Relevant bibliographies by topics / Querying (Computer science)

Academic literature on the topic 'Querying (Computer science)'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Querying (Computer science)"

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Lai, Catherine, and Steven Bird. "Querying Linguistic Trees." Journal of Logic, Language and Information 19, no. 1 (May 28, 2009): 53–73. http://dx.doi.org/10.1007/s10849-009-9086-9.

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Vardi, Moshe Y. "Querying logical databases." Journal of Computer and System Sciences 33, no. 2 (October 1986): 142–60. http://dx.doi.org/10.1016/0022-0000(86)90016-4.

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Ganesan, K., and G. Siva. "Multilingual Querying and Information Processing." Information Technology Journal 6, no. 5 (June 15, 2007): 751–55. http://dx.doi.org/10.3923/itj.2007.751.755.

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Buneman, O. P., S. B. Davidson, and A. Watters. "Querying independent databases." Information Sciences 52, no. 1 (October 1990): 1–34. http://dx.doi.org/10.1016/0020-0255(90)90033-7.

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Barton, Carl, Mathieu Giraud, Costas S. Iliopoulos, Thierry Lecroq, Laurent Mouchard, and Solon P. Pissis. "Querying highly similar sequences." International Journal of Computational Biology and Drug Design 6, no. 1/2 (2013): 119. http://dx.doi.org/10.1504/ijcbdd.2013.052206.

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Chabrier-Rivier, Nathalie, Marc Chiaverini, Vincent Danos, François Fages, and Vincent Schächter. "Modeling and querying biomolecular interaction networks." Theoretical Computer Science 325, no. 1 (September 2004): 25–44. http://dx.doi.org/10.1016/j.tcs.2004.03.063.

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Siddiqui, Tarique, Paul Luh, Zesheng Wang, Karrie Karahalios, and Aditya G. Parameswaran. "Expressive querying for accelerating visual analytics." Communications of the ACM 65, no. 7 (July 2022): 85–94. http://dx.doi.org/10.1145/3535337.

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Data visualization is the primary means by which data analysts explore patterns, trends, and insights in their data. Unfortunately, existing visual analytics tools offer limited expressiveness and scalability when it comes to searching for visualizations over large datasets, making visual data exploration labor-intensive and time-consuming. In this work, we introduce the problem of visualization search and highlight two underlying challenges of search enumeration and visualization matching. To address them, we first present our work on Zenvisage that helps enumerate large collections of visualizations and supports simple visualization matching with the help of an interactive interface and an expressive visualization query language. For more finegrained and flexible visualization matching, including search for underspecified and approximate patterns, we extend Zenvisage to develop ShapeSearch. ShapeSearch supports a novel shape querying algebra that helps express a large class of pattern queries that are hard to specify with existing systems. ShapeSearch exposes multiple specification mechanisms: sketch, natural-language, and visual regular expressions that help users easily issue shape queries, while applying query-aware and perceptually-aware optimizations to efficiently execute them within interactive response times. To conclude, we discuss a number of open research problems to further improve the usability and performance of both Zenvisage and ShapeSearch.
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Cao, Zhongsheng, Zongda Wu, Yuanzhen Wang, and Guiling Li. "Processing Techniques for Querying Multimedia Contents." Information Technology Journal 8, no. 8 (November 1, 2009): 1115–28. http://dx.doi.org/10.3923/itj.2009.1115.1128.

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Flesca, S., F. Furfaro, and S. Greco. "Graph Grammars for Querying Graph-like Data." Electronic Notes in Theoretical Computer Science 50, no. 3 (August 2001): 247–56. http://dx.doi.org/10.1016/s1571-0661(04)00176-8.

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Belazzougui, Djamal, Roman Kolpakov, and Mathieu Raffinot. "Indexing and querying color sets of images." Theoretical Computer Science 647 (September 2016): 74–84. http://dx.doi.org/10.1016/j.tcs.2016.07.041.

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Dissertations / Theses on the topic "Querying (Computer science)"

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Yang, Lei. "Querying Graph Structured Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=case1410434109.

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Chavda, Manoj. "Visually querying object-oriented databases." Master's thesis, University of Cape Town, 1997. http://hdl.handle.net/11427/17516.

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Bibliography: pages 141-145.
As database requirements increase, the ability to construct database queries efficiently becomes more important. The traditional means of querying a database is to write a textual query, such as writing in SQL to query a relational database. Visual query languages are an alternative means of querying a database; a visual query language can embody powerful query abstraction and user feedback techniques, thereby making them potentially easier to use. In this thesis, we develop a visual query system for ODMG-compliant object-oriented databases, called QUIVER. QUIVER has a comprehensive expressive power; apart from supporting data types such as sets, bags, arrays, lists, tuples, objects and relationships, it supports aggregate functions, methods and sub-queries. The language is also consistent, as constructs with similar functionality have similar visual representations. QUIVER uses the DOT layout engine to automatically layout a query; QUIVER queries are easily constructed, as the system does not constrain the spatial arrangement of query items. QUIVER also supports a query library, allowing queries to be saved, retrieved and shared among users. A substantial part of the design has been implemented using the ODMG-compliant database system O₂, and the usability of the interface as well as the query language itself is presented. Visual queries are translated to OQL, the standard query language proposed by the ODMG, and query answers are presented using O₂ Look. During the course of our investigation, we conducted a user evaluation to compare QUIVER and OQL. The results were extremely encouraging in favour of QUIVER.
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Wu, Chao-Hui. "Querying and synchronizing multimedia presentations /." The Ohio State University, 1998. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488186329501598.

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Hossain, Md Delwar. "Querying communities of interest in peer database networks." Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/26926.

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Peer-to-Peer (P2P) networks are used primarily for file sharing. P2P user communities are continuing to grow rapidly, but there is no specific query mechanism for communities of interest in peer database networks. Peer databases are linked to each other through acquaintances. These are individual, independently developed databases that contain local data. Many researchers have tackled the problem of query processing in P2P networks. Moreover, researchers have started to investigate community-based querying in peer database networks. The focus of this thesis is to study a query translation mechanism, to develop an algorithm for querying communities of interest in peer database networks, and to implement a prototype of this algorithm. P2P communities are formed using common claimed items. First, we investigate an existing community formation and discovery algorithm for a text file, as well as an existing query translation mechanism for peer databases. After that, we develop a community-based search algorithm for peer databases. The developed algorithm combines the aforementioned community formation and discovery with the query translation mechanisms. A prototype has been developed and experimental results are shown. An approach for discovering communities 'on the fly' is introduced and a method for optimizing the community discovery technique is shown.
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Chiu, Tsz Wai. "WinyDB : collaboratively querying sensor networks through handheld devices /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?CSED%202008%20CHIUT.

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Colgrove, Matthew Edward. "Querying Geographically Dispersed, Heterogeneous Data Stores: The PPerfXchange Approach." PDXScholar, 2002. https://pdxscholar.library.pdx.edu/open_access_etds/2665.

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This thesis details PPerfXchange’s approach for querying geographically dispersed heterogeneous data stores. While elements of PPerfXchange’s method have been implemented for other application areas, PPerfXchange shows how these elements can be applied to parallel performance analysis. The accomplishments of this thesis are: The design of an architecture for PPerfXchange, giving a uniform method to query heterogeneous data stores; A proof of concept prototype implementation of PPerfXchange including a partial implementation of an XQuery processor and a relational database virtual XML document; and Evaluation of PPerfXchange using example parallel performance analysis data.
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Qiao, Shi. "QUERYING GRAPH STRUCTURED RDF DATA." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1447198654.

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Sun, Yi. "Querying with Ontological Terminologies And their Annotations." Miami University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=miami1177653662.

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Lam, Wai-Yeung. "XCQ : a framework for XML compression and querying /." View abstract or full-text, 2003. http://library.ust.hk/cgi/db/thesis.pl?COMP%202003%20LAM.

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Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2003.
Includes bibliographical references (leaves 142-147). Also available in electronic version. Access restricted to campus users.
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Li, Jing, and 李晶. "Advanced spatial queries with textual and social components." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B49617837.

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The emerging new services for GPS and mobile users have developed applications that access and exploit spatial objects with new components (e.g. text and social network). Web objects, including blogs, tweets, photos and videos, are embedded into a map by the APIs of map service providers, where textual messages are associated with geographic information. Location-based social networking services, arising from Facebook and Foursquare, allow users to browse and share their traces of locations among the social networks. Among this class of applications, the highlight is that the retrieved spatial objects (e.g. points of interest and moving users) are featured with new components. Integrating such new components into the spatial query processing has produced large amounts of promising results. However, handling new components along with the retrieval of spatial objects increases the complexity of such joint query processing significantly. Thus, management over data from such multiple domains has been received considerable attention from database research community. In this thesis, we introduce three interesting problems and study their sophisticated solutions for processing spatial objects with new components: (i) category-aware optimal route query (CORQ), (ii) social and spatial ranking query (SSRQ), and (iii) efficient notification of meeting point (ENMP) query. Our results for (i) and (ii) facilitate the retrieval of spatial objects from multiple domains while our solutions for (iii) provide effective tools for synchronous management of multiple moving users from a social network. Category-aware optimal route queries (CORQ) are generalized from the traveling salesman problem and enable users to retrieve shortest routes covering selected categories. Social and spatial ranking queries (SSRQ) are relevant to spatial object recommendations using social information and allow users to obtain the spatial objects that not only are near their locations but also impress them with high social influence. Efficient notification of meeting point (ENMP) queries are variants of aggregate nearest neighbor queries and provide real-time rearrangement for multiple moving users according to their locations. Query processing in such multiple domains is complicated due to the mixture of domain information and their integration within one search. Naïve algorithms for these problems incur either numerous expensive evaluations or massive communication cost, which render them inapplicable to large datasets. Our main research purpose is to design efficient and effective solutions for the proposed problems, that avoid the aforementioned shortcomings of naïve algorithms.
published_or_final_version
Computer Science
Doctoral
Doctor of Philosophy
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Books on the topic "Querying (Computer science)"

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Salander, Elisabeth C., and Elisabeth C. Salander. Computer search algorithms. Hauppauge, N.Y: Nova Science Publishers, 2010.

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Salander, Elisabeth C. Computer search algorithms. Hauppauge, N.Y: Nova Science Publishers, 2010.

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Bell, Richard, writer of additional text, Dunlop, Davetta writer of additional text, and SAS Institute, eds. SAS enterprise guide 1: Querying and reporting. Cary, N.C: SAS Institute, 2012.

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DuCharme, Bob. Learning SPARQL: Querying and updating with SPARQL 1.1. Sebastopol, CA: O'Reilly Media, 2011.

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Clifford, James. Formal semantics and pragmatics for natural language querying. Cambridge: Cambridge University Press, 1990.

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Clifford, James. Formal Semantics and Pragmatics for Natural Language Querying. Cambridge: Cambridge University Press, 1990.

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Yan, Li. Handbook of research on innovative database query processing techniques. Hershey, PA: Information Science Reference, 2016.

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Bestehorn, Markus. Querying Moving Objects Detected by Sensor Networks. New York, NY: Springer New York, 2013.

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Ma, Zongmin, and Li Yan. Advanced database query systems: Techniques, applications and technologies. Edited by IGI Global. Hershey, Pa: IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA), 2011.

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Nevarez, Benjamin. Inside the SQL server query optimizer. [S.l.]: Red Gate Books, 2011.

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Book chapters on the topic "Querying (Computer science)"

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Denney, Ewen, Dwight Naylor, and Ganesh Pai. "Querying Safety Cases." In Lecture Notes in Computer Science, 294–309. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10506-2_20.

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Arfaoui, Olfa, and Minyar Sassi-Hidri. "Querying Compressed XML Data." In Lecture Notes in Computer Science, 487–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40319-4_42.

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Abiteboul, Serge. "Querying semi-structured data." In Lecture Notes in Computer Science, 1–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-62222-5_33.

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Rho, Hongsik, Wen-Chi Hou, Dunren Che, and Chih-Fang Wang. "Querying Semistructured Data Efficiently." In Lecture Notes in Computer Science, 18–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45227-0_3.

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Pivert, Olivier, and Henri Prade. "Querying Uncertain Multiple Sources." In Lecture Notes in Computer Science, 286–91. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11508-5_24.

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Ahmed, Waqas, and Esteban Zimányi. "Querying Multiversion Data Warehouses." In Communications in Computer and Information Science, 346–57. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23201-0_36.

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Thirunarayan, Krishnaprasad, and Trivikram Immaneni. "Flexible Querying of XML Documents." In Lecture Notes in Computer Science, 198–207. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11875604_23.

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Cheng, Reynold. "Querying and Cleaning Uncertain Data." In Lecture Notes in Computer Science, 41–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04559-2_4.

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Rosati, Riccardo. "The Limits of Querying Ontologies." In Lecture Notes in Computer Science, 164–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11965893_12.

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Dumbrava, Stefania, Angela Bonifati, Amaia Nazabal Ruiz Diaz, and Romain Vuillemot. "Approximate Querying on Property Graphs." In Lecture Notes in Computer Science, 250–65. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35514-2_19.

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Conference papers on the topic "Querying (Computer science)"

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Bárány, Vince, Georg Gottlob, and Martin Otto. "Querying the Guarded Fragment." In 2010 25th Annual IEEE Symposium on Logic in Computer Science (LICS 2010). IEEE, 2010. http://dx.doi.org/10.1109/lics.2010.26.

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Zechinelli-Martini, Jose-Luis, and Ilian Elias-Morales. "Modelling and querying sensor databases." In Eighth Mexican International Conference on Current Trends in Computer Science (ENC 2007). IEEE, 2007. http://dx.doi.org/10.1109/enc.2007.29.

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Zechinelli-Martini, Jose-Luis, and Ilian Elias-Morales. "Modelling and querying sensor databases." In Eighth Mexican International Conference on Current Trends in Computer Science (ENC 2007). IEEE, 2007. http://dx.doi.org/10.1109/enc.2007.4351436.

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Benedikt, Michael, Pierre Bourhis, Balder ten Cate, and Gabriele Puppis. "Querying Visible and Invisible Information." In LICS '16: 31st Annual ACM/IEEE Symposium on Logic in Computer Science. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2933575.2935306.

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Guerroudji-Meddah, Fatiha, Hafida Belbachir, and Robert Laurini. "A visual language for GIS querying." In 2009 2nd IEEE International Conference on Computer Science and Information Technology. IEEE, 2009. http://dx.doi.org/10.1109/iccsit.2009.5234515.

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Wang, Jinpeng, Zhuang Miao, Yafei Zhang, and Bo Zhou. "Querying Heterogeneous Relational Database using SPARQL." In 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science. IEEE, 2009. http://dx.doi.org/10.1109/icis.2009.11.

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Cuevas-Vicenttín, Víctor, Genoveva Vargas-Solar, Christine Collet, and Paolo Bucciol. "Efficiently Coordinating Services for Querying Data in Dynamic Environments." In 2009 Mexican International Conference on Computer Science. IEEE, 2009. http://dx.doi.org/10.1109/enc.2009.34.

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Barcelo, Pablo, Cristina Feier, Carsten Lutz, and Andreas Pieris. "When is Ontology-Mediated Querying Efficient?" In 2019 34th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS). IEEE, 2019. http://dx.doi.org/10.1109/lics.2019.8785823.

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Okure, Akanimo Samuel, and Jeff Z. Pan. "Querying EL Ontology Stream with C-SPARQL." In 2013 International Conference on Advanced Computer Science Applications and Technologies (ACSAT). IEEE, 2013. http://dx.doi.org/10.1109/acsat.2013.73.

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Zhu, Qing. "Integrating Strategies for Keyword Querying across Heterogeneous Databases." In 2009 First International Workshop on Education Technology and Computer Science. IEEE, 2009. http://dx.doi.org/10.1109/etcs.2009.643.

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