to students in APPLIED MATHEMATICS and ENGINEERING.This paper gives an elementary introduction of Graph theory and its application to data structures. Elements of Graph theory are indispensable in almost all computer Science areas .It can be used in Some areas such as syntactic analysis, fault detection, diagnosis in computers and minimal path problems. The computer representation and manipulation of graph are also discussed so that certain algorithms can be included .A major th

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46

He, Meng, J. Ian Munro, and Gelin Zhou. "Data Structures for Path Queries." ACM Transactions on Algorithms 12, no. 4 (2016): 1–32. http://dx.doi.org/10.1145/2905368.

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47

d'Aubigny, Gérard. "Data Analysis of Asymmetric Structures." Journal of the Royal Statistical Society: Series A (Statistics in Society) 170, no. 3 (2007): 858–60. http://dx.doi.org/10.1111/j.1467-985x.2007.00485_9.x.

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48

Feldman, Michael B. "Teaching data structures with Ada." ACM SIGCSE Bulletin 22, no. 2 (1990): 21–29. http://dx.doi.org/10.1145/126445.126450.

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49

Nguyen, Dung. "Design patterns for data structures." ACM SIGCSE Bulletin 30, no. 1 (1998): 336–40. http://dx.doi.org/10.1145/274790.274325.

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50

Hargreaves, Sarah. "Data bank for carbohydrate structures." Nature 324, no. 6094 (1986): 208. http://dx.doi.org/10.1038/324208a0.

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