Auswahl der wissenschaftlichen Literatur zum Thema „Storage and indexing“
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Zeitschriftenartikel zum Thema "Storage and indexing"
Vimal, Vrince. „An Efficient and Secure Query Processing and Indexing model for Secure Dynamic Cloud Storage“. Turkish Journal of Computer and Mathematics Education (TURCOMAT) 10, Nr. 2 (10.09.2019): 1043–48. http://dx.doi.org/10.17762/turcomat.v10i2.13623.
Der volle Inhalt der QuelleIliopoulos, Costas. „Storage and indexing of massive data“. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, Nr. 2016 (28.05.2014): 20130213. http://dx.doi.org/10.1098/rsta.2013.0213.
Der volle Inhalt der QuelleAdeleke, Imran A., Adegbuyi D. Gbadebo und Abayomi O. Dawodu. „A B+-Tree-Based Indexing and Storage of Numerical Records in School Databases“. Asian Journal of Research in Computer Science 16, Nr. 4 (26.12.2023): 418–27. http://dx.doi.org/10.9734/ajrcos/2023/v16i4401.
Der volle Inhalt der QuelleNiu, De Jiao, Yong Zhao Zhan und Tao Cai. „The Multi-Level Metadata Indexing in Mass Storage System“. Advanced Materials Research 532-533 (Juni 2012): 818–22. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.818.
Der volle Inhalt der QuelleJiang, Chao, Jinlin Wang und Yang Li. „An Efficient Indexing Scheme for Network Traffic Collection and Retrieval System“. Electronics 10, Nr. 2 (15.01.2021): 191. http://dx.doi.org/10.3390/electronics10020191.
Der volle Inhalt der QuelleDu, M., J. Wang, C. Jing, J. Jiang und Q. Chen. „HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (05.06.2019): 1295–99. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1295-2019.
Der volle Inhalt der QuelleGeetha, K., und A. Vijaya. „Cross-Layer Fragment Indexing based File Deduplication using Hyper Spectral Hash Duplicate Filter (HSHDF) for Optimized Cloud Storage“. International Journal on Recent and Innovation Trends in Computing and Communication 11, Nr. 8s (18.08.2023): 565–75. http://dx.doi.org/10.17762/ijritcc.v11i8s.7239.
Der volle Inhalt der QuelleMoses, Timothy, Abubakar Usman Othman, Umar Yahaya Aisha, Abdulsalam Ya’u Gital, Boukari Souley und Badmos Tajudeen Adeleke. „Big data indexing: Taxonomy, performance evaluation, challenges and research opportunities“. Journal of Computer Science and Engineering (JCSE) 3, Nr. 2 (06.09.2022): 71–94. http://dx.doi.org/10.36596/jcse.v3i2.548.
Der volle Inhalt der QuelleTurner, James M. „Indexing “Ordinary” Pictures for Storage and Retrieval“. Visual Resources 10, Nr. 3 (Januar 1994): 265–73. http://dx.doi.org/10.1080/01973762.1994.9658292.
Der volle Inhalt der QuelleKundu, Anirban, Siddhartha Sett, Subhajit Kumar, Shruti Sengupta und Srayan Chaudhury. „Search engine indexing storage optimisation using Hamming distance“. International Journal of Intelligent Information and Database Systems 6, Nr. 2 (2012): 113. http://dx.doi.org/10.1504/ijiids.2012.045845.
Der volle Inhalt der QuelleDissertationen zum Thema "Storage and indexing"
Munishwar, Vikram P. „Storage and indexing issues in sensor networks“. Diss., Online access via UMI:, 2006.
Den vollen Inhalt der Quelle findenSchmidt, Karsten [Verfasser]. „Self-Tuning Storage and Indexing for Native XML DBMSs / Karsten Schmidt“. München : Verlag Dr. Hut, 2011. http://d-nb.info/1018981071/34.
Der volle Inhalt der QuelleMick, Alan A. „Knowledge based text indexing and retrieval utilizing case based reasoning /“. Online version of thesis, 1994. http://hdl.handle.net/1850/11715.
Der volle Inhalt der QuelleHabtu, Simon. „Indexing file metadata using a distributed search engine for searching files on a public cloud storage“. Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-232064.
Der volle Inhalt der QuelleVisma Labs AB eller Visma ville genomföra experiment för att se om filmetadata skulle kunna indexeras för att söka efter filer på ett publikt moln. Med tanke på att lagring av filer på ett publikt moln är billigare än den nuvarande lagringslösningen, kan implementeringen spara Visma pengar som spenderas på dyra lagringskostnader. Denna studie är därför till för att hitta och utvärdera ett tillvägagångssätt valt för att indexera filmetadata och söka filer på ett offentligt molnlagring med den utvalda distribuerade sökmotorn Elasticsearch. Arkitekturen för den föreslagna lösningen har likenelser av en filtjänst och implementerades med flera containeriserade tjänster för att den ska fungera. Resultaten visar att filservicelösningen verkligen är möjlig men skulle behöva ytterligare modifikationer och fler resurser att fungera enligt Vismas krav.
Teng, Shyh Wei 1973. „Image indexing and retrieval based on vector quantization“. Monash University, Gippsland School of Computing and Information Technology, 2003. http://arrow.monash.edu.au/hdl/1959.1/5764.
Der volle Inhalt der QuelleYapp, Lawrence. „Content-based indexing of MPEG video through the analysis of the accompanying audio /“. Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/5835.
Der volle Inhalt der QuelleTekli, Joe, Richard Chbeir, Agma J. M. Traina, Caetano Traina, Kokou Yetongnon, Carlos Raymundo Ibanez, Assad Marc Al und Christian Kallas. „Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS“. Elsevier B.V, 2018. http://hdl.handle.net/10757/624626.
Der volle Inhalt der QuelleIn the past decade, there has been an increasing need for semantic-aware data search and indexing in textual (structured and NoSQL) databases, as full-text search systems became available to non-experts where users have no knowledge about the data being searched and often formulate query keywords which are different from those used by the authors in indexing relevant documents, thus producing noisy and sometimes irrelevant results. In this paper, we address the problem of semantic-aware querying and provide a general framework for modeling and processing semantic-based keyword queries in textual databases, i.e., considering the lexical and semantic similarities/disparities when matching user query and data index terms. To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. To investigate the practicality and effectiveness of SemIndex, we discuss its physical design within a standard commercial RDBMS allowing to create, store, and query its graph structure, thus enabling the system to easily scale up and handle large volumes of data. We have conducted a battery of experiments to test the performance of SemIndex, evaluating its construction time, storage size, query processing time, and result quality, in comparison with legacy inverted index. Results highlight both the effectiveness and scalability of our approach.
This study is partly funded by the National Council for Scientific Research - Lebanon (CNRS-L), by the Lebanese American University (LAU), and the Research Support Foundation of the State of Sao Paulo ( FAPESP ). Appendix SemIndex Weighting Scheme We propose a set of weighting functions to assign weight scores to SemIndex entries, including: index nodes , index edges, data nodes , and data edges . The weighting functions are used to select and rank semantically relevant results w.r.t. the user's query (cf. SemIndex query processing in Section 5). Other weight functions could be later added to cater to the index designer's needs.
Revisión por pares
Liu, Hain-Ching. „Automatic scene detection in MPEG digital video for random access indexing and MPEG compression optimization /“. Thesis, Connect to this title online; UW restricted, 1995. http://hdl.handle.net/1773/6001.
Der volle Inhalt der QuelleVasaitis, Vasileios. „Novel storage architectures and pointer-free search trees for database systems“. Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6240.
Der volle Inhalt der QuellePaul, Arnab Kumar. „An Application-Attuned Framework for Optimizing HPC Storage Systems“. Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/99793.
Der volle Inhalt der QuelleDoctor of Philosophy
Clusters of multiple computers connected through internet are often deployed in industry and laboratories for large scale data processing or computation that cannot be handled by standalone computers. In such a cluster, resources such as CPU, memory, disks are integrated to work together. With the increase in popularity of applications that read and write a tremendous amount of data, we need a large number of disks that can interact effectively in such clusters. This forms the part of high performance computing (HPC) storage systems. Such HPC storage systems are used by a diverse set of applications coming from organizations from a vast range of domains from earth sciences, financial services, telecommunication to life sciences. Therefore, the HPC storage system should be efficient to perform well for the different read and write (I/O) requirements from all the different sets of applications. But current HPC storage systems do not cater to the varied I/O requirements. To this end, this dissertation designs and develops a framework for HPC storage systems that is application-attuned and thus provides much improved performance than other state-of-the-art HPC storage systems without such optimizations.
Bücher zum Thema "Storage and indexing"
Manolopoulos, Yannis. Advanced database indexing. Boston: Kluwer Academic, 2000.
Den vollen Inhalt der Quelle findenLancaster, F. Wilfrid. Indexing and abstracting in theory and practice. London: Library Association, 1991.
Den vollen Inhalt der Quelle findenLibrary, Washington State, Hrsg. Agency guide to indexing websites. Olympia: Washington State Library, 1999.
Den vollen Inhalt der Quelle findenSystem, Unesco Computerized Documentation. CDS/ISIS cataloguing and indexing guide. 6. Aufl. [Paris]: UNESCO Integrated Documentation Network, 1994.
Den vollen Inhalt der Quelle findenBenois-Pineau, Jenny. Visual Indexing and Retrieval. New York, NY: Springer New York, 2012.
Den vollen Inhalt der Quelle findenCisco, Susan Lynn. Indexing business records: The value proposition. Silver Spring, MD: Association for Information and Image Management International, 1998.
Den vollen Inhalt der Quelle findenO'Connor, Brian Clark. Doing things with information: Beyond indexing and abstracting. Westport, Conn: Libraries Unlimited, 2008.
Den vollen Inhalt der Quelle findenBertino, Elisa. Indexing Techniques for Advanced Database Systems. Boston, MA: Springer US, 1997.
Den vollen Inhalt der Quelle findenChoi, Hansol. Purifying and Indexing Technology for Nucleic Acids-Based Next Generation Storage Medium. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-4274-7.
Der volle Inhalt der QuelleGreig, Peter E. Newspaper indexes & indexing: Newspaper information storage and retrieval : a checklist, 1980-1987. [S.l: s.n., 1987.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Storage and indexing"
Manolopoulos, Yannis, Yannis Theodoridis und Vassilis J. Tsotras. „Storage Systems“. In Advanced Database Indexing, 1–16. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4419-8590-3_1.
Der volle Inhalt der QuellePalladino, Santiago. „Indexing and Storage“. In Ethereum for Web Developers, 181–214. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5278-9_6.
Der volle Inhalt der QuelleFeng, Dan. „Indexing Schemes“. In Data Deduplication for High Performance Storage System, 53–68. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0112-6_4.
Der volle Inhalt der QuelleStrate, Jason, und Grant Fritchey. „Index Storage Fundamentals“. In Expert Performance Indexing in SQL Server, 15–54. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-1118-2_2.
Der volle Inhalt der QuelleStrate, Jason. „Index Storage Fundamentals“. In Expert Performance Indexing in SQL Server 2019, 29–90. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5464-6_2.
Der volle Inhalt der QuelleStrate, Jason, und Ted Krueger. „Index Storage Fundamentals“. In Expert Performance Indexing for SQL Server 2012, 15–49. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3742-6_2.
Der volle Inhalt der QuelleKorotkevitch, Dmitri. „Special Indexing and Storage Features“. In Pro SQL Server Internals, 81–110. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1964-5_4.
Der volle Inhalt der QuelleKorotkevitch, Dmitri. „Special Indexing and Storage Features“. In Pro SQL Server Internals, 81–112. Berkeley, CA: Apress, 2014. http://dx.doi.org/10.1007/978-1-4302-5963-3_4.
Der volle Inhalt der QuellePollack, Edward, und Jason Strate. „Index Storage Fundamentals“. In Expert Performance Indexing in Azure SQL and SQL Server 2022, 29–51. Berkeley, CA: Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9215-0_2.
Der volle Inhalt der QuelleGibbons, Philip B. „Data Storage and Indexing in Sensor Networks“. In Encyclopedia of Database Systems, 635–38. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_112.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Storage and indexing"
Alsubaiee, Sattam, Michael J. Carey und Chen Li. „LSM-Based Storage and Indexing“. In SIGMOD/PODS'15: International Conference on Management of Data. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2786006.2786007.
Der volle Inhalt der QuelleWei, Hai, und Lansun Shen. „Fractal-based image storage and indexing“. In Electronic Imaging, herausgegeben von Minerva M. Yeung, Boon-Lock Yeo und Charles A. Bouman. SPIE, 1999. http://dx.doi.org/10.1117/12.373574.
Der volle Inhalt der QuellePanwar, Ajeet Pal Singh, Devendra Kumar und Jaydesh Chandra. „Hierarchal data storage using NAI indexing“. In 2017 3rd International Conference on Advances in Computing,Communication & Automation (ICACCA) (Fall). IEEE, 2017. http://dx.doi.org/10.1109/icaccaf.2017.8344687.
Der volle Inhalt der QuellePaul, Arnab K., Brian Wang, Nathan Rutman, Cory Spitz und Ali R. Butt. „Efficient Metadata Indexing for HPC Storage Systems“. In 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID). IEEE, 2020. http://dx.doi.org/10.1109/ccgrid49817.2020.00-77.
Der volle Inhalt der Quelle„Session details: Industry 2: Storage & Indexing“. In the 2019 International Conference, Chair Alexander Shraer. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3299869.3341283.
Der volle Inhalt der QuelleSima, Jin, Netanel Raviv und Jehoshua Bruck. „Robust Indexing - Optimal Codes for DNA Storage“. In 2020 IEEE International Symposium on Information Theory (ISIT). IEEE, 2020. http://dx.doi.org/10.1109/isit44484.2020.9174447.
Der volle Inhalt der QuelleBarreto, João, und Paulo Ferreira. „Efficient file storage using content-based indexing“. In the twentieth ACM symposium. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1095810.1118597.
Der volle Inhalt der QuelleShraer, Alexander. „Session details: Industry 2: Storage & Indexing“. In SIGMOD/PODS '19: International Conference on Management of Data. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3341283.
Der volle Inhalt der QuelleWeintraub, Grisha, Ehud Gudes und Shlomi Dolev. „Indexing cloud data lakes within the lakes“. In SYSTOR '21: The 14th ACM International Systems and Storage Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3456727.3463828.
Der volle Inhalt der QuelleSmith, Mark, und Alireza Khotanzad. „Efficient Indexing and Storage Algorithm for Visual Databases“. In 2008 Fifth International Conference on Information Technology: New Generations (ITNG). IEEE, 2008. http://dx.doi.org/10.1109/itng.2008.162.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Storage and indexing"
Bethel, E. Wes, Luke Gosink, John Shalf, Kurt Stockinger und Kesheng Wu. HDF5-FastQuery: An API for Simplifying Access to Data Storage,Retrieval, Indexing and Querying. Office of Scientific and Technical Information (OSTI), Juni 2006. http://dx.doi.org/10.2172/888964.
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