Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 21 for “"frequent patterns"”.
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A Sampling-Based Framework for Parallel Mining Frequent Patterns
We implemented parallel algorithms for mining frequent itemsets, sequential patterns and closed-sequential patterns following our framework. A comprehensive performance study has been conducted in our experiments on both synthetic and real-world datasets. The experimental results have shown that …
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Analyzing frequent patterns in data streams using a dynamic compact stream pattern algorithm
… online applications, devices and sources. Mining frequent patterns from these streams of data is now an important research topic in the field of data mining and knowledge discovery. The traditional approach of mining data may not be appropriate for a large volume of data stream environment where …
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Tree model guided (TMG) enumeration as the basis for mining frequent patterns from XML documents
… consists of two important problems, namely frequent patterns discovery and rule construction. The former task is considered to be a more challenging problem to solve. Because of its importance and application in a number of data mining tasks, it has become the focus of many studies. A …
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GENERIC FRAMEWORKS FOR INTERACTIVE PERSONALIZED INTERESTING PATTERN DISCOVERY
The traditional frequent pattern mining algorithms generate an exponentially large number of patterns of which a substantial portion are not much significant for many data analysis endeavours. Due to this, the discovery of a small number of interesting patterns from the exponentially large number …
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DPLearn: an effective but concise learning framework based on discriminative patterns
… proposed to improve the accuracy using selected frequent patterns, where many efforts were paid to prune a huge number of non-discriminative frequent patterns. On the other hand, tree-based models have shown strong abilities on many learning tasks since they can easily build high-order …
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Un modelo neuronal basado en la metaplasticidad para la clasificación de objetos en señales 1-d y 2-d
… The BPA has been success used in problems of patterns classification in areas such as: Medicine, Bioinformatic, Telecommunications, Banking, Climatological Predictions, etc. However the BPA has some limitations that prevent to reach an optimal efficiency level (slowness problems, convergence …
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Work optimization with association rule mining of negative effective deterioration in building components
… (SQL) based association rule mining to find frequent patterns of observed condition deterioration among different component types. A new metric, negative effective deterioration, is introduced which is based on actual deterioration observed from inspection data, relative to expected condition …
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Machine learning and data analytics for multilayer data in policy planning
… data lead to better decisions?” has been a frequent question for discussion among many decision makers—data scientists as well as organizational leaders and managers. Educational institutions, finance, and the retail industry have had big data for several decades that did not significantly …
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FP-tree Based Spatial Co-location Pattern Mining
… co-location pattern is a set of spatial features frequently located together in space. A frequent pattern is a set of items that frequently appears in a transaction database. Since its introduction, the paradigm of frequent pattern mining has undergone a shift from candidate generation-and-test …
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New Approaches to Frequent and Incremental Frequent Pattern Mining
… (DM) is a process for extracting interesting patterns from large volumes of data. It is one of the crucial steps in Knowledge Discovery in Databases (KDD). It involves various data mining methods that mainly fall into predictive and descriptive models. Descriptive models look for patterns, …
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Summarizing data with representative patterns
… problem of summarizing data with representative patterns. The objective is to find a set of patterns, which is much more concise but still contains rich information of the original data, and may provide valuable insights for further analysis of data. In the light of this idea, we formally …
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Sequential pattern mining with uncertain data
… database, it is probabilistic that a pattern is frequent or not; thus, we define the concept of probabilistic frequent sequential patterns. And various algorithms are designed to mine probabilistic frequent patterns efficiently in uncertain databases. We also implement our algorithms on …
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The Effect of Family Solidarity on Female Juvenile Delinquency: An Exploratory Study
… family group is of primary influence in the frequent patterns of female juvenile delinquency. A further conclusion is that the unstable family, whether consisting of one or two parents is the most destructive obstacle toward breaking a delinquent pattern. Future studies might be helpful to …
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The Impact of substrate texture on cell behavior
… fibronectin stripes, which mimic some of the frequent patterns that cells are exposed to in their natural microenvironment, and studied the effects of these patterns on 3T3 fibroblasts and human mesenchymal stem cells which are of significant importance in the field of regenerative medicine …
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A method to detect and represent temporal patterns from time series data and its application for analysis of physiological data streams
… pattern generation and quantification (c) frequent patterns identification and (d) building a classification system. This method is applied to a neonatal intensive care case study with a motivating problem that discovery of specific patterns from patient data could be crucial for making …
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Data-driven analyses of watersheds as coupled human-nature systems
Both climate and human activities alter watershed characteristics. Because climate will continue to change and human population will continue to increase, we can expect that all watersheds will change during the foreseeable future. Interactions between climate change and human activity drive …
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Case study of a creative writing program and the interaction of white instructors' and African American students' social and cultural backgrounds
… used the constant-comparative method to generate frequent patterns and themes across the students, their teacher, and the instructors' interactions. I identified literacy events in which socio-cultural differences among the instructors and students occurred. However, the differences in the …
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A comprehensive and efficient framework for subgraph matching
… avoided. Due to the complex edge connections in patterns, existing works perform repetitive matching, indicating a novel concept of candidate dependency to reuse candidates and avoid repetition. As real-world graph analysis often relies on frequent patterns, such patterns are often symmetric and …
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Harmonizing data mining and static analysis to tackle hardware and system level verification
… on STAR, a technique for generating input vector patterns for all paths of an RTL design using RTL symbolic execution. To attack the path explosion problem in STAR, we present HYBRO and the symbolic state caching method. HYBRO uses branch coverage metric to guide the path exploration. It is a …
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Semantically aware hierarchical Bayesian network model for knowledge discovery in data : an ontology-based framework
… invented algorithms are confined to generating frequent patterns and do not illustrate how to act upon them. Hence, many researchers have argued that existing mining algorithms have some limitations with respect to performance and workability. Quantity and quality are the main limitations of the …
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