Relevant bibliographies by topics / Temporal association rules

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  1. Dissertations / Theses

Academic literature on the topic 'Temporal association rules'

Author: Grafiati
Published: 4 June 2021
Last updated: 18 February 2022

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Dissertations / Theses on the topic "Temporal association rules"

1

Matthews, Stephen. "Learning lost temporal fuzzy association rules." Thesis, De Montfort University, 2012. http://hdl.handle.net/2086/8257.

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Fuzzy association rule mining discovers patterns in transactions, such as shopping baskets in a supermarket, or Web page accesses by a visitor to a Web site. Temporal patterns can be present in fuzzy association rules because the underlying process generating the data can be dynamic. However, existing solutions may not discover all interesting patterns because of a previously unrecognised problem that is revealed in this thesis. The contextual meaning of fuzzy association rules changes because of the dynamic feature of data. The static fuzzy representation and traditional search method are ina
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2

Chen, Xiaodong. "Temporal data mining : algorithms, language and system for temporal association rules." Thesis, Manchester Metropolitan University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297977.

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Studies on data mining are being pursued in many different research areas, such as Machine Learning, Statistics, and Databases. The work presented in this thesis is based on the database perspective of data mining. The main focuses are on the temporal aspects of data mining problems, especially association rule discovery, and issues on the integration of data mining and database systems. Firstly, a theoretical framework for temporal data mining is proposed in this thesis. Within this framework, not only potential patterns but also temporal features associated with the patterns are expected to
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3

Zhao, Yi. "Discovery of temporal association rules in multivariate time series." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-31576.

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This thesis focuses on mining association rules on multivariate time series. Com-mon association rule mining algorithms can usually only be applied to transactional data, and a typical application is market basket analysis. If we want to mine temporal association rules on time series data, changes need to be made. During temporal association rule mining, the temporal ordering nature of data and the temporal interval between the left and right patterns of a rule need to be considered. This thesis reviews some mining methods for temporal association rule mining, and proposes two similar algorith
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4

Pray, Keith A. "Apriori Sets And Sequences: Mining Association Rules from Time Sequence Attributes." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0506104-150831/.

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Thesis (M.S.) -- Worcester Polytechnic Institute.<br>Keywords: mining complex data; temporal association rules; computer system performance; stock market analysis; sleep disorder data. Includes bibliographical references (p. 79-85).
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5

TATAVARTY, GIRIDHAR. "FINDING TEMPORAL ASSOCIATION RULES BETWEEN FREQUENT PATTERNS IN MULTIVARIATE TIME SERIES." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1141325950.

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6

Unal, Calargun Seda. "Fuzzy Association Rule Mining From Spatio-temporal Data: An Analysis Of Meteorological Data In Turkey." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609308/index.pdf.

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Data mining is the extraction of interesting non-trivial, implicit, previously unknown and potentially useful information or patterns from data in large databases. Association rule mining is a data mining method that seeks to discover associations among transactions encoded within a database. Data mining on spatio-temporal data takes into consideration the dynamics of spatially extended systems for which large amounts of spatial data exist, given that all real world spatial data exists in some temporal context. We need fuzzy sets in mining association rules from spatio-temporal databases since
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7

João, Rafael Stoffalette. "Mineração de padrões sequenciais e geração de regras de associação envolvendo temporalidade." Universidade Federal de São Carlos, 2015. https://repositorio.ufscar.br/handle/ufscar/8923.

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Submitted by Aelson Maciera (aelsoncm@terra.com.br) on 2017-08-07T19:16:02Z No. of bitstreams: 1 DissRSJ.pdf: 7098556 bytes, checksum: 78b5b020899e1b4ef3e1fefb18d32443 (MD5)<br>Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-08-07T19:18:39Z (GMT) No. of bitstreams: 1 DissRSJ.pdf: 7098556 bytes, checksum: 78b5b020899e1b4ef3e1fefb18d32443 (MD5)<br>Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-08-07T19:18:50Z (GMT) No. of bitstreams: 1 DissRSJ.pdf: 7098556 bytes, checksum: 78b5b020899e1b4ef3e1fefb18d32443 (MD5)<br>Made available in DSp
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8

Weitl, Harms Sherri K. "Temporal association rule methodologies for geo-spatial decision support /." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3091989.

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9

Gredebäck, Gustaf. "Infants’ Knowledge of Occluded Objects: Evidence of Early Spatiotemporal Representations." Doctoral thesis, Uppsala University, Department of Psychology, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4058.

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<p>This thesis demonstrates that infants represent temporarily non-visible, or occluded, objects. From 4 months of age, infants could accurately predict the reappearance of a moving object after 660 ms of non visibility; indicating accurate spatiotemporal representations. At this age predictions were dominated by associations between specific events and outcomes (associative rules). Between 6 and 8 months of age predictions became dominated by extrapolations (Study III). From 6 months infants could represent occluded objects for up to 4 seconds. The number of successful predictions decreased,
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10

Sammouri, Wissam. "Data mining of temporal sequences for the prediction of infrequent failure events : application on floating train data for predictive maintenance." Thesis, Paris Est, 2014. http://www.theses.fr/2014PEST1041/document.

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De nos jours, afin de répondre aux exigences économiques et sociales, les systèmes de transport ferroviaire ont la nécessité d'être exploités avec un haut niveau de sécurité et de fiabilité. On constate notamment un besoin croissant en termes d'outils de surveillance et d'aide à la maintenance de manière à anticiper les défaillances des composants du matériel roulant ferroviaire. Pour mettre au point de tels outils, les trains commerciaux sont équipés de capteurs intelligents envoyant des informations en temps réel sur l'état de divers sous-systèmes. Ces informations se présentent sous la form
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