Bibliografías temáticas / Text Data Streams

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Literatura académica sobre el tema "Text Data Streams"

Autor: Grafiati
Publicado: 28 de diciembre de 2024
Última modificación: 31 de julio de 2025

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Artículos de revistas sobre el tema "Text Data Streams"

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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 (2008): 112–28. http://dx.doi.org/10.1007/s11390-008-9115-1.

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Aggarwal, Charu C., and Philip S. Yu. "On clustering massive text and categorical data streams." Knowledge and Information Systems 24, no. 2 (2009): 171–96. http://dx.doi.org/10.1007/s10115-009-0241-z.

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FRAHLING, GEREON, PIOTR INDYK, and CHRISTIAN SOHLER. "SAMPLING IN DYNAMIC DATA STREAMS AND APPLICATIONS." International Journal of Computational Geometry & Applications 18, no. 01n02 (2008): 3–28. http://dx.doi.org/10.1142/s0218195908002520.

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A dynamic geometric data stream is a sequence of m ADD/REMOVE operations of points from a discrete geometric space {1,…, Δ} d ?. ADD (p) inserts a point p from {1,…, Δ} d into the current point set P , REMOVE(p) deletes p from P . We develop low-storage data structures to (i) maintain ε-nets and ε-approximations of range spaces of P with small VC-dimension and (ii) maintain a (1 + ε)-approximation of the weight of the Euclidean minimum spanning tree of P . Our data structure for ε-nets uses [Formula: see text] bits of memory and returns with probability 1 – δ a set of [Formula: see text] point
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Zhang, 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.

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Russo, 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 (2023): 2897–910. http://dx.doi.org/10.14778/3611479.3611496.

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Analysts and scientists are interested in querying streams of video, audio, and text to extract quantitative insights. For example, an urban planner may wish to measure congestion by querying the live feed from a traffic camera. Prior work has used deep neural networks (DNNs) to answer such queries in the batch setting. However, much of this work is not suited for the streaming setting because it requires access to the entire dataset before a query can be submitted or is specific to video. Thus, to the best of our knowledge, no prior work addresses the problem of efficiently answering queries
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Devendra, Kumar Mishra*1. "CHALLENGES IN TEXT MINING FOR BUSINESS INTELLIGENCE." International Journal of Engineering Technologies and Management Research 5, no. 2 (SE) (2018): 301–4. https://doi.org/10.5281/zenodo.1247479.

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Today is the era of internet; the internet represents a big space where large amounts of data are added every day. This huge amount of digital data and interconnection exploding data. Big Data mining have the capability to retrieving useful information in large datasets or streams of data. Analysis can also be done in a distributed environment. The framework needed for analysis to this large amount of data must support statistical analysis and data mining. The framework should be design in such a way so that big data and traditional data can be combined, so results that come analyzing new data
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Belov, Boris, and Peter Panfilov. "Generative AI-based Approach to Concept Drift Generation in Streaming Text Data." WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS 22 (October 21, 2024): 11–20. https://doi.org/10.37394/23209.2025.22.2.

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Real-time analysis of text streams is crucial for industrial and business processes and scenarios. It is expected to be one of the important future research topics in the text processing and understanding domain. Analysis of text data is based on the use of pre-trained machine learning/data mining (ML/DM) models that may demonstrate performance degradation over time due to the drift in text data. The problem of tracking drift in data and quickly retraining a model in response to changes in the operational environment represents a great challenge in product model environments. We discuss and ev
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Petrasova, 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.

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Currently, the volume of news data streams is growing that contributes to increasing interest in systems that allow automating the big data streams processing. Based on intelligent data processing tools, the semantic similarity identification of text information will make it possible to select common information spaces of news. The article analyzes up-to-date statistical metrics for identifying coherent fragments, in particular, from news texts displaying the agenda, identifies the main advantages and disadvantages as well. The information technology is proposed for identifying the common info
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AL-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 (2020): 916–35. http://dx.doi.org/10.3844/jcssp.2020.916.935.

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Hasan, 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 (2018): 35–51. http://dx.doi.org/10.1007/s41060-018-0096-z.

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Tesis sobre el tema "Text Data Streams"

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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.

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Data mining in text streams, or text stream mining, is an increasingly im- portant topic for a number of reasons, including the recent explosion in the availability of textual data and an increasing need for people and organi- sations to process and understand as much of that information as possible, from single users to multinational corporations and governments. In this thesis we present a data structure based on a generalised suffix tree which is capable of solving a number of text stream mining tasks. It can be used to detect changes in the text stream, detect when chunks of text are reuse
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Mejova, Yelena Aleksandrovna. "Sentiment analysis within and across social media streams." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/2943.

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Social media offers a powerful outlet for people's thoughts and feelings -- it is an enormous ever-growing source of texts ranging from everyday observations to involved discussions. This thesis contributes to the field of sentiment analysis, which aims to extract emotions and opinions from text. A basic goal is to classify text as expressing either positive or negative emotion. Sentiment classifiers have been built for social media text such as product reviews, blog posts, and even Twitter messages. With increasing comple
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Hill, 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.

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Ben-Fares, Maha. "Apprentissage de représentation non supervisé de flux de données textuelles." Electronic Thesis or Diss., CY Cergy Paris Université, 2024. http://www.theses.fr/2024CYUN1316.

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Cette thèse présente des méthodes innovantes pour le regroupement de flux de données textuelles et introduit également un système d'identification des textes générés par l'IA. Cette méthode de détection de l'IA peut être utilisée indépendamment ou comme étape de prétraitement pour filtrer les documents entrants, en supprimant le contenu généré par l'IA et en préservant l'authenticité et la validité de l'information.Plus précisément, nous développons un système de classification qui distingue entre le texte écrit par des humains et celui généré par l'IA. Pour ce faire, cette méthode utilise une
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Pinho, 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/.

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Representações visuais têm sido adotadas na exploração de conjuntos de documentos, auxiliando a extração de conhecimento sem que seja necessária a análise individual de milhares de textos. Mapas de documentos, em particular, apresentam documentos individualmente representados espalhados em um espaço visual, refletindo suas relações de similaridade ou conexões. A construção destes mapas de documentos inclui, entre outras tarefas, o posicionamento dos textos e a identificação automática de áreas temáticas. Um desafio é a visualização de conjuntos dinâmicos de documentos. Na visualização de infor
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Wu, Yingyu. "Using Text based Visualization in Data Analysis." Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1398079502.

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Young, Tom, and Mark Wigent. "Dynamic Formatting of the Test Article Data Stream." International Foundation for Telemetering, 2010. http://hdl.handle.net/10150/605948.

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ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California
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Crossman, 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.

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Franco, Tom. "Performing Frame Transformations to Correctly Stream Position Data." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1491562251744704.

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Vickers, Stephen R. "Examining the Duplication of Flight Test Data Centers." International Foundation for Telemetering, 2011. http://hdl.handle.net/10150/595653.

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ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada<br>Aircraft 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 geographic
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Libros sobre el tema "Text Data Streams"

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Dufort, Benoit, та Gordon W. Roberts. Analog Test Signal Generation Using Periodic ΣΔ-Encoded Data Streams. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4377-0.

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1959-, Roberts Gordon W., ed. Analog test signal generation using periodic [sigma delta]-encoded data streams. Kluwer Academic, 2000.

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Dufort, Benoit. Analog test signal generation using periodic [sigma delta]-encoded data streams. Springer Science+Business Media, 2000.

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Verderaime, V. Test load verification through strain data analysis. National Aeronautics and Space Administration, 1995.

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Lane, Norman E. Users manual for the Automated Performance Test System (APTS). Essex Corp., 1990.

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Swarts, 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.

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Analyzing streams of language: Twelve steps to the systematic coding of text, talk, and other verbal data. Longman, 2003.

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Giacovazzo, Carmelo. Phasing in Crystallography. Oxford University Press, 2013. http://dx.doi.org/10.1093/oso/9780199686995.001.0001.

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Modern crystallographic methods originate from the synergy of two main research streams, the small-molecule and the macro-molecular streams. The first stream was able to definitively solve the phase problem for molecules up to 200 atoms in the asymmetric unit. The achievements obtained by the macromolecular stream are also impressive. A huge number of protein structures have been deposited in the Protein Data Bank. The solution of them is no longer reserved to an elite group of scientists, but may be attained in a large number of laboratories around the world, even by young scientists. New pro
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Analog Test Signal Generation Using Periodic -Encoded Data Streams. Island Press, 2000.

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Test load verification through strain data analysis. National Aeronautics and Space Administration, Marshall Space Flight Center, 1995.

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Capítulos de libros sobre el tema "Text Data Streams"

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Aggarwal, Charu C. "Mining Text Streams." In Mining Text Data. Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-3223-4_9.

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Joshi, Basanta, Umanga Bista, and Manoj Ghimire. "Intelligent Clustering Scheme for Log Data Streams." In Computational Linguistics and Intelligent Text Processing. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54903-8_38.

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Rothkrantz, Leon J. M., Jacek C. Wojdeł, and Pascal Wiggers. "Fusing Data Streams in Continuous Audio-Visual Speech Recognition." In Text, Speech and Dialogue. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11551874_5.

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Liu, 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. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73871-8_36.

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Feng, 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. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23862-3_21.

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Fung, 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. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24775-3_45.

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Bosch, Harald, Robert Krüger, and Dennis Thom. "Data-Driven Exploration of Real-Time Geospatial Text Streams." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23461-8_14.

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Windmann, Stefan, and Christian Kühnert. "Information modeling and knowledge extraction for machine learning applications in industrial production systems." In Machine Learning for Cyber Physical Systems. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62746-4_8.

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AbstractIn this paper, a new information model for machine learning applications is introduced, which allows for a consistent acquisition and semantic annotation of process data, structural information and domain knowledge from industrial productions systems. The proposed information model is based on Industry 4.0 components and IEC 61360 component descriptions. To model sensor data, components of the OGC SensorThings model such as data streams and observations have been incorporated in this approach. Machine learning models can be integrated into the information model in terms of existing mod
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Weik, Martin H. "text data stream." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_19461.

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Wittenberg, Thomas, Thomas Lang, Thomas Eixelberger, and Roland Grube. "Acquisition of Semantics for Machine-Learning and Deep-Learning based Applications." In Unlocking Artificial Intelligence. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64832-8_8.

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AbstractFor the development, training, and validation of machine learning (ML) and deep learning (DL) based methods, such as, e.g., image analysis, prediction of critical events, extraction or reconstruction of information from disrupted data streams, searching similarities in data collections, or planning of procedures, a lot of data is needed. Additionally to this data (images, bio-signals, vital-signs, text records, machine states, trajectories, antenna data, ...) adequate supplementary information about the meaning encoded in the data is required. Only with this additional information – th
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Actas de conferencias sobre el tema "Text Data Streams"

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Rajski, Janusz, Maciej Trawka, Jerzy Tyszer, and Bartosz Włodarczak. "Test Data Encryption with a New Stream Cipher." In 2024 IEEE International Test Conference (ITC). IEEE, 2024. http://dx.doi.org/10.1109/itc51657.2024.00052.

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Leão Imai, Bruno Yuiti, Cristiano Mesquita Garcia, Marcio Vinicius Rocha, Alessandro Lameiras Koerich, Alceu De Souza Britto, and Jean Paul Barddal. "Is it Fine to Tune? Evaluating SentenceBERT Fine-tuning for Brazilian Portuguese Text Stream Classification." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825456.

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Ahmad, 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). IEEE, 2024. http://dx.doi.org/10.1109/aidas63860.2024.10730385.

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Malonjao, Ray H., Juvy B. Malonjao, and Philip John Borromeo. "Friedman Chi-Square Test Analysis of Carbon Steel Tensile Stress Data Using Python." In 2024 IEEE International Conference on Technology, Informatics, Management, Engineering and Environment (TIME-E). IEEE, 2024. https://doi.org/10.1109/time-e62724.2024.10919828.

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Zuo, 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). IEEE, 2024. http://dx.doi.org/10.23919/date58400.2024.10546799.

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Calvo Martinez, John. "Event Mining over Distributed Text Streams." In WSDM 2018: The Eleventh ACM International Conference on Web Search and Data Mining. ACM, 2018. http://dx.doi.org/10.1145/3159652.3170462.

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He, 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. Society for Industrial and Applied Mathematics, 2007. http://dx.doi.org/10.1137/1.9781611972771.50.

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Whitney, Paul, Dave Engel, and Nick Cramer. "Mining for Surprise Events Within Text Streams." In Proceedings of the 2009 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2009. http://dx.doi.org/10.1137/1.9781611972795.53.

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Yin, 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. ACM, 2018. http://dx.doi.org/10.1145/3219819.3220094.

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Zhang, 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.

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Informes sobre el tema "Text Data Streams"

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Hajj, Ramez, and Babak Asadi. Review of Illinois Multiple Stress Creep and Recovery Data for Future Implementation. Illinois Center for Transportation, 2023. http://dx.doi.org/10.36501/0197-9191/23-027.

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The multiple stress creep recovery (MSCR) test, per AASHTO M 332, or as a supplement to M 320, has been widely implemented across the United States and in other parts of the world for assessing the rutting resistance of asphalt binder. Meanwhile, the Illinois Department of Transportation (IDOT) has conducted wide-ranging MSCR testing since 2006 but has not yet implemented this test into the binder specification, which utilizes AASHTO M 320 with other PG Plus tests for modified asphalt binder. This report presents a review of the existing literature and an update of specifications in the United
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George, D. L., and R. C. Burkey. PR-015-06603-R01 Tests of Instruments for Measuring Hydrocarbon Dew Points in Natural Gas Streams Phase 1. Pipeline Research Council International, Inc. (PRCI), 2008. http://dx.doi.org/10.55274/r0010820.

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Two commercially-available hydrocarbon dew point analyzers, an Ametek� Model 241 CE II and a Michell Condumax II, were provided by JIP participants for testing. An experimental HCDP research apparatus, first designed at Southwest Research Institute to gather reference hydrocarbon dew point data, was modified to test the automated analyzers. Both automated analyzers, along with a Bureau of Mines chilled mirror device serving as a reference, were installed in the apparatus. Gravimetrically-prepared gas blends containing hydrocarbons through decane were used as test gases, and a small warm box wa
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Messner, Mark. Modified 316H constitutive model updated with high temperature stress relaxation test data. Office of Scientific and Technical Information (OSTI), 2025. https://doi.org/10.2172/2564966.

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Ginzel. L51748 Detection of Stress Corrosion Induced Toe Cracks-Advancement of the Developed Technique. Pipeline Research Council International, Inc. (PRCI), 1996. http://dx.doi.org/10.55274/r0010659.

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In the past few years an ongoing problem has existed with stress corrosion cracking (SCC) in pipelines around the world. Several member companies of the Pipeline Research Council International, Inc. have experienced multiple incidents as a result of ERW defects and SCC. TCPL is running a series of hydrostatic tests and trial digs to identify the most severely affected areas. These excavations and failure studies have ascertained that most of the SCC causing failure has been on the outside diameter of long seam welded pipe at the edge of the weld. Defects at that location are known as "Toe-Crac
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George. PR-015-08610-R01 Laboratory Conformation of the Effect of Methanol on Gas Chromatograph Performance. Pipeline Research Council International, Inc. (PRCI), 2010. http://dx.doi.org/10.55274/r0010717.

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In natural gas production and processing applications, methanol is commonly injected into natural gas streams containing water to prevent the formation of hydrates in gas lines and subsequent equipment damage. However, gas chromatographs (GCs) at field sites are typically not equipped to identify or measure methanol, and unless excess methanol is expected to carry over into a gas stream, samples sent to a laboratory are not likely to be analyzed for methanol. As a result, the potential exists for errors in gas property determination, particularly in heating value and sound speed. A previous PR
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Zevotek, 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, 2018. http://dx.doi.org/10.54206/102376/dnyq2164.

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As research continues into how fire department interventions affect fire dynamics in the modern fire environment, questions continue to arise on the impact and implications of interior versus exterior fire attack on both occupant survivability and firefighter safety. This knowledge gap and lack of previous research into the impact of fire streams has driven the need for further research into fire department interventions at structure fires with a focus on hose streams and suppression tactics. As the third report in the project “Impact of Fire Attack Utilizing Interior and Exterior Streams on F
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Parkins and Leis. L51654 Spatial Densities of Stress-Corrosion Cracks in Line-Pipe Steels. Pipeline Research Council International, Inc. (PRCI), 1992. http://dx.doi.org/10.55274/r0010367.

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There was a need to define the spatial density of stress-corrosion crack arrays that develop in operating gas-transmission pipelines and in laboratory test specimens of line-pipe steel, to improve understanding of the factors that control the density and provide data to test models of pipeline cracking. Within the broad definition of crack density are included the locations, numbers, lengths, depths, and degree of linkage of cracks. An analysis has been conducted of location, numbers, lengths, depths, and degree of linkage of stress-corrosion crack colonies in samples from the field and from l
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Vaughn, Tim, and Daniel Olsen. PR-179-19601-R03 Evaluation of Online Analyzers for Multiple Gas Contaminants-Field Test. Pipeline Research Council International, Inc. (PRCI), 2022. http://dx.doi.org/10.55274/r0012242.

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Operating companies currently use several analyzers per location to monitor gas streams throughout their operations. By replacing multiple analyzers with a single analyzer capable of measuring multiple contaminants, both capital and operations and maintenance expenditures can be reduced. A field trial of two commercially available on-line analyzers was conducted between February 2021 and February 2022. The analyzers (ABB LGR-ICOS 950, AP2e ProCeas) were sited at an operational gas compression facility, whose own process gas analyzers were used as reference analyzers for comparison ("Site Ref")
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9

Leis, B. N., O. C. Chang, and T. A. Bubenik. GTI-000232 Leak vs Rupture for Steel Low-Stress Pipelines. Pipeline Research Council International, Inc. (PRCI), 2001. http://dx.doi.org/10.55274/r0011871.

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Pipeline codes and regulations worldwide have less stringent requirements for low-wall stress pipelines. Factors underlying this include a reduced exposure zone as pipeline pressure decreases and the expectation that leaks occur for lower wall stress. This report evaluates leak versus rupture as a function of wall stress with a focus on pipelines operating between 20 to 40 percent of the specified minimum yield stress. Potential threats to the integrity of low-stress pipelines are identified and worst-case scenarios for these threats evaluated to determine leak versus rupture as a function of
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Gutiérrez, José E., and Luis Fernández Lafuerza. Credit line runs and bank risk management: evidence from the disclosure of stress test results. Banco de España, 2022. http://dx.doi.org/10.53479/25006.

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As noted in recent literature, firms can run on credit lines due to fear of future credit restrictions. We exploit the 2011 stress test supervised by the European Banking Authority (EBA) and the Spanish Central Credit Register to explore: 1) the occurrence and magnitude of these runs after the release of negative stress test results; and 2) banks’ behaviour before and after the release of this information. We find that, following the release of the results, firms drew down approximately 10 pp more available funds from lines granted by banks that had a worse performance in the stress test. More
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