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Recommender-based Multiple Classifier System
P. 21-30.
Kashnitsky Y.
The paper briefly introduces multiple classifer 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 of assigning a classifier to each object is based on Formal Concept Analysis. We explain the idea of the algorithm with a toy example and describe our first experiments with real-world datasets.
Publication based on the results of:
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
Bardukov A., В кн. : МЕЖДИСЦИПЛИНАРНЫЕ ПРОБЛЕМЫ ЧЕЛОВЕКО-МАШИННОГО ВЗАИМОДЕЙСТВИЯ. : М. : ОнтоПринт, 2023. С. 48-54.
The article considers the possibility of using multimodal methods of information transfer to solve the search problem in the image corpus. The solution is to build a recommender system that solves the problem in two stages: selection of candidates and ranking. Several variants of the candidate selection algorithm are presented, as well as an algorithm ...
Added: June 13, 2023
Ignatov D. I., Kaminskaya A. Y., Malioukov A. et al., , in : Proceedings of International Conference on Conceptual Structures 2014. Vol. 8577: Graph-Based Representation and Reasoning.: Springer, 2014. P. 287-292.
This paper considers a recommender part of the data anal- ysis system for the collaborative platform Witology. It was developed by the joint research team of the National Research University Higher School of Economics and the Witology company. This recommender sys- tem is able to recommend ideas, like-minded users and antagonists at the respective phases ...
Added: June 9, 2014
Springer, 2015
Proceedings of the 9th International Symposium on Intelligent Distributed Computing – IDC'2015, Guimarães, Portugal, October 2015 ...
Added: October 19, 2015
Zhuk R., Ignatov D. I., Konstantinova N., Procedia Computer Science 2014 Vol. 31 P. 928-938
We propose extensions of the classical JSM-method and the Na ̈ıve Bayesian classifier for the case of triadic relational data. We performed a series of experiments on various types of data (both real and synthetic) to estimate quality of classification techniques and compare them with other classification algorithms that generate hypotheses, e.g. ID3 and Random ...
Added: June 9, 2014
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 ...
Added: September 12, 2014
Kashnitsky Y., Kuznetsov S., , in : Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 2016). : M. : [б.и.], 2016. P. 105-112.
Decision tree learning is one of the most popular classifica- tion techniques. However, by its nature it is a greedy approach to finding a classification hypothesis that optimizes some information-based crite- rion. It is very fast but may lead to finding suboptimal classification hy- potheses. Moreover, in spite of decision trees being easily interpretable, ensembles ...
Added: October 6, 2016
Gerasimova O., Makarov I., , in : Advances in Computational Intelligence. IWANN 2019. : Berlin : Springer, 2019. P. 667-677.
In this paper, we study the problem of predicting quantity of collaborations in co-authorship network. We formulated our task in terms of link prediction problem on weighted co-authorship network, formed by authors writing papers in co-authorship represented by edges between authors in the network. Our task is formulated as regression for edge weights, for which ...
Added: July 29, 2019
CEUR-WS.org, 2020
The CLA conference is an international forum for researchers, practitioners and students dedicated to the practice of Formal Concept Analysis (FCA) and areas closely related to it, including data analysis and mining, information retrieval, knowledge management, knowledge engineering, logic, algebra and lattice theory.
The 15th of CLA, CLA 2020, was going to be held in Tallinn, Estonia ...
Added: October 30, 2020
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 ...
Added: December 3, 2012
Romov P. A., Sokolov E., , in : Proceedings of the 2015 International ACM Recommender Systems Challenge. : NY : ACM, 2015.
In this paper, we describe the winning approach for the RecSys Challenge 2015. Our key points are (1) two-stage classification, (2) massive usage of categorical features, (3) strong classifiers built by gradient boosting and (4) threshold optimization based directly on the competition score. We describe our approach and discuss how it can be used to ...
Added: February 24, 2016
M. : [б.и.], 2016
The four 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, the second one with IJCAI 2013 in Beijing, ...
Added: October 6, 2016
Makarov I., Gerasimova O., , in : Proceedings of the 14th International Workshop on Semantic and Social Media Adaptation and Personalization. : NY : IEEE, 2019. P. 1-6.
In this paper, we study the problem of predicting collaborations in co-authorship network. We formulated our task in terms of link prediction problem on weighted co-authorship network, in which authors play the role of nodes, and weighted edges connecting two authors are formed by storing either a number or quality metric of research papers co-authored ...
Added: July 30, 2019
Kashnitsky Y., Kuznetsov S., , in : CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop Proceedings. Vol. 1624.: M. : Higher School of Economics, National Research University, 2016. Ch. 19. P. 189-202.
Nowadays decision tree learning is one of the most popular classification and regression techniques. Though decision trees are not accurate on their own, they make very good base learners for advanced tree-based methods such as random forests and gradient boosted trees. However, applying ensembles of trees deteriorates interpretability of the final model. Another problem is ...
Added: October 6, 2016
Сендерович М. А., В кн. : Межвузовская научно-техническая конференция студентов, аспирантов и молодых специалистов им. Е.В. Арменского. : М. : МИЭМ НИУ ВШЭ, 2019. С. 223-224.
Данная работа посвящена актуальной теме автоматизации в машинном обучении на примере создания универсальной рекомендательной системы. В работе исследуются различные типы рекомендательных систем, акцент делается на подходы коллаборативной фильтрации. Изучаются методы автоматизации машинного обучения, на основе которых будет разработана данная рекомендательная система. ...
Added: October 31, 2020
Buzmakov A. V., В кн. : МАШИННОЕ ОБУЧЕНИЕ В ИССЛЕДОВАНИЯХ МЕДИКО-БИОЛОГИЧЕСКИХ И СОЦИАЛЬНО-ЭКОНОМИЧЕСКИХ ДАННЫХ. : СПб. : Федеральное государственное автономное образовательное учреждение высшего образования "Санкт-Петербургский политехнический университет Петра Великого", 2020. С. 284-333.
In many practical tasks it is needed to estimate an effect of treatment on individual level. For example, in medicine it is essential to determine the patients that would benefit from a certain medicament. In marketing, knowing the persons that are likely to buy a new product would reduce the amount of spam. In this ...
Added: December 7, 2021
Ignatov D. I., Poelmans J., , in : Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems. : Hershey : IGI Global, 2012. Ch. 8. P. 185-195.
Recommender systems are becoming an inseparable part of many modern Internet web sites and web shops. The quality of recommendations made may significantly influence the browsing experience of the user and revenues made by web site owners. Developers can choose between a variety of recommender algorithms; unfortunately no general scheme exists for evaluation of their ...
Added: December 3, 2012
Ignatov D. I., Kaminskaya A. Y., Konstantinova N. et al., , in : Proceedings of The 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2014, 11-14 August 2014 Warsaw, Poland. : Los Alamitos, Washington, Tokyo : IEEE Computer Society, 2014. P. 327-335.
This paper discusses the recommender models and methods for crowdsourcing platforms. These models are based on modern methods of data analysis of object-attribute data, such as Formal Concept Analysis and biclustering. In particular, the paper is focused on the solution of two tasks – idea and antagonists recommendation – on the example of crowdsourcing platform ...
Added: June 9, 2014
Makarov I., Gerasimova O., Sulimov P. et al., , in : Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science. Vol. 11179.: Berlin : Springer, 2018. P. 32-38.
Co-authorship networks contain invisible patterns of collaboration among researchers. The process of writing joint paper can depend of different factors, such as friendship, common interests, and policy of university. We show that, having a temporal co-authorship network, it is possible to predict future publications. We solve the problem of recommending collaborators from the point of ...
Added: September 5, 2018
Ignatov D. I., Ненова Е. Н., Konstantinov A. V. et al., , in : Artificial Intelligence: Methodology, Systems, and Applications 16th International Conference, AIMSA 2014, Varna, Bulgaria, September 11-13, 2014. Proceedings. Vol. 8722.: Dordrecht, L., Cham, Heidelberg, NY : Springer, 2014. P. 47-58.
We propose a new approach for Collaborative filtering 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 an SVD-based one in terms of Mean Average Error (MAE). One of the experimental consequences is that it is enough to ...
Added: October 20, 2014
Ignatov D. I., Zhuk R., Konstantinova N., , in : Proceedings of The 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2014, 11-14 August 2014 Warsaw, Poland. : Los Alamitos, Washington, Tokyo : IEEE Computer Society, 2014. P. 474-480.
We propose extensions of the classical JSM-method andtheNa ̈ıveBayesianclassifierforthecaseoftriadicrelational data. We performed a series of experiments on various types of data (both real and synthetic) to estimate quality of classification techniques and compare them with other classification algorithms that generate hypotheses, e.g. ID3 and Random Forest. In addition to classification precision and recall we also ...
Added: June 9, 2014
Kashnitsky Y., Ignatov D. I., Интеллектуальные системы. Теория и приложения 2015 Т. 19 № 4 С. 37-55
The paper makes a brief introduction into multiple classifier systems and describes a particular algorithm which improves classification accuracy by making a recommendation of an algorithm to an object. This recommendation is done under a hypothesis that a classifier is likely to predict the label of the object correctly if it has correctly classified its ...
Added: December 7, 2015
Ignatov D. I., Корнилов Д. И., , in : Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at IJCAI 2015). : Buenos Aires : [б.и.], 2015. P. 87-98.
We propose a new algorithm for recommender systems with numeric ratings which is based on Pattern Structures (RAPS). As the input the algorithm takes rating matrix, e.g., such that it contains movies rated by users. For a target user, the algorithm returns a rated list of items (movies) based on its previous ratings and ratings ...
Added: October 23, 2015
University Rennes 1, 2017
This volume is the supplementary volume of the 14th International Conference on Formal Concept Analysis (ICFCA 2017), held from June 13th to 16th 2017, at IRISA, Rennes. The ICFCA conference series is one of the major venues for researches from the field of Formal Concept Analysis and related areas to present and discuss their recent ...
Added: June 19, 2017