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 111 for “"Data mining techniques."”.
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DATA MINING TECHNIQUES ON VOLCANO MONITORING
The aim of this thesis is the study of data mining process able to discover implicit information from huge amount of data. In particular, indexing of datasets is studied to speed the efficiency of search algorithm. All of the presented techniques are applied in geophysical research field where the …
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Data mining techniques for complex application domains
The emergence of advanced communication techniques has increased availability of large collection of data in electronic form in a number of application domains including healthcare, e- business, and e-learning. Everyday a large amount of records are stored electronically. However, finding useful …
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High Performance Data Mining Techniques For Intrusion Detection
… transformed the way in which information and data was stored. With this new paradigm of data access, comes the threat of this information being exposed to unauthorized and unintended users. Many systems have been developed which scrutinize the data for a deviation from the normal behavior of a …
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Analysis of Healthcare Coverage Using Data Mining Techniques
… using a quantitative analysis on a large dataset from the United States. One of the objectives is to build supervised models including decision tree and neural network to study the efficient factors in healthcare coverage. We also discover groups of people with health coverage problems and …
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Using Data Mining Techniques to Improve Software Reliability
… bugs. CP-Miner uses frequent sequence mining to efficiently identify copy-pasted code in large software, and detects copy-paste related bugs. In order to further understand copy-paste in system software, this dissertation also analyzes some interesting characteristics of copy-paste in …
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Data mining techniques for large-scale gene expression analysis
… computational biology is awash in large-scale data mining problems. Several high-throughput technologies have been developed that enable us, with relative ease and little expense, to evaluate the coordinated expression levels of tens of thousands of genes, evaluate hundreds of thousands of …
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Immiscible displacement of trapped oil through experimental and data mining techniques.
Extensive experimental and data mining techniques have been applied to investigate the potential and competitiveness of gases used in immiscible gas-enhanced oil recovery (EOR) processes. Methane (CH4), Nitrogen (N2), Air (21%O2/N2) and Carbon Dioxide (CO2) are some of the gases injected in …
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Data mining techniques in higher education research : The example of student retention.
Data Mining has been used for more than a decade in a variety of differing environments. It takes an inductive approach to data analysis in that it is concerned with the extraction of patterns from the data often without preconceived ideas. Data mining is part of the field of Business Intelligence, …
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The Use of Data Mining Techniques in Crime Trend Analysis and Offender Profiling
… aim of this project is to ascertain whether the data in existing Police recording systems can be used by existing mature data mining techniques in an efficient manner to achieve results that are more accurate than those achieved by Police specialists when analysing crime. The Police Service has …
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Measuring MERCI: exploring data mining techniques for examining surgical outcomes of stroke patients
… in 2004. The importance of analyzing real-world data collected from MERCI clinical trials is key to providing insights on the effectiveness of MERCI. Most of the existing data analysis on MERCI results has thus far employed conventional statistical analysis techniques. To the best of the …
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Using data mining techniques to identify “the best” operational patterns for enrollment modeling
… research will utilize pre-existing historical data from Texas Woman's University containing readily available and easily measured factors, which most institutions of higher learning will have available, and will split the existing data in all the sub sets possible. Running a chi square analysis …
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Decision support tool for the tanker second-hand market using data mining techniques
… This is feasible with the use of powerful data mining techniques and the construction of explanatory forecasting models. Data mining techniques seek and extract patterns from databases. These patterns can be used to reveal possible interactions between database variables and to predict …
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Development and application of soft computing and data mining techniques in hot dip galvanising
… have increased investments for improving data storage capacity. The huge volume of information stored by companies and its high complexity render traditional methods of data processing useless. However, the use of tools to extract the information hidden inside databases is still under …
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Determination of drivers of stock-out performance of retail stores using data mining techniques
This research applies data mining techniques to give a picture of the interaction of performance variables such as between stock-outs and store attributes, and stock-outs and other variables including store sales, income and demographic data, as well as various aspects of inventory management data. …
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Development of Enhanced Neural Decision Tree Model and Application of Data Mining Techniques for Modeling of Petroleum Datasets
In this work, two data mining techniques are studied and applied to petroleum datasets. so as to extract useful information such as: correlations and interdependencies among the attributes. This helps to better understand important characteristics that can increase oil production. The two data …
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Utilizing data mining techniques and ensemble learning to predict development of surgical site infections in gynecologic cancer patients
… immune system. This research leverages popular data mining techniques to create a prediction model to identify high risk patients. Implemented techniques include logistic regression, naive Bayes, recursive partitioning and regression trees, random forest, feed forward neural network, k-nearest …
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Application of data mining techniques to predict the performance of matured Vertical Flow Constructed Wetlands Systems treating urban wastewater
… over three years of monitoring performance data from 03rd December 2014 to 28th March 2018 (thirty-nine months) of the vertical flow vertical wetlands system, receiving and treating domestic wastewater, were collected and utilised to assess and investigate the treatment performance …
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