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Modeling Generalization in Domain Taxonomies Using a Maximum Likelihood Criterion
P. 141–147.
We define a most specific generalization of a fuzzy set of topics assigned to leaves of the rooted tree of a domain taxonomy. This generalization lifts the set to its “head subject” node in the higher ranks of the taxonomy tree. The head subject is supposed to “tightly” cover the query set, possibly involving some errors referred to as “gaps” and “offshoots”. We develop a method to globally maximize the likelihood of a scenario involving gains and losses of the general concept manifested in a fuzzy cluster of leaf nodes of the taxonomy. Probabilities of the gain and loss events are derived from multiple runs of our earlier method of maximum parsimony starting with randomly generated values for the two parameters involved. Supplemented with fuzzy c-means clustering, this allows us to obtain meaningful generalizations for six fuzzy thematic clusters of Data Science topics using over 17000 abstracts from 17 research journals published by Springer.
Alekseev A., Chaichuk M., Butko M. et al., , in: 30th International Conference on Applications of Natural Language to Information Systems, NLDB 2025, Kanazawa, Japan, July 4–6, 2025, Proceedings, Part I. Natural Language Processing and Information Systems. (LNCS, volume 15836)* I. Vol. 15836.: Springer, 2025. P. 426–441.
Large language models excel in question-answering (QA) but struggle with multi-hop reasoning and temporal questions. Query-based knowledge graph QA (KGQA) offers a modular alternative by generating executable queries instead of direct answers. We explore multi-stage query-based framework for WikiData QA, proposing multi-stage approach that enhances performance on challenging multi-hop and temporal benchmarks. Through generalization and ...
Added: February 3, 2026
Belomestny D., Ulyanov V. V., Butucea C. et al., Springer Publishing Company, 2023.
This book contains contributions from the participants of the international conference “Foundations of Modern Statistics” which took place at Weierstrass Institute for Applied Analysis and Stochastics (WIAS), Berlin, during November 6–8, 2019, and at Higher School of Economics (HSE University), Moscow, during November 30, 2019. The events were organized in honor of Professor Vladimir Spokoiny ...
Added: November 30, 2023
Springer, 2022.
This book covers the following main topics: A) information and knowledge management; B) organizational models and information systems; C) software and systems modeling; D) software systems, architectures, applications and tools; E) multimedia systems and applications; F) computer networks, mobility and pervasive systems; G) intelligent and decision support systems; H) big data analytics and applications; I) ...
Added: November 18, 2022
Mirkin B., Frolov D., Vlasov A. et al., , in: Intelligent Data Engineering and Automated Learning – IDEAL 2020/ 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part IIVol. 12490: Lecture Notes in Computer Science.: Cham: Springer, 2020. P. 423–433.
We define and find a most specific generalization of a fuzzy set of topics assigned to leaves of the rooted tree of a taxonomy. This generalization lifts the set to a “head subject” in the higher ranks of the taxonomy, that is supposed to “tightly” cover the query set, possibly bringing in some errors, both ...
Added: November 13, 2020
Mirkin B., Frolov D., Vlasov A. et al., , in: WIMS 2020: Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics.: Association for Computing Machinery (ACM), 2020. P. 184–189.
We define and find a most specific generalization of a fuzzy set of topics assigned to leaves of the rooted tree of a taxonomy. This generalization lifts the set to a “head subject” in the higher ranks of the taxonomy, that is supposed to “tightly” cover the query set, possibly bringing in some errors, both ...
Added: August 28, 2020
Springer, 2019.
We define a most specific generalization of a fuzzy set of
topics assigned to leaves of the rooted tree of a domain taxonomy. This
generalization lifts the set to its “head subject” node in the higher ranks
of the taxonomy tree. The head subject is supposed to “tightly” cover
the query set, possibly bringing in some errors referred to ...
Added: December 7, 2019
Frolov D., Nascimento S., Fenner T. et al., Information Sciences 2020 Vol. 512 P. 595–615
This paper proposes a novel method, referred to as ParGenFS, for finding a most specific generalization of a query set represented by a fuzzy set of topics assigned to leaves of the rooted tree of a taxonomy. The query set is generalized by “lifting” it to one or more “head subjects” in the higher ranks ...
Added: October 9, 2019
Frolov D., Taran Z., Mirkin B., , in: International Conference on Human Interaction and Emerging Technologies.: Springer, 2020. P. 837–841.
We propose a novel method for efficient target audience augmentation in programmatic digital advertising. This method utilizes a novel ParGenFS algorithm for most adequate generalization in taxonomies which was developed by the authors in a joint work. The ParGenFS extends user segments by parsimoniously lifting them off-line as a fuzzy set over IAB content taxonomy ...
Added: July 31, 2019
Frolov D., Mirkin B., Nascimento S. et al., , in: Optimization of Complex Systems: Theory, Models, Algorithms and Applications.: Switzerland: Springer Publishing Company, 2020. P. 779–789.
This paper presents a relatively rare case of an optimization problem in data analysis to admit a globally optimal solution by a recursive algorithm. We are concerned with finding a most specific generalization of a fuzzy set of topics assigned to leaves of domain taxonomy represented by a rooted tree. The idea is to “lift” ...
Added: June 25, 2019
Frolov D., Mirkin B., Nascimento S. et al., , in: CONTENT 2019, The Eleventh International Conference on Creative Content Technologies.: International Academy, Research, and Industry Association (IARIA), 2019. P. 20–25.
We define a most specific generalization of a fuzzy set of topics assigned to leaves of the rooted tree of a domain taxonomy. This generalization lifts the set to its 'head subject' in the higher ranks of the taxonomy tree. The head subject is supposed to 'tightly' cover the query set, possibly bringing in some ...
Added: June 4, 2019
International Academy, Research, and Industry Association (IARIA), 2019.
Added: June 4, 2019
Cham: Springer, 2019.
The series Lecture Notes in Computer Science (LNCS), including its subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI), has established itself as a medium for the publication of new developments in computer science and information technology research and teaching - quickly, informally, and at a high level.
The two-volume set LNCS ...
Added: June 3, 2019
Efimov E., Shevgunov T., Filimonova D., , in: 2016 17th International Radar Symposium (IRS).: IEEE, 2016. P. 1–3.
This paper presents the approach to the design of angle of arrival estimator for narrow-band noise-like signal based on artificial neural network (ANN). The multilayer perceptron type ANNs are trained to minimize the sum of squared errors or maximize the likelihood function using the deterministic approach with the data samples generated by the single station ...
Added: May 5, 2019
Savchenko A., Belova N. S., Expert Systems with Applications 2018 Vol. 108 P. 170–182
The paper deals with unconstrained face recognition task for the small sample size problem based on computation of distances between high-dimensional off-the-shelf features extracted by deep convolution neural network. We present the novel statistical recognition method, which maximizes the likelihood (joint probabilistic density) of the distances to all reference images from the gallery set. This ...
Added: May 17, 2018
Savchenko A., Компьютерная оптика 2017 Т. 41 № 3 С. 422–430
In this paper we focus on the image recognition problem in the case of small sample size based on the nearest neighbor rule and matching of high-dimensional feature vectors extracted with the deep convolutional neural network. We propose the novel recognition algorithm based on the maximum likelihood method for the joint density of dissimilarities between ...
Added: July 8, 2017
Kozunov V., Ossadtchi A., Frontiers in Neuroscience 2015 Vol. 9 No. 107
Although MEG/EEG signals are highly variable between subjects, they allow characterizing systematic changes of cortical activity in both space and time. Traditionally a two-step procedure is used. The first step is a transition from sensor to source space by the means of solving an ill-posed inverse problem for each subject individually. The second is mapping ...
Added: July 28, 2016
Panarin S. I., Труды МАИ 2011 № 44 С. 5–25
In aerospace industry one of the main issues is the problem of the qualified specialists education. During the learning process positive incentives improve the effectiveness of the education . One of such incentives is the rating system. In this work the construction and evaluation of the specialized rating system is regarded with examples on the ...
Added: December 5, 2013
Osipov D., Lecture Notes in Computer Science 2012 Vol. 7642 LNCS P. 37–48
In what follows an upper bound for the probability of erroneous decoding in a coded DHA FH OFDMA system with a noncoherent ML detector under multitone jamming is introduced. ...
Added: February 6, 2013
Lokshin M., Glinskaya E., / Series WPS "Policy Research Working Paper". 2000. No. 2376.
About 20,000 early childhood development centers provided day care for and prepared for primary school more than 1 million children aged three to seven (roughly 20 percent of children in that age group) in Kenya in 1995. The number of child care facilities reached 23,690 by the end of 1999. The authors analyze the effect ...
Added: November 14, 2012
Lokshin M., Sajaia Z., The Stata Journal 2011 Vol. 11 No. 3 P. 368–385
In this article, we describe the switch_probit command, which implements the maximum likelihood method to fit the model of the binary choice with binary endogenous regressors. ...
Added: October 15, 2012