Academic literature on the topic 'Text Data Streams'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Text Data Streams.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Text Data Streams"
Liu, Yu-Bao, Jia-Rong Cai, Jian Yin, and Ada Wai-Chee Fu. "Clustering Text Data Streams." Journal of Computer Science and Technology 23, no. 1 (January 2008): 112–28. http://dx.doi.org/10.1007/s11390-008-9115-1.
Full textAggarwal, Charu C., and Philip S. Yu. "On clustering massive text and categorical data streams." Knowledge and Information Systems 24, no. 2 (August 6, 2009): 171–96. http://dx.doi.org/10.1007/s10115-009-0241-z.
Full textFRAHLING, GEREON, PIOTR INDYK, and CHRISTIAN SOHLER. "SAMPLING IN DYNAMIC DATA STREAMS AND APPLICATIONS." International Journal of Computational Geometry & Applications 18, no. 01n02 (April 2008): 3–28. http://dx.doi.org/10.1142/s0218195908002520.
Full textZhang, Yuhong, Guang Chu, Peipei Li, Xuegang Hu, and Xindong Wu. "Three-layer concept drifting detection in text data streams." Neurocomputing 260 (October 2017): 393–403. http://dx.doi.org/10.1016/j.neucom.2017.04.047.
Full textRusso, Matthew, Tatsunori Hashimoto, Daniel Kang, Yi Sun, and Matei Zaharia. "Accelerating Aggregation Queries on Unstructured Streams of Data." Proceedings of the VLDB Endowment 16, no. 11 (July 2023): 2897–910. http://dx.doi.org/10.14778/3611479.3611496.
Full textPetrasova, Svitlana, Nina Khairova, and Anastasiia Kolesnyk. "TECHNOLOGY FOR IDENTIFICATION OF INFORMATION AGENDA IN NEWS DATA STREAMS." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 1 (5) (July 12, 2021): 86–90. http://dx.doi.org/10.20998/2079-0023.2021.01.14.
Full textAL-Dyani, Wafa Zubair, Farzana Kabir Ahmad, and Siti Sakira Kamaruddin. "A Survey on Event Detection Models for Text Data Streams." Journal of Computer Science 16, no. 7 (July 1, 2020): 916–35. http://dx.doi.org/10.3844/jcssp.2020.916.935.
Full textHasan, Maryam, Elke Rundensteiner, and Emmanuel Agu. "Automatic emotion detection in text streams by analyzing Twitter data." International Journal of Data Science and Analytics 7, no. 1 (February 9, 2018): 35–51. http://dx.doi.org/10.1007/s41060-018-0096-z.
Full textZhao, Xuezhuan, Ziheng Zhou, Lingling Li, Lishen Pei, and Zhaoyi Ye. "Scene Text Detection Based On Fusion Network." International Journal of Pattern Recognition and Artificial Intelligence 35, no. 10 (May 29, 2021): 2153005. http://dx.doi.org/10.1142/s0218001421530050.
Full textAzkan, Can, Markus Spiekermann, and Henry Goecke. "Uncovering Research Streams in the Data Economy Using Text Mining Algorithms." Technology Innovation Management Review 9, no. 11 (January 1, 2019): 62–74. http://dx.doi.org/10.22215/timreview/1284.
Full textDissertations / Theses on the topic "Text Data Streams"
Snowsill, Tristan. "Data mining in text streams using suffix trees." Thesis, University of Bristol, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556708.
Full textMejova, Yelena Aleksandrovna. "Sentiment analysis within and across social media streams." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/2943.
Full textHill, Geoffrey. "Sensemaking in Big Data: Conceptual and Empirical Approaches to Actionable Knowledge Generation from Unstructured Text Streams." Kent State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=kent1433597354.
Full textPinho, Roberto Dantas de. "Espaço incremental para a mineração visual de conjuntos dinâmicos de documentos." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-14092009-123807/.
Full textVisual representations are often adopted to explore document collections, assisting in knowledge extraction, and avoiding the thorough analysis of thousands of documents. Document maps present individual documents in visual spaces in such a way that their placement reflects similarity relations or connections between them. Building these maps requires, among other tasks, placing each document and identifying interesting areas or subsets. A current challenge is to visualize dynamic data sets. In Information Visualization, adding and removing data elements can strongly impact the underlying visual space. That can prevent a user from preserving a mental map that could assist her/him on understanding the content of a growing collection of documents or tracking changes on the underlying data set. This thesis presents a novel algorithm to create dynamic document maps, capable of maintaining a coherent disposition of elements, even for completely renewed sets. The process is inherently incremental, has low complexity and places elements on a 2D grid, analogous to a chess board. Consistent results were obtained as compared to (non-incremental) multidimensional scaling solutions, even when applied to visualizing domains other than document collections. Moreover, the corresponding visualization is not susceptible to occlusion. To assist users in indentifying interesting subsets, a topic extraction technique based on association rule mining was also developed. Together, they create a visual space where topics and interesting subsets are highlighted and constantly updated as the data set changes
Wu, Yingyu. "Using Text based Visualization in Data Analysis." Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1398079502.
Full textYoung, Tom, and Mark Wigent. "Dynamic Formatting of the Test Article Data Stream." International Foundation for Telemetering, 2010. http://hdl.handle.net/10150/605948.
Full textCrossman, Nathaniel C. "Stream Clustering And Visualization Of Geotagged Text Data For Crisis Management." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1590957641168863.
Full textFranco, Tom. "Performing Frame Transformations to Correctly Stream Position Data." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1491562251744704.
Full textVickers, Stephen R. "Examining the Duplication of Flight Test Data Centers." International Foundation for Telemetering, 2011. http://hdl.handle.net/10150/595653.
Full textAircraft flight test data processing began with on site data analysis from the very first aircraft design. This method of analyzing flight data continued from the early 1900's to the present day. Today each new aircraft program builds a separate data center for post flight processing (PFP) to include operations, system administration, and management. Flight Test Engineers (FTE) are relocated from geographical areas to ramp up the manpower needed to analyze the PFP data center products and when the first phase of aircraft design and development is completed the FTE headcount is reduced with the FTE either relocated to another program or the FTE finds other employment. This paper is a condensed form of the research conducted by the author on how the methodology of continuing to build PFP data centers cost the aircraft company millions of dollars in development and millions of dollars on relocation plus relocation stress effects on FTE which can hinder productivity. This method of PFP data center development can be avoided by the consolidation of PFP data centers using present technology.
Yates, James William. "Mixing Staged Data Flow and Stream Computing Techniques in Modern Telemetry Data Acquisition/Processing Architectures." International Foundation for Telemetering, 1999. http://hdl.handle.net/10150/608707.
Full textToday’s flight test processing systems must handle many more complex data formats than just the PCM and analog FM data streams of yesterday. Many flight test programs, and their respective test facilities, are looking to leverage their computing assets across multiple customers and programs. Typically, these complex programs require the ability to handle video, packet, and avionics bus data in real time, in addition to handling the more traditional PCM format. Current and future telemetry processing systems must have an architecture that will support the acquisition and processing of these varied data streams. This paper describes various architectural designs of both staged data flow and stream computing architectures, including current and future implementations. Processor types, bus design, and the effects of varying data types, including PCM, video, and packet telemetry, will be discussed.
Books on the topic "Text Data Streams"
Dufort, Benoit, and Gordon W. Roberts. Analog Test Signal Generation Using Periodic ΣΔ-Encoded Data Streams. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4377-0.
Full text1959-, Roberts Gordon W., ed. Analog test signal generation using periodic [sigma delta]-encoded data streams. Boston: Kluwer Academic, 2000.
Find full textDufort, Benoit. Analog test signal generation using periodic [sigma delta]-encoded data streams. New York: Springer Science+Business Media, 2000.
Find full textVerderaime, V. Test load verification through strain data analysis. Washington, DC: National Aeronautics and Space Administration, 1995.
Find full textLane, Norman E. Users manual for the Automated Performance Test System (APTS). Orlando, FL: Essex Corp., 1990.
Find full textSwarts, Jason, and Cheryl Geisler. Coding Streams of Language: Techniques for the Systematic Coding of Text, Talk, and Other Verbal Data. University Press of Colorado, 2020.
Find full textAnalyzing streams of language: Twelve steps to the systematic coding of text, talk, and other verbal data. New York: Longman, 2003.
Find full textGiacovazzo, Carmelo. Phasing in Crystallography. Oxford University Press, 2013. http://dx.doi.org/10.1093/oso/9780199686995.001.0001.
Full textAnalog Test Signal Generation Using Periodic -Encoded Data Streams. Island Press, 2000.
Find full textTest load verification through strain data analysis. MSFC, Ala: National Aeronautics and Space Administration, Marshall Space Flight Center, 1995.
Find full textBook chapters on the topic "Text Data Streams"
Aggarwal, Charu C. "Mining Text Streams." In Mining Text Data, 297–321. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-3223-4_9.
Full textJoshi, Basanta, Umanga Bista, and Manoj Ghimire. "Intelligent Clustering Scheme for Log Data Streams." In Computational Linguistics and Intelligent Text Processing, 454–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54903-8_38.
Full textRothkrantz, Leon J. M., Jacek C. Wojdeł, and Pascal Wiggers. "Fusing Data Streams in Continuous Audio-Visual Speech Recognition." In Text, Speech and Dialogue, 33–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11551874_5.
Full textLiu, Yubao, Jiarong Cai, Jian Yin, and Ada Wai-Chee Fu. "Clustering Massive Text Data Streams by Semantic Smoothing Model." In Advanced Data Mining and Applications, 389–400. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73871-8_36.
Full textFeng, Xiao, Shuwu Zhang, Wei Liang, and Jie Liu. "Efficient Location-Based Event Detection in Social Text Streams." In Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques, 213–22. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23862-3_21.
Full textFung, Gabriel Pui Cheong, Jeffrey Xu Yu, and Hongjun Lu. "Classifying Text Streams in the Presence of Concept Drifts." In Advances in Knowledge Discovery and Data Mining, 373–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24775-3_45.
Full textBosch, Harald, Robert Krüger, and Dennis Thom. "Data-Driven Exploration of Real-Time Geospatial Text Streams." In Machine Learning and Knowledge Discovery in Databases, 203–7. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23461-8_14.
Full textWindmann, Stefan, and Christian Kühnert. "Information modeling and knowledge extraction for machine learning applications in industrial production systems." In Machine Learning for Cyber Physical Systems, 73–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62746-4_8.
Full textWeik, Martin H. "text data stream." In Computer Science and Communications Dictionary, 1773. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_19461.
Full textWittenberg, Thomas, Thomas Lang, Thomas Eixelberger, and Roland Grube. "Acquisition of Semantics for Machine-Learning and Deep-Learning based Applications." In Unlocking Artificial Intelligence, 153–75. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64832-8_8.
Full textConference papers on the topic "Text Data Streams"
Rajski, Janusz, Maciej Trawka, Jerzy Tyszer, and Bartosz Włodarczak. "Test Data Encryption with a New Stream Cipher." In 2024 IEEE International Test Conference (ITC), 313–22. IEEE, 2024. http://dx.doi.org/10.1109/itc51657.2024.00052.
Full textAhmad, Zaaba, Azlinah Mohamed, Mike Conway, Rozanizam Zakaria, Noor Hasimah Ibrahim Teo, and Ruhaila Maskat. "MyDAS Corpus: Malay Social Media Texts for Detecting Depression, Anxiety, and Stress on Facebook." In 2024 5th International Conference on Artificial Intelligence and Data Sciences (AiDAS), 111–20. IEEE, 2024. http://dx.doi.org/10.1109/aidas63860.2024.10730385.
Full textZuo, Yunfan, Yuyang Ye, Hongchao Zhang, Tinghuan Chen, Hao Yan, and Longxing Shi. "A Graph-Learning-Driven Prediction Method for Combined Electromigration and Thermomigration Stress on Multi-Segment Interconnects." In 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1–6. IEEE, 2024. http://dx.doi.org/10.23919/date58400.2024.10546799.
Full textCalvo Martinez, John. "Event Mining over Distributed Text Streams." In WSDM 2018: The Eleventh ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3159652.3170462.
Full textHe, Qi, Kuiyu Chang, Ee-Peng Lim, and Jun Zhang. "Bursty Feature Representation for Clustering Text Streams." In Proceedings of the 2007 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2007. http://dx.doi.org/10.1137/1.9781611972771.50.
Full textWhitney, Paul, Dave Engel, and Nick Cramer. "Mining for Surprise Events Within Text Streams." In Proceedings of the 2009 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2009. http://dx.doi.org/10.1137/1.9781611972795.53.
Full textYin, Jianhua, Daren Chao, Zhongkun Liu, Wei Zhang, Xiaohui Yu, and Jianyong Wang. "Model-based Clustering of Short Text Streams." In KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3219819.3220094.
Full textZhang, Yang, Xue Li, and Maria Orlowska. "One-Class Classification of Text Streams with Concept Drift." In 2008 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2008. http://dx.doi.org/10.1109/icdmw.2008.54.
Full textSun, Gang, Jianqiao Liu, Wei Mengxue, Wang Zhongxin, Zhao Jia, and Guan Xiaowen. "An Ensemble Classification Algorithm for Imbalanced Text Data Streams." In 2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2020. http://dx.doi.org/10.1109/icaica50127.2020.9182576.
Full textWang, Xiting, Shixia Liu, Yangqiu Song, and Baining Guo. "Mining evolutionary multi-branch trees from text streams." In KDD' 13: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2487575.2487603.
Full textReports on the topic "Text Data Streams"
Hajj, Ramez, and Babak Asadi. Review of Illinois Multiple Stress Creep and Recovery Data for Future Implementation. Illinois Center for Transportation, December 2023. http://dx.doi.org/10.36501/0197-9191/23-027.
Full textGeorge, D. L., and R. C. Burkey. PR-015-06603-R01 Tests of Instruments for Measuring Hydrocarbon Dew Points in Natural Gas Streams Phase 1. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), January 2008. http://dx.doi.org/10.55274/r0010820.
Full textGinzel. L51748 Detection of Stress Corrosion Induced Toe Cracks-Advancement of the Developed Technique. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), March 1996. http://dx.doi.org/10.55274/r0010659.
Full textGeorge. PR-015-08610-R01 Laboratory Conformation of the Effect of Methanol on Gas Chromatograph Performance. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), November 2010. http://dx.doi.org/10.55274/r0010717.
Full textZevotek, Robin, Keith Stakes, and Joseph Willi. Impact of Fire Attack Utilizing Interior and Exterior Streams on Firefighter Safety and Occupant Survival: Full-Scale Experiments. UL Firefighter Safety Research Institute, January 2018. http://dx.doi.org/10.54206/102376/dnyq2164.
Full textParkins and Leis. L51654 Spatial Densities of Stress-Corrosion Cracks in Line-Pipe Steels. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), April 1992. http://dx.doi.org/10.55274/r0010367.
Full textVaughn, Tim, and Daniel Olsen. PR-179-19601-R03 Evaluation of Online Analyzers for Multiple Gas Contaminants-Field Test. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), September 2022. http://dx.doi.org/10.55274/r0012242.
Full textLeis, B. N., O. C. Chang, and T. A. Bubenik. GTI-000232 Leak vs Rupture for Steel Low-Stress Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), January 2001. http://dx.doi.org/10.55274/r0011871.
Full textGutiérrez, José E., and Luis Fernández Lafuerza. Credit line runs and bank risk management: evidence from the disclosure of stress test results. Madrid: Banco de España, December 2022. http://dx.doi.org/10.53479/25006.
Full textGutiérrez, José E., and Luis Fernández Lafuerza. Credit line runs and bank risk management: evidence from the disclosure of stress test results. Madrid: Banco de España, January 2023. http://dx.doi.org/10.53479/24998.
Full text