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Scalable Knowledge Discovery in Complex Data with Pattern Structures
P. 30–41.
Язык:
английский
Ключевые слова: knowledge discovery
В книге
Vol. LNCS 8251. , Berlin, Heidelberg: Springer, 2013.
Децентрализованные финансы (или DeFi от англ. "Decentralized finance") предлагают ряд финансовых инструментов и услуг, использующих возможности технологии web3. В частности протокол Maker позволяет пользователям получать кредиты, обеспеченные криптовалютами. В отличие от традиционных банков, данные Maker прозрачно записываются в блокчейн Ethereum. В этой статье мы сосредоточимся на анализе кредитного аспекта Maker с традиционной финансовой точки зрения. ...
Добавлено: 4 сентября 2024 г.
SciTePress, 2019.
Добавлено: 15 января 2020 г.
SciTePress, 2016.
Добавлено: 29 сентября 2018 г.
Setúbal: SciTePress, 2013.
Добавлено: 17 октября 2016 г.
CEUR Workshop Proceedings, 2016.
This volume contains the papers presented at the Second International Workshop on Soft Computing Applications and Knowledge Discovery (SCAKD 2016) held on July 18, 2016 at the National Research University Higher School of Economics, Moscow, Russia. Soft computing is a collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty and partial truth to ...
Добавлено: 28 сентября 2016 г.
Switzerland: Springer, 2015.
Добавлено: 18 февраля 2016 г.
Незнанов А. А., Паринов А. А., , in: CEUR Workshop Proceedings. Proceedings of the International Workshop on Social Network Analysis using Formal Concept Analysis (SNAFCA 2015)Issue 1534: SNAFCA 2015 Social Network Analysis using Formal Concept Analysis.: Malaga: CEUR Workshop Proceedings, 2015. Ch. 5 P. 43–54.
Добавлено: 19 октября 2015 г.
Незнанов А. А., Паринов А. А., , in: Intelligent Distributed Computing IX.: Springer, 2015. P. 265–271.
Добавлено: 19 октября 2015 г.
Buenos Aires: [б.и.], 2015.
The three preceding editions of the FCA4AI Workshop showed that many researchers working in Artificial Intelligence are deeply interested by a well-founded method for classi- fication and mining such as Formal Concept Analysis (see http://www.fca4ai.hse.ru/). The first edition of FCA4AI was co-located with ECAI 2012 in Montpellier and published as http://ceur-ws.org/Vol-939/, the second edition was ...
Добавлено: 5 августа 2015 г.
Irina V. Efimenko, Хорошевский В. Ф., Lecture Notes in Computer Science 2014 No. 8722 P. 170–177
Добавлено: 23 октября 2014 г.
Prague: CEUR Workshop Proceedings, 2014.
The first and the second edition of the FCA4AI Workshop showed that many researchers working in Artificial Intelligence are indeed interested by a well-founded method for classi- fication and mining such as Formal Concept Analysis (see http://www.fca4ai.hse.ru/). The first edition of FCA4AI was co-located with ECAI 2012 in Montpellier and published as http://ceur-ws.org/Vol-939/ while the ...
Добавлено: 12 сентября 2014 г.
Кузнецов С. О., , in: Proc. 11th International Conference on Formal Concept Analysis (ICFCA 2013)Vol. 7880.: Springer, 2013. P. 254–266.
Pattern structures, an extension of FCA to data with complex descriptions, propose an alternative to conceptual scaling (binarization) by giving direct way to knowledge discovery in complex data such as logical formulas, graphs, strings, tuples of numerical intervals, etc. Whereas the approach to classification with pattern structures based on preceding generation of classifiers can lead ...
Добавлено: 2 июня 2013 г.
Leuven: Katholieke Universiteit Leuven, 2012.
Добавлено: 10 марта 2013 г.
Finn V., Mikheyenkova M., Logic and Logical Philosophy 2011 No. 20 P. 113–139
The plausible reasoning class (called the JSM-reasoning in honour of John Stuart Mill) is described. It implements interaction of three forms of non-deductive procedures _ induction, analogy and abduction. Empirical induction in the JSM-reasoning is the basis for generation of hypotheses on causal relations (determinants of social behaviour). Inference by analogy means that predictions about ...
Добавлено: 9 декабря 2011 г.
Найденова К., Игнатов Д. И., Hershey: IGI Global, 2012.
The consideration of symbolic machine learning algorithms as an entire class will make it possible, in the future, to generate algorithms, with the aid of some parameters, depending on the initial users’ requirements and the quality of solving targeted problems in domain applications.
Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems surveys, analyzes, and ...
Добавлено: 3 декабря 2012 г.
Пульманс Й., Элзинга П., Незнанов А. А. и др., , in: CDUD'11 – Concept Discovery in Unstructured Data Workshop co-located with the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC-2011), June 2011, Moscow, RussiaIssue 757.: M.: Higher School of Economics Publishing House, 2011. P. 53–62.
Concept Relation Discovery and Innovation Enabling Technology (CORDIET), is a toolbox for gaining new knowledge from unstructured text data. At the core of CORDIET is the C-K theory which captures the essential elements of innovation. The tool uses Formal Concept Analysis (FCA), Emergent Self Organizing Maps (ESOM) and Hidden Markov Models (HMM) as main artifacts ...
Добавлено: 3 декабря 2012 г.
M.: Higher School of Economics Publishing House, 2011.
Concept discovery is a Knowledge Discovery in Databases (KDD) research field that uses human-centered techniques such as Formal Concept Analysis (FCA), Biclustering, Triclustering, Conceptual Graphs etc. for gaining insight into the underlying conceptual structure of the data. Traditional machine learning techniques are mainly focusing on structured data whereas most data available resides in unstructured, often ...
Добавлено: 3 декабря 2012 г.
Добавлено: 20 ноября 2012 г.
M.: Higher School of Economics Publishing House, 2011.
Добавлено: 31 августа 2012 г.