Распознавание структур стебель-петля транспозонов человека и прогнозирование их функции при помощи модели машинного обучения.
Properties of Erdos measure and the invariant Erdos measure for the golden ratio and all values of the Bernoulli parameter are studies. It is proved that a shift on the two-sided Fibonacci compact set with invariant Erdos measure is isomorphic to the integral automorphism for a Bernoulli shift with countable alphabet. An effective algorithm for calculating the entropy of an invariant Erdos measure is proposed. It is shown that, for certain values of the Bernulli parameter, the algorithm gives the Hausdorff dimension of an Erdos measure to 15 decimal places.
The volume contains the abstracts of the 12th International Conference "Intelligent Data Processing: Theory and Applications". The conference is organized by the Russian Academy of Sciences, the Federal Research Center "Informatics and Control" of the Russian Academy of Sciences and the Scientific and Coordination Center "Digital Methods of Data Mining". The conference has being held biennially since 1989. It is one of the most recognizable scientific forums on data mining, machine learning, pattern recognition, image analysis, signal processing, and discrete analysis. The Organizing Committee of IDP-2018 is grateful to Forecsys Co. and CFRS Co. for providing assistance in the conference preparation and execution. The conference is funded by RFBR, grant 18-07-20075. The conference website http://mmro.ru/en/.
Properties of Erdos measure and the invariant Erdos measure for the golden ratio and all values of the Bernoulli parameter are studies. It is proved that a shift on the two-sided Fibonacci compact set with invariant Erdos measure is isomorphic to the integral automorphism for a Bernoulli shift with countable alphabet.
This paper is an overview of the current issues and tendencies in Computational linguistics. The overview is based on the materials of the conference on computational linguistics COLING’2012. The modern approaches to the traditional NLP domains such as pos-tagging, syntactic parsing, machine translation are discussed. The highlights of automated information extraction, such as fact extraction, opinion mining are also in focus. The main tendency of modern technologies in Computational linguistics is to accumulate the higher level of linguistic analysis (discourse analysis, cognitive modeling) in the models and to combine machine learning technologies with the algorithmic methods on the basis of deep expert linguistic knowledge.
This book constitutes the refereed proceedings of the 12th Industrial Conference on Data Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised full papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on data mining in medicine and biology; data mining for energy industry; data mining in traffic and logistic; data mining in telecommunication; data mining in engineering; theory in data mining; theory in data mining: clustering; theory in data mining: association rule mining and decision rule mining.