Search Results (65)
Text mining for cross-domain knowledge discovery
One of the prevailing tendencies in science is research over-specialization, resulting in deep but relatively isolated islands of knowledge. Due to the huge amounts of scientific information produced at an increasingly fast pace, it has become difficult to follow even the specific literature limited to a single domain of specialization. …
Detection of anomalous and suspicious behavior patterns from spatio-temporal agent traces
Many applications, including smart environments, surveillance, human-robot interaction, and ambient assisted living, involve the problem of learning patterns of agent behavior from sensor data. Deviant behavior is a pattern in the data that either does not conform to the expected behavior, that is, anomalous behavior, or matches previously defined unwanted …
Sintering and phase transition behaviour of sodium niobate
Sodium niobate (NaNbO3) is the end member of several alkaline niobate-based solid solutions, which represent an important group of environment-friendly lead-free piezoceramics. Even though alkaline niobates are of considerable technological importance, problems in obtaining high densities and a fine-grained microstructure are still reported and not much is known about the …
Knowledge discovery in a service-oriented data mining environment
The thesis addresses the development of novel knowledge discovery scenarios in a modern data mining platform by utilising principles of service-oriented architecture with web services, interactive scientific workflows, knowledge discovery ontologies and automated construction of data mining workflows. We present the developed Orange4WS platform which upgrades Orange, a mature open-source …
Considering autocorrelation in predictive models
Most machine learning, data mining and statistical methods rely on the assumption that the analyzed data are independent and identically distributed (i.i.d.). More specifically, the individual examples included in the training data are assumed to be drawn independently from each other from the same probability distribution. However, cases where this …
Algorithms for Learning Regression Trees and Ensembles on Evolving Data Streams
In this thesis we address the problem of learning various types of decision trees from timechanging data streams. In particular, we study online machine learning algorithms for learning regression trees, linear model trees, option trees for regression, multi-target model trees, and ensembles of model trees from data streams. These are …
Low-temperature sintering of piezoelectric K0.5Na0.5NbO3 ceramics
The KNN solid solution was prepared from pre-synthesized binary compounds of, sodium and potassium niobate in a 1/1 molar ratio. The KNG sintering aid was prepared by homogenizing the pre-reacted binary mixtures of alkaline reagents and germanium oxide with the Na/Ge = 1/1 and K/Ge = 1/1 molar ratios. The …
A Modular Ontology of Data Mining
The domain of data mining (DM) deals with analyzing different types of data. The data typically used in data mining is in the format of a single table, with primitive datatypes as attributes. However, structured (complex) data, such as graphs, sequences, networks, text, image, multimedia and relational data, are receiving …
An Evaluation Method for Feature Rankings
Feature ranking is the machine learning task of inducing an ordering of features in a given dataset according to some notion of relevance. We consider the feature ranking task in the context of supervised learning, where the notion of feature relevance is defined with respect to a target concept. Feature …
Parameter Identification in Nonlinear Dynamic Systems with Meta-heuristic Approaches
The task of mathematical modeling of dynamic systems from observed system behavior, widely known under the name of system identification, breaks down into two subtasks. The first task, referred to as structure identification, is to specify the model structure, i.e., the functional form of the model. In practice, the model …