Relevant bibliographies by topics / Text Data Streams

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Text Data Streams'

Author: Grafiati
Published: 28 December 2024
Last updated: 7 July 2025

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Journal articles on the topic "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] points that is an e-net for an arbitrary fixed finite range space with VC-dimension [Formula: see text]. Our data structure for ε-approximations uses [Formula: see text] bits of memory and returns with probability 1 – δ a set of [Formula: see text] points that is an ε-approximation for an arbitrary fixed finite range space with VC-dimension [Formula: see text]. The data structure for the approximation of the weight of a Euclidean minimum spanning tree uses O ( log (1/δ)( log Δ/ε) O ( d )) space and is correct with probability at least 1 – δ. Our results are based on a new data structure that maintains a set of elements chosen (almost) uniformly at random from P .
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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 over multiple modalities of streams. In this work we propose InQuest, a system for accelerating aggregation queries on unstructured streams of data with statistical guarantees on query accuracy. InQuest leverages inexpensive approximation models ("proxies") and sampling techniques to limit the execution of an expensive high-precision model (an "oracle") to a subset of the stream. It then uses the oracle predictions to compute an approximate query answer in real-time. We theoretically analyzed InQuest and show that the expected error of its query estimates converges on stationary streams at a rate inversely proportional to the oracle budget. We evaluated our algorithm on six real-world video and text datasets and show that InQuest achieves the same root mean squared error (RMSE) as two streaming baselines with up to 5.0x fewer oracle invocations. We further show that InQuest can achieve up to 1.9x lower RMSE at a fixed number of oracle invocations than a state-of-the-art batch setting algorithm.
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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 information space of relevant news in the data stream for a certain period of time. The technology includes the logical-linguistic and distributive-statistical models for identifying collocations. The MI distributional semantic model is applied at the stage of potential collocation extraction. At the same time, regular expressions developed in accordance with the grammar of the English language make it possible to identify grammatically correct constructions. The advantage of the developed logical-linguistic model formalizing the semantic-grammatical characteristics of collocations, based on the use of algebraicpredicate operations and a semantic equivalence predicate, is that both the grammatical structure of the language and the meaning of words (collocates) are analyzed. The WordNet thesaurus is used to determine the synonymy relationship between the main and dependent collocation components. Based on the investigated corpus of news texts from the CNN and BBC services, the effectiveness of the developed technology is assessed. The analysis shows that the precision coefficient is 0.96. The use of the proposed technology could improve the quality of news streams processing. The solution to the problem of automatic identification of semantic similarity can be used to identify texts of the same domain, relevant information, extract facts and eliminate semantic ambiguity, etc.
 Keywords: data stream, agenda, logical-linguistic model, distribution-statistical model, collocation, semantic similarity, WordNet, news text corpus, precision.
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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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Zhao, 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 (2021): 2153005. http://dx.doi.org/10.1142/s0218001421530050.

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Due to the robustness resulted from scale transformation and unbalanced distribution of training samples in scene text detection task, a new fusion framework TSFnet is proposed in this paper. This framework is composed of Detection Stream, Judge Stream and Fusion Stream. In the Detection Stream, loss balance factor (LBF) is raised to improve the region proposal network (RPN). To predict the global text segmentation map, the algorithm combines regression strategy and case segmentation method. In the Judge Stream, a classification of the samples is proposed based on the Judge Map and the corresponding tags to calculate the overlap rate. As a support of Detection Stream, feature pyramid network is utilized in the algorithm to extract Judge Map and calculate LBF. In the Fusion Stream, a new fusion algorithm is raised. By fusing the output of the two streams, we can position the text area in the natural scene accurately. Finally, the algorithm is experimented on the standard data sets ICDAR 2015 and ICDAR2017-MLT. The test results show that the [Formula: see text] values are 87.8% and 67.57%, respectively, superior to the state-of-the art models. This proves that the algorithm can solve the robustness issues under the unbalance between scale transformation and training data.
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Azkan, Can, Markus Spiekermann, and Henry Goecke. "Uncovering Research Streams in the Data Economy Using Text Mining Algorithms." Technology Innovation Management Review 9, no. 11 (2019): 62–74. http://dx.doi.org/10.22215/timreview/1284.

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Dissertations / Theses on the topic "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 reused and detect events through identifying when the frequencies of phrases change in a statistically significant way. Suffix trees have been used for many years in the areas of combinatorial pattern matching and computational genomics. In this thesis we demonstrate how the suffix tree can become more widely applicable by making it possible to use suffix trees to analyse streams of data rather than static data sets, opening up a number of future avenues for research. The algorithms which we present are designed to be efficient in an on-line setting by having time complexity independent of the total amount of text seen and polynomial in the rate at which text is seen. We demonstrate the effectiveness of our methods on a large text stream comprising thousands of documents every day. This text stream is the stream of text news coming from over 600 online news outlets and the results ob- tained are of interest to news consumers, journalists and social scientists.
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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 complexity of text sources and topics, it is time to re-examine the standard sentiment extraction approaches, and possibly to re-define and enrich sentiment definition. Thus, this thesis begins by introducing a rich multi-dimensional model based on Affect Control Theory and showing its usefulness in sentiment classification. Next, unlike sentiment analysis research to date, we examine sentiment expression and polarity classification within and across various social media streams by building topical datasets. When comparing Twitter, reviews, and blogs on consumer product topics, we show that it is possible, and sometimes even beneficial, to train sentiment classifiers on text sources which are different from the target text. This is not the case, however, when we compare political discussion in YouTube comments to Twitter posts, demonstrating the difficulty of political sentiment classification. We further show that neither discussion volume or sentiment expressed in these streams correspond well to national polls, putting in question recent research linking the two. The complexity of political discussion also calls for a more specific re-definition of "sentiment" as agreement with the author's political stance. We conclude that sentiment must be defined, and tools for its analysis designed, within a larger framework of human interaction.
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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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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 informação, é comum que alterações no conjunto de dados tenham um forte impacto na organização do espaço visual, dificultando a manutenção, por parte do usuário, de um mapa mental que o auxilie na interpretação dos dados apresentados e no acompanhamento das mudanças sofridas pelo conjunto de dados. Esta tese introduz um algoritmo para a construção dinâmica de mapas de documentos, capaz de manter uma disposição coerente à medida que elementos são adicionados ou removidos. O processo, inerentemente incremental e de baixa complexidade, utiliza um espaço bidimensional dividido em células, análogo a um tabuleiro de xadrez. Resultados consistentes foram alcançados em comparação com técnicas não incrementais de projeção de dados multidimensionais, tendo sido a técnica aplicada também em outros domínios, além de conjuntos de documentos. A visualização resultante não está sujeita a problemas de oclusão. A identificação de áreas temáticas é alcançada com técnicas de extração de regras de associação representativas para a identificação automática de tópicos. A combinação da extração de tópicos com a projeção incremental de dados em um processo integrado de mineração visual de textos compõe um espaço visual em que tópicos e áreas de interesse são destacados e atualizados à medida que o conjunto de dados é modificado<br>Visual 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
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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 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.
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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.

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International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada<br>Today’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.
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Books on the topic "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 probabilistic approaches have been tailored to deal with larger structures, errors in the experimental data, and modest data resolution. Traditional phasing techniques like ab initio, molecular replacement, isomorphous replacement, and anomalous dispersion techniques have been revisited. The new approaches have been implemented in robust phasing programs, which have been organized in automatic pipelines usable even by non-experts. Protein structures, which 50 years ago could take months or even years to solve, can now be solved in a matter of hours, partly also due to technological advances in computer science. This book describes all modern crystallographic phasing methods, and introduces a new rational classification of them. A didactic approach is used, with the techniques described simply and logically in the main text, and further mathematical details confined to the Appendices for motivated readers. Numerous figures and applicative details illustrate the text.
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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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Book chapters on the topic "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 model serving frameworks like PMML or Tensorflowgraph. Based on the proposed information model, a tool chain for automatic knowledge extraction is introduced and the automatic classification of unstructured text is investigated as a particular application case for the proposed tool chain.
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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 – the meaning or knowledge – a tight relation between the raw data and the human-understandable concepts – the semantics – from the real world can be established. Nevertheless, as the amount of data needed to develop robust ML or DL methods is strongly increasing, the assessment and acquisition of the related knowledge becomes more and more challenging. Within this chapter, an overview of concepts of knowledge acquisition applied to the different examples of applications is described and evaluated. Six main groups of knowledge acquisition related to AI-based technologies have been identified, namely (1) manual annotation methods, (2) data augmentation, (3) generative networks or simulation techniques, (4) synchronized sensors, (5)Active Learning approaches, and (6) explicit knowledge modeling using semantic networks.
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Conference papers on the topic "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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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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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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Sun, 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.

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Wang, 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. ACM, 2013. http://dx.doi.org/10.1145/2487575.2487603.

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Reports on the topic "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 States for the rutting resistance of asphalt binder. The report also presents an analysis of existing MSCR data collected by IDOT and a machine learning model with the ability to predict asphalt binder elastic recovery using MSCR. This model demonstrated the potential effectiveness of MSCR to serve as an appropriate surrogate for this test, but further study is needed of Illinois mixture performance compared to MSCR to best understand how this specification can be implemented for local materials and traffic levels.
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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 was built to keep the test gases above their hydrocarbon dew points at various simulated line pressures.
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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-Cracks" Ginzel has developed an ultrasonic inspection technique that will detect both SCC colonies and toe cracks in long seam pipe. The main design objective for this research project was the selection and placement of ultrasonic transducers to combine weld, plate thickness and lamination inspection, along with SCC detection and sizing. Examination of sample pipe sections to demonstrate its success is reported. The primary stages for this research project are: �Assemble test equipment Establish test procedure System trials and data collection Evaluation of system performance and collected data Correlation of test data - Results
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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 PRCI project investigated the potential for GCs to quantify methanol as a hydrocarbon, and estimated the resulting errors on heating value and other properties. This theoretical study used assumptions about where methanol would elute on GC columns, but experimental data on GC performance in streams with methanol was unavailable to verify these assumptions. To verify the estimates of the theoretical study, this project collected experimental data on methanol elution behavior in a series of field and laboratory GCs, and established the errors in computed natural gas properties caused by methanol behavior. Three GCs used by the laboratory of a PRCI member company were nominated for testing: ABB NGC 8206 C7+ field GC, Agilent Model 7890A laboratory GC, configured for extended natural gas analysis, and Daniel Model 575 C6+ field GC. The separation columns, valve configurations, and other design features of these GCs that could influence methanol elution were reviewed. Since each GC was predicted to respond differently to methanol, the nominated units were accepted for testing. A fourth GC, a Varian CP-4900 Quad MicroGC outfitted to quantify methanol, was provided to the lab to serve as a reference unit. Hydrocarbon base gas compositions were chosen to represent production and transmission gases and a gas blender was consulted to identify an effective method of stabilizing the methanol content of the test gases delivered to the GCs. Lab personnel and the gas blender then provided the required hardware and the test and calibration gases, with the gas blend compositions traceable to NIST.
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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 Firefighter Safety and Occupant Survival”, this report expands upon the fire research conducted to date by analyzing how firefighting tactics, specifically suppression methods, affect the thermal exposure and survivability of both building occupants and firefighters in residential structures. • Part I: Water Distribution • Part II: Air Entrainment • Part III: Full-Scale Residential Fire Experiments. This report evaluates fire attack in residential structures through twenty-six full-scale structure fire experiments. Two fire attack methods, interior and transitional, were preformed at UL’s large fire lab in Northbrook, IL, in a single-story 1,600 ft2 ranch test structure utilizing three different ventilation configurations. To determine conditions within the test structure it was instrumented for temperature, pressure, gas velocity, heat flux, gas concentration, and moisture content. Ad- ditionally, to provide information on occupant burn injuries, five sets of instrumented pig skin were located in pre-determined locations in the structure. The results were analyzed to determine consistent themes in the data. These themes were evaluated in conjunction with a panel of fire service experts to develop 18 tactical considerations for fire ground operations. As you review the following tactical considerations it is important to utilize both these research results and your per- sonal experience to develop your department’s polices and implement these considerations during structural firefighting.
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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 laboratory tests. This has provided data to test any model of the cracking of pipelines. Thus, it is shown that crack densities are of the order of 5 cracks/mm of distance normal to the crack length direction and that the depths and lengths of cracks are distributed according to log normal and Weibull functions. During the growth stage of cracks in a colony, their spatial distribution is not random, because of the interaction of their associated stress fields. That interaction also results in the coalescence of cracks, an extremely important part of the overall growth process, and that interaction is defined quantitatively to provide further information to which modeling must aspire.
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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"). Measured data for contaminant species (CO2, O2, H2S, and H2O) were recorded at 5-second intervals, collected remotely, and compared to hourly data provided by site reference analyzers. Related webinar.
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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 wall stress. The evaluation is based on an assessment of existing full-scale test data, incident experience in the United States, and mechanics and fracture calculations.
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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. Moreover, before the release date, poorer performing banks were more likely to reduce the size of credit lines, while those with more significant balances of undrawn credit lines were more likely to cut term lending.
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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, 2023. http://dx.doi.org/10.53479/24998.

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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. Moreover, before the release date, poorer performing banks were more likely to reduce the size of credit lines, while those with more significant balances of undrawn credit lines were more likely to cut term lending.
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