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 36 for “"Association rule mining"”.
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Indirect association rule mining for crime data analysis
… of this 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 …
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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
… to occupant 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 …
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Identifying relationships among drug side-effects using probabilistic association rule mining
… of research by proposing a method to determine associations between side-effects. The problem is cast in the form of a merged basket analysis problem. A modified version of association rule mining together with the use of hierarchical terminology is employed to rank potential associations …
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Work optimization with association rule mining of negative effective deterioration in building components
… on using structured 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 …
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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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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
… consensus. 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 …
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Improving RDF data with data mining
… range definitions, 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 …
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A study of undergraduate health science students' perceptions, navigational choices, and learning outcomes with IPSims simulative learning environment
… such as 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 …
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An association rule dynamics and classification approach to event detection and tracking in Twitter.
… real-life 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 …
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Approximate Dynamic Programming with Parallel Stochastic Planning Operators
… its environment 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 …
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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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Mining User Facebook Post Likes for Cross Domain Product Recommendations across E- commerce platforms
… recommendation accuracy can be improved by mining patterns from other domains such as social media (Facebook), to predict purchase behaviours. The "cross-site cold start problem" arises when traditional recommender systems, relying on e-commerce purchase history, face platforms with no user …
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Discovering E-commerce Sequential Data Sets and Sequential Patterns for Recommendation
… Existing recommendation systems that use mining techniques with some sequences are those referred to as LiuRec09, ChoiRec12, SuChenRec15, and HPCRec18. LiuRec09 system clusters users with similar clickstream sequence data, then uses association rule mining and segmentation based …
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A geographic knowledge discovery approach to property valuation
… has been designed and implemented. It employs association rule mining and associative classification algorithms to uncover any existing inter-relationships and perform the valuation. Various algorithms that perform the above tasks have been proposed in the literature. The algorithm developed in …
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Development and application of soft computing and data mining techniques in hot dip galvanising
… computer-based methodologies derived from data mining are being developed. By using these methods, researchers are seeking to obtain non-trivial hidden knowledge from historical records of industrial processes. For this reason, data mining has now become a crucial discipline for performing …
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