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.
Results
Showing 1 to 20 of 916 for “"Data mining"”.
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Mantenimiento industrial & data mining
… será entonces demostrar la importancia del Data Mining (DM) para el mantenimiento industrial moderno, como una solución a esta dificultad anteriormente mencionada. Como objetivos específicos se busca acercar a la persona de mantenimiento industrial con la minería de datos, presentar sus …
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Data mining with bilattices
Data mining has become a key research area in database after Agrawal and Sirkant introduced association rules in data mining and proposed Apriori for mining association. However, most of the works focuses on finding patterns on itemsets, especially associations between items. With the fast …
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Algorithms for data mining
Data of massive size are now available in a wide variety of fields and come with great promise. In theory, these massive data sets allow data mining and exploration on a scale previously unimaginable. However, in practice, it can be difficult to apply classic data mining techniques to such massive …
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Robust methods in data mining
The thesis focuses on two problems in Data Mining, namely clustering, an exploratory technique to group observations in similar groups, and classification, a technique used to assign new observations to one of the known groups. A thorough study of the two problems, which are also known in the …
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Data Mining with Newton's Method.
<p>Capable and well-organized data mining algorithms are essential and fundamental to helpful, useful, and successful knowledge discovery in databases. We discuss several data mining algorithms including genetic algorithms (GAs). In addition, we propose a modified multivariate Newton's method (NM) …
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Optimization Problems in Data Mining
"We introduce a novel type of rule, wherein claims of the form ""our object ranked r or better in x of the last t time units,"" are formalized, and where maximal claims of this form are defined under two natural partial orders. For the first, we give an efficient and optimal algorithm for finding …
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Integer optimization in data mining
… methods have been widely used in statistics and data mining over the last thirty years, integer optimization has had very limited impact in statistical computation. Thus, our objective is to develop a methodology utilizing state of the art integer optimization methods to exploit the discrete …
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On semiparametric regression and data mining
… an increasingly large role in the analysis of datasets exhibiting various complications (Ruppert, Wand & Carroll, 2003). In particular semiparametric regression a plays prominent role in the area of data mining where such complications are numerous (Hastie, Tibshirani & Friedman, 2001). In this …
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Improving RDF data with data mining
Linked Open Data (LOD) comprises very many and often large public data sets and knowledge bases. Those datasets are mostly presented in the RDF triple structure of subject, predicate, and object, where each triple represents a statement or fact. Unfortunately, the heterogeneity of available open …
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I2MAPREDUCE: DATA MINING FOR BIG DATA
… Incremental MapReduce for Mining Evolving Big Data . i<sup>2</sup>MapReduce is used for incremental big data processing, which uses a fine-grained incremental engine, a general purpose iterative model that includes iteration algorithms such as PageRank, Fuzzy-C-Means(FCM), …
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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 and Visual Analytics Techniques
… explore, analyze and summarize large quantity of data. To achieve this purposes a data mining techniques and information visualization methods are used since decades. In the last years a new research field is gaining importance: Visual Analytics, an outgrowth of the fields of scientific and …
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Data-mining natural language materials syntheses
… thesis aims to realize the potential of this data for informing the syntheses of inorganic materials through the use of data-mining algorithms. Critically, the methods used and produced in this thesis are fully automated, thus maximizing the impact for accelerated synthesis planning by human …
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Overdue invoice forecasting and data mining
… The main procedures of the research work are data cleaning and processing, statistical analysis, building machine learning models and evaluating model performance. The analytical and modeling of the study are based on the real-world invoice data from a Fortune 500 company. The thesis also …
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Data mining for structure type prediction
Determining the stable structure types of an alloy is critical to determining many properties of that material. This can be done through experiment or computation. Both methods can be expensive and time consuming. Computational methods require energy calculations of hundreds of structure types. …
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Critical Success Factors in Data Mining Projects.
The increasing awareness of data mining technology, along with the attendant increase in the capturing, warehousing, and utilization of historical data to support evidence-based decision making, is leading many organizations to recognize that the effective use of data is the key element in the next …
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Data mining techniques for complex application domains
… 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 information from such a large data collection is a …
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Data mining and mathematical modelling on diabetes
… dynamics and was validated with experimental data obtained from oral glucose tolerance test (OGTT) in women with a history of gestational diabetes (GDM). GDM occurs when pregnant women without a previous diagnosis of diabetes develop a high blood glucose level. GDM could be a risk factor of …
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