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 42 for “"Rule Mining"”.
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Indirect association rule mining for crime data analysis
… thesis are 1) develop an indirect association rule mining algorithm from a large, publicly available data set with a focus on crimes of the domestic violence nature 2) extend the indirect association rule mining algorithm for generating indirect association rules and determine its impact"--Leaf …
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Multi-drug association rule mining on graphics processing unit
… be associated to a drug or combination of drugs. Mining patient data allows unknown associations between drugs and symptoms to be discovered. General-purpose GPU computing is the next evolution in processing architectures; utilization of this massively parallel processor towards drug data mining …
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Geovisualization for Association Rule Mining in CHOPS Well Data
Association rule mining has recently been applied to improve the oil recovery of CHOPS by discovering the association rules between reservoir properties and oil production from CHOPS well data. However, it leaves reservoir engineers with big challenging tasks to find interesting rules, understand …
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Occupant location prediction in smart buildings using association rule mining
… location prediction based on association rule mining, allowing prediction based on historical occupant locations. Association rule mining is a machine learning technique designed to find any correlations which exist in a given dataset. Occupant location datasets have a number of properties …
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Identifying relationships among drug side-effects using probabilistic association rule mining
… problem. A modified version of association rule mining together with the use of hierarchical terminology is employed to rank potential associations between side-effects. Results are validated by comparison with conventional association rule mining under different assumptions of uncertainty …
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Work optimization with association rule mining of negative effective deterioration in building components
… query language (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 …
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Fusion: a Visualization Framework for Interactive Ilp Rule Mining With Applications to Bioinformatics
… them with both visual data exploration and data mining capabilities. Its multiple view visual framework allows the user to choose different views for different types of data. Fusion uses Proteus, an Inductive Logic Programming (ILP) rule finding algorithm to mine relationships in the microarray …
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SAERMA: Stacked Autoencoders Rule Mining Algorithm for the Interpretation of Epistatic Interactions in GWAS of Extreme Obesity
… stacked autoencoders (SAE) and association rule mining (ARM) to identify epistatic interactions between SNPs. This is achieved using a case-control dataset containing 2,193 observations (962 cases and 1,231 controls) each with 594,034 genetic markers. A statistical filtering strategy is …
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Assessing Lightning and Wild Fire Hazard by Land Properties and Cloud to Ground Lightning Data with Association Rule Mining over Alberta, Canada
… by using 2010-2016 lightning data with data mining methods. The hotspot analysis was implemented to find the regions with high frequency CG lightning strikes clustered together. Generally, hotspot regions are located in central, central east and south central regions of the study regions. …
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Mining Functional and Structural Relationships of Context Variables in Smart-Buildings
… presents an extension to the new IoT class rule programming paradigm, which simplifies rule creation based on classes. The proposed extension uses a semantic compiler to simplify the device and inferred-context associations. Using direct-context information and template classes, the compiler …
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Learning lost temporal fuzzy association rules
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, …
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Some Aspects on Data Modelling
… areas, such as finance, bioinformatics and text mining. In this dissertation, two problems regarding these two types of data: association rule mining from transaction data and structural change estimation in time-ordered sequence, are studied. Informative association rule mining is fundamental …
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Mining Social Tags to Predict Mashup Patterns
… The proposed approach applies association rule mining techniques to discover relationships between APIs and mashups based on their annotated tags. The importance of the mined relationships is advocated as a valuable source for recommending mashup candidates while mitigating common problems …
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An Approach For Scalable First-Order Rule Learning On Twitter Data
Scalable Rule Learning (SRLearn) is a scalable divide-and-conquer approach with graph-based modeling of social media data, to scale up first-order rule learning through Markov Logic Networks on a commodity cluster on large scale Twitter data. SRLearn takes advantage of distributed systems to …
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Improving RDF data with data mining
… and topical classifications. Association rule mining, which was originally applied for sales analysis on transactional databases, is a promising and novel technique to explore such data. We designed an adaptation of this technique for min-ing Rdf data and introduce the concept of “mining …
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A study of undergraduate health science students' perceptions, navigational choices, and learning outcomes with IPSims simulative learning environment
… traditional statistical analysis and Association Rule mining. This study will investigate how students perceptions of the simulative learning environment IPSims (Interprofessional Simulations) usability impacts learning outcomes, and how these environments may impact student disposition to engage …
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An association rule dynamics and classification approach to event detection and tracking in Twitter.
… topics over a specified period using Association Rule Mining. We termed our novel methodology Transaction-based Rule Change Mining (TRCM). TRCM is a system built on top of the Apriori method of Association Rule Mining to extract patterns of Association Rules changes in tweets hashtag keywords at …
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Approximate Dynamic Programming with Parallel Stochastic Planning Operators
… in response to actions, using an association rule mining approach. An approximate policy is then derived by iteratively improving state value aggregation estimates attached to the operators using the P-SPOs as a model in a Dyna-Q-like architecture. Reinforcement learning and dynamic …
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Xeditor: Inferring and Applying XML Consistency Rules
… called Xeditor where we extract XML consistency rules from open-source projects and use these rules to detect XML bugs. There are two phases in Xeditor: rule inference and application. To infer rules, Xeditor mines XML-based deployment descriptors in open-source projects, extracting XML entity …
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