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Dissertations / Theses on the topic 'Fuzzy temporal association rule'

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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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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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Carse, Brian. "Artificial evolution of fuzzy and temporal rule based systems." Thesis, University of the West of England, Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267551.

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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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5

Cai, Chun Hing. "Mining association rules with weighted items." Hong Kong : Chinese University of Hong Kong, 1998. http://www.cse.cuhk.edu.hk/%7Ekdd/assoc%5Frule/thesis%5Fchcai.pdf.

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Thesis (M. Phil.)--Chinese University of Hong Kong, 1998.<br>Description based on contents viewed Mar. 13, 2007; title from title screen. Includes bibliographical references (p. 99-103). Also available in print.
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Isik, Narin. "Fuzzy Spatial Data Cube Construction And Its Use In Association Rule Mining." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606056/index.pdf.

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The popularity of spatial databases increases since the amount of the spatial data that need to be handled has increased by the use of digital maps, images from satellites, video cameras, medical equipment, sensor networks, etc. Spatial data are difficult to examine and extract interesting knowledge<br>hence, applications that assist decision-making about spatial data like weather forecasting, traffic supervision, mobile communication, etc. have been introduced. In this thesis, more natural and precise knowledge from spatial data is generated by construction of fuzzy spatial data cube and extr
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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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8

He, Yuanchen. "Fuzzy-Granular Based Data Mining for Effective Decision Support in Biomedical Applications." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_diss/12.

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Due to complexity of biomedical problems, adaptive and intelligent knowledge discovery and data mining systems are highly needed to help humans to understand the inherent mechanism of diseases. For biomedical classification problems, typically it is impossible to build a perfect classifier with 100% prediction accuracy. Hence a more realistic target is to build an effective Decision Support System (DSS). In this dissertation, a novel adaptive Fuzzy Association Rules (FARs) mining algorithm, named FARM-DS, is proposed to build such a DSS for binary classification problems in the biomedical dom
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Castro, Ricardo Ferreira Vieira de. "Análise de desempenho dos algoritmos Apriori e Fuzzy Apriori na extração de regras de associação aplicados a um Sistema de Detecção de Intrusos." Universidade do Estado do Rio de Janeiro, 2014. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=8137.

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A extração de regras de associação (ARM - Association Rule Mining) de dados quantitativos tem sido pesquisa de grande interesse na área de mineração de dados. Com o crescente aumento das bases de dados, há um grande investimento na área de pesquisa na criação de algoritmos para melhorar o desempenho relacionado a quantidade de regras, sua relevância e a performance computacional. O algoritmo APRIORI, tradicionalmente usado na extração de regras de associação, foi criado originalmente para trabalhar com atributos categóricos. Geralmente, para usá-lo com atributos contínuos, ou quantitativos, é
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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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Pazhoumand-Dar, Hossein. "Unsupervised monitoring of an elderly person's activities of daily living using Kinect sensors and a power meter." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2017. https://ro.ecu.edu.au/theses/1971.

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The need for greater independence amongst the growing population of elderly people has made the concept of “ageing in place” an important area of research. Remote home monitoring strategies help the elderly deal with challenges involved in ageing in place and performing the activities of daily living (ADLs) independently. These monitoring approaches typically involve the use of several sensors, attached to the environment or person, in order to acquire data about the ADLs of the occupant being monitored. Some key drawbacks associated with many of the ADL monitoring approaches proposed for the
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12

Lee, Wan-Jui, and 李婉瑞. "Discovery of fuzzy temporal and periodic association rules." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/3w6k3p.

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博士<br>國立中山大學<br>電機工程學系研究所<br>96<br>With the rapidly growing volumes of data from various sources, new tools and computational theories are required to extract useful information (knowledge) from large databases. Data mining techniques such as association rules have been proved to be effective in searching hidden knowledge in a large database. However, if we want to extract knowledge from data with temporal components, it becomes necessary to incorporate temporal semantics with the traditional data mining techniques. As mining techniques evolves, mathematical techniques become more involved to
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13

Jin, Weiqing. "Fuzzy classification based on fuzzy association rule mining." 2004. http://www.lib.ncsu.edu/theses/available/etd-12072004-130619/unrestricted/etd.pdf.

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14

Chen, Yi-Ling, and 陳依伶. "Developing an Optimal Fuzzy Association Rule Algorithm." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/35075325825710983294.

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碩士<br>元智大學<br>工業工程與管理學系<br>93<br>Association rule is one of the most often discussed data mining technology. It is used in market basket analysis to know the regularity of customer’s purchase behavior. Although association rule is popular, it is limited to the item with categorical value. To solve the difficulty, this research develops an optimal fuzzy association rule algorithm so that the items with numerical data values can also be applied. First, linguistic sets of each attribute are encoded as genes of a chromosome. The optimal fuzzy membership functions are generated automatically after
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15

WU, CHEN-HAN, and 余承翰. "A Study of Enterprise Personnel Selection using Fuzzy Association Rule." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/68167669038838643667.

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碩士<br>大葉大學<br>資訊管理學系碩士班<br>93<br>Recently, the enterprise gradually realizes that the good human resource, is the key factor to gain the competitive advantage. Therefore, the human resource management has become the most important work for enterprise to maintain the strength of market competition. Under this situation, how to find or select the good employee is the first challenge for enterprise. In general, personnel selection is usually to review his applicant and judge his ability to match the job. In fact, if the enterprise can not choose the suitable talented person that it will create th
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16

Liu, Hung-Yu, and 劉泓郁. "Using Fuzzy Association Rule Algorithms to Enhance New Product Development." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/96107653364246198325.

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碩士<br>元智大學<br>工業工程與管理學系<br>91<br>In today’s competitive market, consumer-oriented product development should be intensified to meet consumers’ various requirements. If product designers can comprehend the preferences of the targeted consumers, the developed products will be remarkable and popular. Therefore, how to help designer understand and analyze consumers’ favors becomes one of the most important tasks in new product development. Association rule algorithm, an essential technique in the data mining applications, can be used to find out the relation between consumers and products. Althoug
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17

陳孟華. "Two-Phase Chinese Word Segmentation -- Using Fuzzy Theory and Association Rule." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/57723686343216437893.

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碩士<br>淡江大學<br>資訊工程學系<br>90<br>With the growing convenience of knowledge acquisition and the abundance of available data in this era of information, we must rely increasingly on technology to assist with the recording and analysis of documents in order to successfully accomplish their classification. Usually, there are three steps in document classification: word segmentation analysis, keyword search and, finally, classification. There is, however, a major difference between English and Chinese when it comes to word segmentation: specifically, English words are separated by spaces, w
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18

Yu, Shao-Huei, and 游邵惠. "Using Self-Tuning Fuzzy Membership Functions for Optimal Association Rule Mining." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/6c323r.

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碩士<br>國立虎尾科技大學<br>資訊管理研究所<br>98<br>With the advancement in information technology, data mining is often used to generate the association rules by semantic or quantitative transaction data. But how to extract the value of hiding the importance information is a preoccupation. In recent years, the reasoning process of association rules can be removed the unimportant inference through defined fuzzy membership functions and threshold settings, but its subjective setting impact the correctness of the final numbers of association rules derived and mining results. And the past, most scholars only cons
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19

Hsu, Chia-Ling, and 徐嘉鈴. "The Study of Fuzzy Association Rule into the Problem of Missing Value." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/42437980221686168487.

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碩士<br>元智大學<br>資訊管理學系<br>96<br>Large-scale database and data warehousing increasing, in the data collection process have the missing value are large problems. The problem of the missing value, it will seriously affect the quality of the analysis of data mining. So how to properly handle the issue of the missing value, will become an important topic. There has been the method that a lot of processing the missing value being put forward, among them with the concept of the association rule most is familiar. In this paper, the study take the association rule as the foundation, join the fuzzy set an
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20

Yin, Kuo Cheng, and 尹國正. "On Effective Association Rule Mining Algorithms for Temporal, Continuous and Big Data." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/99483196922371054393.

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博士<br>逢甲大學<br>資訊工程學系<br>102<br>Data mining technology has been widely applied in various fields, while the association rule mining algorithm is the most representative technique. Our researches of association rule mining are divided into three major areas. The first of which is the rationality of discovered rules that are mined by association rule mining algorithm. The second is the adaptation of association rule mining algorithm when it is applied in different fields. The third is the mining efficiency improvement of association rule mining algorithm. In this dissertation, we identify potenti
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21

Tsai, Ming-Chien, and 蔡明蒨. "Fuzzy High-Orders Time-Series Model Based on GSP and Association Rule in Financial Market Application." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/29207658329658943039.

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碩士<br>雲林科技大學<br>資訊管理系碩士班<br>99<br>In the recent years, traditional time series model has been widely researched. The previous time series methods can predict future problems based on historical data, but have a problem that determines subjectively the length of intervals. Song and Chissom (1993) proposed the fuzzy time series to solve the problem of traditional time series methods. So far, many researchers have proposed different fuzzy time series models to deal with uncertain and vague data. Besides, the consideration of a forecasting stage only discusses the relations for previous period and
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22

Yuan, Xin. "Multi-approaches to achieve an advanced cognitive agent in a new type of parallel processing computer." Thesis, 2020. http://hdl.handle.net/2440/130741.

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In this work, we addressed the problem of developing an agent-based artificial general intelligence that can be implemented in compact and power-efficient electronic hardware. We proposed an approach intended to show the feasibility of using this conceptual hardware-based architecture to replicate simple cognitive behaviours. This research started with surveys on cognitive behaviours and their decision-making architectures and compared them with a production rule-based parallel processing computation architecture. In order to demonstrate their potential, a sample case study of the homing behav
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23

Vaudry, Pierre-Luc. "Narrative generation by associative network extraction from real-life temporal data." Thèse, 2016. http://hdl.handle.net/1866/18473.

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Les données portant sur des événements abondent dans notre société technologique. Une façon intéressante de présenter des données temporelles réelles pour faciliter leur interprétation est un récit généré automatiquement. La compréhension de récits implique la construction d'un réseau causal par le lecteur. Les systèmes de data-to-text narratifs semblent reconnaître l'importance des relations causales. Cependant, celles-ci jouent un rôle secondaire dans leurs planificateurs de document et leur identification repose principalement sur des connaissances du domaine. Cette thèse propose un modè
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