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Metric Generalization and Modification of Classification Algorithms Based on Formal Concept Analysis
P. 43-50.
Evgeny Kolmakov
Language:
English
In book
Vol. 1257. , Prague : CEUR Workshop Proceedings, 2014
Buzmakov A. V., Kuznetsov S., Napoli A., Procedia Computer Science 2014 Vol. 31 P. 918-927
There is a lot of usefulness measures of patterns in data mining. This paper is focused on the measures used in Formal Concept Analysis (FCA). In particular, concept stability is a popular relevancy measure in FCA. Experimental results of this paper show that high stability of a pattern in a given dataset derived from the ...
Added: October 22, 2015
Buzmakov A. V., Kuznetsov S., Makhalova T. et al., , in : Proceedings of the 9th International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2021). Vol. 2972.: CEUR-WS, 2021. Ch. 2. P. 19-26.
Added: December 7, 2021
Buzmakov A. V., Kuznetsov S., Napoli A., , in : 2017 IEEE 17th International Conference on Data Mining (ICDM). : New Orleans : IEEE, 2017. Ch. 89. P. 757-762.
A scalable method for mining graph patterns stable under subsampling is proposed.
The existing subsample stability and robustness measures are not antimonotonic according to definitions known so far.
We study a broader notion of antimonotonicity for graph patterns, so that measures of subsample stability become antimonotonic. Then we propose gSOFIA for mining the most subsample-stable graph patterns.
The ...
Added: September 26, 2017
Alam M., Buzmakov A. V., Napoli A., Discrete Applied Mathematics 2018 Vol. 249 P. 2-17
With an increased interest in machine processable data and with the progress of semantic technologies, many datasets are now published in the form of RDF triples for constituting the so-called Web of Data. Data can be queried using SPARQL but there are still needs for integrating, classifying and exploring the data for data analysis and ...
Added: September 26, 2017
Dudyrev E., Kuznetsov S., , in : Proceedings of the 9th International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2021). Vol. 2972.: CEUR-WS, 2021. Ch. 9. P. 99-104.
Ensembles of decision trees, like Random Forests are efficient machine learning models with state-of-the-art prediction quality. However, their predictions are much less transparent than those of a single decision tree. In this paper, we describe a prediction model based on a single decision tree in terms of Formal Concept Analysis. We define a differential way ...
Added: December 8, 2021
Ignatov D. I., Kuznetsov S., Zhukov L. E. et al., International Journal of General Systems 2013 Vol. 42 No. 6 P. 572-593
formal concept analysis,
data mining,
triclustering,
three-way data,
folksonomy,
spectral triclustering ...
Added: October 16, 2013
Buzmakov A. V., Egho E., Jay N. et al., International Journal of General Systems 2016 Vol. 45 No. 2 P. 135-159
Nowadays data-sets are available in very complex and heterogeneous ways. Mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of “complex” sequential data by means of interesting sequential patterns. We approach the problem using the elegant mathematical framework of ...
Added: February 25, 2016
Ryzhova D., Obiedkov S., , in : CLLS 2016. Computational Linguistics and Language Science. Proceedings of the Workshop on Computational Linguistics and Language Science. Moscow, Russia, April 26, 2016. Vol. 1886.: Aachen : CEUR Workshop Proceedings, 2017. Ch. 10. P. 78-87.
In this paper, we present an application for formal concept analysis (FCA) by showing how it can help construct a semantic map for a lexical typological study. We show that FCA captures typological regularities, so that concept lattices automatically built from linguistic data appear to be even more informative than traditional semantic maps. While sometimes ...
Added: October 14, 2017
Alam M., Buzmakov A. V., Codocedo V. et al., , in : Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, July 25-31, 2015. : Palo Alto : AAAI Press, 2015. P. 823-829.
The popularization and quick growth of Linked Open Data (LOD) has led to challenging aspects regarding quality assessment and data exploration of the RDF triples that shape the LOD cloud. Particularly, we are interested in the completeness of data and its potential to provide concept definitions in terms of necessary and sufficient conditions. In this ...
Added: October 22, 2015
Leeuwenberg A., Buzmakov A. V., Toussaint Y. et al., , in : Formal Concept Analysis. 13th International Conference, ICFCA 2015, Nerja, Spain, June 23-26, 2015, Proceedings. Vol. 9113.: Springer, 2015. P. 153-168.
In this paper we explore the possibility of defining an original pattern structure for managing syntactic trees. More precisely, we are interested in the extraction of relations such as drug-drug interactions (DDIs) in medical texts where sentences are represented as syntactic trees. In this specific pattern structure, called STPS, the similarity operator is based on ...
Added: October 22, 2015
Ignatov D. I., Shestakoff A., Lecture Notes in Computer Science 2013
We propose a new FCA-based algorithm for consensus clustering FCA-Consensus. As the input the algorithm takes $n$ partitions of a certain set of objects obtained by k-means algorithm after its $n$ different executions. The resulting consensus partition is extracted from a (partial) antichain of the concept lattice built on formal context $objects \times classes$, where ...
Added: October 26, 2013
Metric Generalization and Modification of Classification Algorithms Based on Formal Concept Analysis
Kolmakov E.A., Computational Mathematics and Modeling 2015 Vol. 26 No. 4 P. 566-576
Added: December 5, 2018
Naidenova X., Buzmakov A. V., Parkhomenko V. et al., , in : Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017. Vol. 1921.: CEUR-WS.org, 2017. P. 88-103.
Symbolic classifiers allow for solving classification task and provide the reason for the classifier decision. Such classifiers were studied by a large number of researchers and known under a number of names including tests, JSM-hypotheses, version spaces, emerging patterns, proper predictors of a target class, representative sets etc. Here we consider such classifiers with restriction ...
Added: March 14, 2018
Kashnitsky Y., Ignatov D. I., , in : Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 2014). Vol. 1257.: Prague : CEUR Workshop Proceedings, 2014. Ch. 3. P. 17-26.
The paper briefly introduces multiple classifier systems and describes a new algorithm, which improves classification accuracy by means of recommendation of a proper algorithm to an object classification. This recommendation is done assuming that a classifier is likely to predict the label of the object correctly if it has correctly classified its neighbors. The process ...
Added: September 12, 2014
Buzmakov A. V., Kuznetsov S., Napoli A., , in : Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings. * 2. Vol. 9285.: Dordrecht, L., Cham, Heidelberg, NY : Springer, 2015. P. 157-172.
In pattern mining, the main challenge is the exponential explosion of the set of patterns. Typically, to solve this problem, a constraint for pattern selection is introduced. One of the first constraints proposed in pattern mining is support (frequency) of a pattern in a dataset. Frequency is an anti-monotonic function, i.e., given an infrequent pattern, ...
Added: October 22, 2015
Nenova Elena, Ignatov D. I., Konstantinov A. V., , in : Formal Concept Analysis Meets Information Retrieval 2013. Vol. 977.: Aachen : CEUR Workshop Proceedings, 2013. P. 57-73.
We propose a new approach for Collaborative ltering which is based on Boolean Matrix Factorisation (BMF) and Formal Concept Analysis. In a series of experiments on real data (Movielens dataset) we compare the approach with the SVD- and NMF-based algorithms in terms of Mean Average Error (MAE). One of the experimental con- sequences is that ...
Added: October 10, 2013
Kashnitsky Y., , in : Supplementary Proceedings of the 3rd International Conference on Analysis of Images, Social Networks and Texts (AIST 2014). Vol. 1197: Supplementary Proceedings of AIST 2014.: Ekaterinburg : CEUR Workshop Proceedings, 2014. Ch. 12. P. 69-80.
Visual analytics is a subdomain of data analysis which combines both human and machine analytical abilities and is applied mostly in decision-making and data mining tasks. Triclustering, based on Formal Concept Analysis (FCA), was developed to detect groups of objects with similar properties under similar conditions. It is used in Social Network Analysis (SNA) and ...
Added: August 28, 2014
Ignatov D. I., Kaminskaya A. Y., Konstantinov A. V. et al., , in : Conceptual Structures for STEM Research and Education, 20th International Conference on Conceptual Structures. Vol. 7735: Conceptual Structures for STEM Research and Education, 20th International Conference on Conceptual Structures.: Berlin, Heidelberg : Springer, 2013. P. 173-192.
This paper considers a data analysis system for collaborative platforms which was developed by the joint research team of the National Research University Higher School of Economics and the Witology company. Our focus is on describing the methodology and results of the first experiments. The developed system is based on several modern models and methods ...
Added: October 10, 2013
Buzmakov A. V., Napoli A., , in : Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 2016). : M. : [б.и.], 2016. P. 89-96.
FCA is a mathematical formalism having many applications
in data mining and knowledge discovery. Originally it deals with binary
data tables. However, there is a number of extensions that enrich stan
dard FCA. In this paper we consider two important extensions: fuzzy
FCA and pattern structures, and discuss the relation between them. In
particular we introduce a scaling procedure that ...
Added: October 14, 2016
Aachen : CEUR Workshop Proceedings, 2013
Formal Concept Analysis (FCA) is a mathematically well-founded theory aimed at data analysis and classication, introduced and detailed in the book of Bernhard Ganter and Rudolf Wille, \Formal Concept Analysis", Springer 1999. The area came into being in the early 1980s and has since then spawned over 10000 scientic publications and a variety of practically ...
Added: October 10, 2013
Ignatov D. I., Egurnov D., Точилкин Д. С., , in : Supplementary Proceedings ICFCA 2019 Conference and Workshops. Vol. 2378.: CEUR Workshop Proceedings, 2019. P. 137-151.
This paper presents further development of distributed multimodal clustering. We introduce a new version of multimodal clustering algorithm for distributed processing in Apache Hadoop on computer clusters. Its implementation allows a user to conduct clustering on data with modality greater than two. We provide time and space complexity of the algorithm and justify its relevance. ...
Added: October 31, 2019
Kashnitsky Y., Труды Московского физико-технического института 2014 Т. 6 № 3 С. 43-56
Triclustering is an outgrowth of Formal Concept Analysis intented to detect groups of objects with similar properties (clusters) in a context of three sets of entities. In case of social network analysis, for instance, these sets might be users, their interests and events they take part in. Triclustering here can help to detect users with ...
Added: November 8, 2013
Kaytoue M., Codocedo V., Buzmakov A. V. et al., , in : Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings. * III. Vol. 9286.: Dordrecht, L., Heidelberg, NY, Cham : Springer, 2015. P. 227-231.
This article aims at presenting recent advances in Formal Concept Analysis (2010-2015), especially when the question is dealing with complex data (numbers, graphs, sequences, etc.) in domains such as databases (functional dependencies), data-mining (local pattern discovery), information retrieval and information fusion. As these advances are mainly published in artificial intelligence and FCA dedicated venues, a ...
Added: October 23, 2015
Buzmakov A. V., Egho E., Jay N. et al., , in : CLA 2013 Proceedings of the Tenth International Conference on Concept Lattices and Their Applications. : La Rochelle : Laboratory L3i, University of La Rochelle, 2013. P. 199-210.
In this paper, we are interested in the analysis of sequential data and we propose an original framework based on FCA. For that, we introduce sequential pattern structures, an original specification of pattern structures for dealing with sequential data. Sequential pattern structures are given by a subsumption operation between set of sequences, based on subsequence ...
Added: October 22, 2015