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Olegas Vasilecas

Researcher at Vilnius Gediminas Technical University

Publications -  158
Citations -  1023

Olegas Vasilecas is an academic researcher from Vilnius Gediminas Technical University. The author has contributed to research in topics: Business rule & Business process modeling. The author has an hindex of 15, co-authored 155 publications receiving 963 citations. Previous affiliations of Olegas Vasilecas include Klaipėda University & University of Ljubljana.

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Journal ArticleDOI

Application of Interactive Classification System in University Study Course Comparison.

TL;DR: The approach suggests an automated/semi-automated classification solution, which incorporates both machine learning facilities and interactive involvement of a domain expert for improving classification results, and allows to classify educational data, thus reducing the number of misclassified instances significantly in comparison with the automatic machine learning approach.
Book ChapterDOI

Natural language based heavy personal assistant architecture for information retrieval and presentation

TL;DR: The progress of the natural language usage as the paradigm for information extraction and presentation in the enterprise environment is presented and a new methodology based on connectionist and symbol processing techniques for a knowledge worker to process his documents and utterance is suggested.
Journal ArticleDOI

Advances in databases and information systems: report of 5th East European Conference ADBIS'2001

TL;DR: The 5th East European Conference ADBIS'2001 was organized by the Vilnius Gediminas Technical University, Institute of Mathematics and Informatics (Lithuania), Lithuanian Computer Society in cooperation with Moscow ACM SIGMOD Chapter and Law University of Lithuania and had 127 registered participants from 23 countries.
Journal ArticleDOI

Estimation of the autoregressive operator by wavelet packets

TL;DR: In this article, the authors suggest to use wavelet packet bases as an alternative to principal component analysis (PCA) in an estimation of the functional autoregressive processes and search for the best basis on a criterion of highest correlation between pairs of wavelet coefficients.
Proceedings Article

The use of the natural language understanding agents with conceptual models

TL;DR: Traditional natural language interfaces in data exploration domain is extended in the following direction: the use of feedforward neural network as concepts indexes in the usersnatural language interfaces are suggested.