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Showing 1 to 20 of 48 for “"association rule"”.
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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
… 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 will accelerate the research and …
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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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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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Assessing Lightning and Wild Fire Hazard by Land Properties and Cloud to Ground Lightning Data with Association Rule Mining over Alberta, Canada
… by measuring preference index (PI). The association rule mining technique was used to investigate frequent CG lightning patterns, which were verified by similarity measurement to check the patterns’ consistency. The verification of CG lightning hazard map generated with 2010-2014 data was …
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Some Aspects on Data Modelling
… 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 for knowledge discovery from transaction data, for which brute-force search …
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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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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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Mining User Facebook Post Likes for Cross Domain Product Recommendations across E- commerce platforms
… transforming then into itemsets. A modified association rule mining is applied uncover patterns of frequent co-occurrence between user Facebook post likes and e-commerce transactions as rules. It then uses the proposed HARR (Hybrid Association Rule Recommendation) algorithm to match new user …
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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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New Approaches to Frequent and Incremental Frequent Pattern Mining
… models. Descriptive models look for patterns, rules, relationships and associations within data. One of the descriptive methods is association rule analysis, which represents co-occurrence of items or events. Association rules are commonly used in market basket analysis. An association rule is …
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Efficient Web Searching for Open -Ended Questions: The Effects of Visualization and Data Mining Technology
… of simultaneously handling multiple tasks. The association rule data mining technology allowed the students to make use of Web search queries and Web resources that previous Web searchers had found to be useful in extending and refining their Web search results. Finally, the students' Web …
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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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Scaling data mining activities on very large datasets
… mining techniques, with specific emphasis on association rule and frequent itemset mining. In particular, it proposes a scalable itemset mining approach relying on (i) a persistent (disk-based) representation of the transactional data, (ii) ad-hoc data retrieval techniques, and …
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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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