Gotowa bibliografia na temat „Storage and indexing”
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Artykuły w czasopismach na temat "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.
Pełny tekst źródłaIliopoulos, 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.
Pełny tekst źródłaAdeleke, Imran A., Adegbuyi D. Gbadebo i 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.
Pełny tekst źródłaNiu, De Jiao, Yong Zhao Zhan i Tao Cai. "The Multi-Level Metadata Indexing in Mass Storage System". Advanced Materials Research 532-533 (czerwiec 2012): 818–22. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.818.
Pełny tekst źródłaJiang, Chao, Jinlin Wang i 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.
Pełny tekst źródłaDu, M., J. Wang, C. Jing, J. Jiang i 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 (5.06.2019): 1295–99. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1295-2019.
Pełny tekst źródłaGeetha, K., i 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.
Pełny tekst źródłaMoses, Timothy, Abubakar Usman Othman, Umar Yahaya Aisha, Abdulsalam Ya’u Gital, Boukari Souley i Badmos Tajudeen Adeleke. "Big data indexing: Taxonomy, performance evaluation, challenges and research opportunities". Journal of Computer Science and Engineering (JCSE) 3, nr 2 (6.09.2022): 71–94. http://dx.doi.org/10.36596/jcse.v3i2.548.
Pełny tekst źródłaTurner, James M. "Indexing “Ordinary” Pictures for Storage and Retrieval". Visual Resources 10, nr 3 (styczeń 1994): 265–73. http://dx.doi.org/10.1080/01973762.1994.9658292.
Pełny tekst źródłaKundu, Anirban, Siddhartha Sett, Subhajit Kumar, Shruti Sengupta i 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.
Pełny tekst źródłaRozprawy doktorskie na temat "Storage and indexing"
Munishwar, Vikram P. "Storage and indexing issues in sensor networks". Diss., Online access via UMI:, 2006.
Znajdź pełny tekst źródłaSchmidt, Karsten [Verfasser]. "Self-Tuning Storage and Indexing for Native XML DBMSs / Karsten Schmidt". München : Verlag Dr. Hut, 2011. http://d-nb.info/1018981071/34.
Pełny tekst źródłaMick, Alan A. "Knowledge based text indexing and retrieval utilizing case based reasoning /". Online version of thesis, 1994. http://hdl.handle.net/1850/11715.
Pełny tekst źródłaHabtu, 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.
Pełny tekst źródłaVisma 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.
Pełny tekst źródłaYapp, 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.
Pełny tekst źródłaTekli, Joe, Richard Chbeir, Agma J. M. Traina, Caetano Traina, Kokou Yetongnon, Carlos Raymundo Ibanez, Assad Marc Al i 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.
Pełny tekst źródłaIn 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.
Pełny tekst źródłaVasaitis, Vasileios. "Novel storage architectures and pointer-free search trees for database systems". Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6240.
Pełny tekst źródłaPaul, Arnab Kumar. "An Application-Attuned Framework for Optimizing HPC Storage Systems". Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/99793.
Pełny tekst źródłaDoctor 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.
Książki na temat "Storage and indexing"
Manolopoulos, Yannis. Advanced database indexing. Boston: Kluwer Academic, 2000.
Znajdź pełny tekst źródłaLancaster, F. Wilfrid. Indexing and abstracting in theory and practice. London: Library Association, 1991.
Znajdź pełny tekst źródłaLibrary, Washington State, red. Agency guide to indexing websites. Olympia: Washington State Library, 1999.
Znajdź pełny tekst źródłaSystem, Unesco Computerized Documentation. CDS/ISIS cataloguing and indexing guide. Wyd. 6. [Paris]: UNESCO Integrated Documentation Network, 1994.
Znajdź pełny tekst źródłaBenois-Pineau, Jenny. Visual Indexing and Retrieval. New York, NY: Springer New York, 2012.
Znajdź pełny tekst źródłaCisco, Susan Lynn. Indexing business records: The value proposition. Silver Spring, MD: Association for Information and Image Management International, 1998.
Znajdź pełny tekst źródłaO'Connor, Brian Clark. Doing things with information: Beyond indexing and abstracting. Westport, Conn: Libraries Unlimited, 2008.
Znajdź pełny tekst źródłaBertino, Elisa. Indexing Techniques for Advanced Database Systems. Boston, MA: Springer US, 1997.
Znajdź pełny tekst źródłaChoi, 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.
Pełny tekst źródłaGreig, Peter E. Newspaper indexes & indexing: Newspaper information storage and retrieval : a checklist, 1980-1987. [S.l: s.n., 1987.
Znajdź pełny tekst źródłaCzęści książek na temat "Storage and indexing"
Manolopoulos, Yannis, Yannis Theodoridis i Vassilis J. Tsotras. "Storage Systems". W Advanced Database Indexing, 1–16. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4419-8590-3_1.
Pełny tekst źródłaPalladino, Santiago. "Indexing and Storage". W Ethereum for Web Developers, 181–214. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5278-9_6.
Pełny tekst źródłaFeng, Dan. "Indexing Schemes". W 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.
Pełny tekst źródłaStrate, Jason, i Grant Fritchey. "Index Storage Fundamentals". W Expert Performance Indexing in SQL Server, 15–54. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-1118-2_2.
Pełny tekst źródłaStrate, Jason. "Index Storage Fundamentals". W 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.
Pełny tekst źródłaStrate, Jason, i Ted Krueger. "Index Storage Fundamentals". W 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.
Pełny tekst źródłaKorotkevitch, Dmitri. "Special Indexing and Storage Features". W Pro SQL Server Internals, 81–110. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1964-5_4.
Pełny tekst źródłaKorotkevitch, Dmitri. "Special Indexing and Storage Features". W Pro SQL Server Internals, 81–112. Berkeley, CA: Apress, 2014. http://dx.doi.org/10.1007/978-1-4302-5963-3_4.
Pełny tekst źródłaPollack, Edward, i Jason Strate. "Index Storage Fundamentals". W 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.
Pełny tekst źródłaGibbons, Philip B. "Data Storage and Indexing in Sensor Networks". W Encyclopedia of Database Systems, 635–38. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_112.
Pełny tekst źródłaStreszczenia konferencji na temat "Storage and indexing"
Alsubaiee, Sattam, Michael J. Carey i Chen Li. "LSM-Based Storage and Indexing". W SIGMOD/PODS'15: International Conference on Management of Data. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2786006.2786007.
Pełny tekst źródłaWei, Hai, i Lansun Shen. "Fractal-based image storage and indexing". W Electronic Imaging, redaktorzy Minerva M. Yeung, Boon-Lock Yeo i Charles A. Bouman. SPIE, 1999. http://dx.doi.org/10.1117/12.373574.
Pełny tekst źródłaPanwar, Ajeet Pal Singh, Devendra Kumar i Jaydesh Chandra. "Hierarchal data storage using NAI indexing". W 2017 3rd International Conference on Advances in Computing,Communication & Automation (ICACCA) (Fall). IEEE, 2017. http://dx.doi.org/10.1109/icaccaf.2017.8344687.
Pełny tekst źródłaPaul, Arnab K., Brian Wang, Nathan Rutman, Cory Spitz i Ali R. Butt. "Efficient Metadata Indexing for HPC Storage Systems". W 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.
Pełny tekst źródła"Session details: Industry 2: Storage & Indexing". W the 2019 International Conference, Chair Alexander Shraer. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3299869.3341283.
Pełny tekst źródłaSima, Jin, Netanel Raviv i Jehoshua Bruck. "Robust Indexing - Optimal Codes for DNA Storage". W 2020 IEEE International Symposium on Information Theory (ISIT). IEEE, 2020. http://dx.doi.org/10.1109/isit44484.2020.9174447.
Pełny tekst źródłaBarreto, João, i Paulo Ferreira. "Efficient file storage using content-based indexing". W the twentieth ACM symposium. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1095810.1118597.
Pełny tekst źródłaShraer, Alexander. "Session details: Industry 2: Storage & Indexing". W SIGMOD/PODS '19: International Conference on Management of Data. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3341283.
Pełny tekst źródłaWeintraub, Grisha, Ehud Gudes i Shlomi Dolev. "Indexing cloud data lakes within the lakes". W SYSTOR '21: The 14th ACM International Systems and Storage Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3456727.3463828.
Pełny tekst źródłaSmith, Mark, i Alireza Khotanzad. "Efficient Indexing and Storage Algorithm for Visual Databases". W 2008 Fifth International Conference on Information Technology: New Generations (ITNG). IEEE, 2008. http://dx.doi.org/10.1109/itng.2008.162.
Pełny tekst źródłaRaporty organizacyjne na temat "Storage and indexing"
Bethel, E. Wes, Luke Gosink, John Shalf, Kurt Stockinger i Kesheng Wu. HDF5-FastQuery: An API for Simplifying Access to Data Storage,Retrieval, Indexing and Querying. Office of Scientific and Technical Information (OSTI), czerwiec 2006. http://dx.doi.org/10.2172/888964.
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