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pro vyhledávání: '"03G10 68T27"'
Conceptual Scaling is a useful standard tool in Formal Concept Analysis and beyond. Its mathematical theory, as elaborated in the last chapter of the FCA monograph, still has room for improvement. As it stands, even some of the basic definitions are
Externí odkaz:
http://arxiv.org/abs/2302.09101
Autor:
Hanika, Tom, Hirth, Johannes
Publikováno v:
Int. J. Approx. Reason. 159, 2023
Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially parallelizabil
Externí odkaz:
http://arxiv.org/abs/2302.05270
Autor:
Hanika, Tom, Hirth, Johannes
Dimension reduction of data sets is a standard problem in the realm of machine learning and knowledge reasoning. They affect patterns in and dependencies on data dimensions and ultimately influence any decision-making processes. Therefore, a wide var
Externí odkaz:
http://arxiv.org/abs/2106.06815
Autor:
Hanika, Tom, Hirth, Johannes
Measurement is a fundamental building block of numerous scientific models and their creation. This is in particular true for data driven science. Due to the high complexity and size of modern data sets, the necessity for the development of understand
Externí odkaz:
http://arxiv.org/abs/2102.02576
Autor:
Hanika, Tom, Hirth, Johannes
Publikováno v:
Information Sciences, 613, 2022, 453-468
We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i.e., continuous maps between closure systems, and derive a canonical representation. Moreover, we prove said scale-measures are lattice ordered wi
Externí odkaz:
http://arxiv.org/abs/2012.05267
Knowledge graphs have recently become the state-of-the-art tool for representing the diverse and complex knowledge of the world. Examples include the proprietary knowledge graphs of companies such as Google, Facebook, IBM, or Microsoft, but also free
Externí odkaz:
http://arxiv.org/abs/1902.00916
Publikováno v:
Discrete Applied Mathematics Volume 273 (2020), Pages 30-42
We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solve
Externí odkaz:
http://arxiv.org/abs/1807.06149
Autor:
Hanika, Tom, Zumbrägel, Jens
Publikováno v:
Graph-Based Representation and Reasoning, 120-134, LNAI 10872, Springer
In domains with high knowledge distribution a natural objective is to create principle foundations for collaborative interactive learning environments. We present a first mathematical characterization of a collaborative learning group, a consortium,
Externí odkaz:
http://arxiv.org/abs/1712.08858
We revisit the notion of probably approximately correct implication bases from the literature and present a first formulation in the language of formal concept analysis, with the goal to investigate whether such bases represent a suitable substitute
Externí odkaz:
http://arxiv.org/abs/1701.00877
Autor:
Tom Hanika, Johannes Hirth
Publikováno v:
Information Sciences. 613:453-468
We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i.e., continuous maps between closure systems, and derive a canonical representation. Moreover, we prove said scale-measures are lattice ordered wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92086e36096b462f890b87d127a560e7
https://doi.org/10.1016/j.ins.2022.09.005
https://doi.org/10.1016/j.ins.2022.09.005
