Annotated Suffix Tree Method for German Compound Splitting

Миркин Б. Г., Фролов Д. С., Vlasov A. и др., , 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.

Добавлено: 13 ноября 2020 г.

A Hybrid Approach to Interpretable Analysis of Research Paper Collections

Миркин Б. Г., Фролов Д. С., Власов А. С. и др., , in: WIMS 2020: Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics.: Association for Computing Machinery (ACM), 2020. P. 184–189.

Добавлено: 28 августа 2020 г.

Computational Generalization in Taxonomies Applied to: (1) Analyze Tendencies of Research and (2) Extend User Audiences

Фролов Д. С., Миркин Б. Г., Nascimento S. и др., , in: Intelligent Data Engineering and Automated Learning – IDEAL 2019Vol. 2.: Springer, 2019. P. 3–11.

Добавлено: 7 декабря 2019 г.

Intelligent Data Engineering and Automated Learning – IDEAL 2019

Springer, 2019.

Добавлено: 7 декабря 2019 г.

Using Taxonomy Tree to Generalize a Fuzzy Thematic Cluster

Фролов Д. С., Миркин Б. Г., Nascimento S. и др., , in: Fuzzy Systems (FUZZ-IEEE), IEEE International Conference Proceedings.: IEEE, 2019. P. 1–6.

Добавлено: 30 октября 2019 г.

Parsimonious Generalization of Fuzzy Thematic Sets in Taxonomies Applied to the Analysis of Tendencies of Research in Data Science

Фролов Д. С., Nascimento S., Fenner T. и др., Information Sciences 2020 Vol. 512 P. 595–615

Добавлено: 9 октября 2019 г.

Globally Optimal Parsimoniously Lifting a Fuzzy Query Set Over a Taxonomy Tree

Фролов Д. С., Миркин Б. Г., Nascimento S. и др., , in: Optimization of Complex Systems: Theory, Models, Algorithms and Applications.: Switzerland: Springer Publishing Company, 2020. P. 779–789.

Добавлено: 25 июня 2019 г.

CONTENT 2019, The Eleventh International Conference on Creative Content Technologies

International Academy, Research, and Industry Association (IARIA), 2019.

Добавлено: 4 июня 2019 г.

Method for Generalization of Fuzzy Sets

Фролов Д. С., Миркин Б. Г., Nascimento S. и др., , in: International Conference on Artificial Intelligence and Soft Computing. 18th International Conference, ICAISC 2019, Zakopane, Poland, June 16–20, 2019, Proceedings* 1. Issue 11508.: Cham: Springer, 2019. P. 273–286.

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 ...

Добавлено: 3 июня 2019 г.

International Conference on Artificial Intelligence and Soft Computing. 18th International Conference, ICAISC 2019, Zakopane, Poland, June 16–20, 2019, Proceedings

Cham: Springer, 2019.

The two-volume set LNCS 11508 and 11509 constitutes the refereed proceedings of of the 18th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2019, held in Zakopane, Poland, in June 2019. The 122 revised full papers presented were carefully reviewed and selected from 333 submissions. The papers included in the first volume are organized in the ...

Добавлено: 3 июня 2019 г.

Comparison of String Similarity Measures for Obscenity Filtering

Артемова Е. Л., , in: Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing.: Stroudsburg, PA: Association for Computational Linguistics, 2017. P. 97–101.

Добавлено: 10 октября 2017 г.

Annotated suffix trees for text clustering

Артемова Е. Л., Ильвовский Д. А., , in: The 3d International Workshop on Concept Discovery in Unstructured Data (CDUD 2016). Proceedings of the Third Workshop on Concept Discovery in Unstructured Data co-located with the 13th International Conference on Concept Lattices and Their Applications (CLA 2016), Moscow, Russia, July 18, 2016. CEUR Workshop ProceedingsVol. 1625.: Aachen: CEUR Workshop Proceedings, 2016. P. 25–31.

In this paper an extension of tf-idf weighting on annotated suffix tree (AST) structure is described. The new weighting scheme can be used for computing similarity between texts, which can further serve as in input to clustering algorithm. We present preliminary tests of us-ing AST for computing similarity of Russian texts and show slight im-provement ...

Добавлено: 26 октября 2016 г.

Some thoughts on using annotated suffix trees for Natural Language Processing

Артемова Е. Л., , in: 2nd Workshop on Interactions Between Data Mining and Natural Language Processing, DMNLP 2015; Porto; Portugal; 7 September 2015Issue 1410.: Aachen: CEUR-WS, 2015. P. 5–18.

The paper defines an annotated suffix tree (AST) - a data structure used to calculate and store the frequencies of all the fragments of the given string or a collection of strings. The AST is associated with a string to text scoring, which takes all fuzzy matches into account. We show how the AST and ...

Добавлено: 8 октября 2015 г.

Refining a Taxonomy by Using Annotated Suffix Trees and Wikipedia Resources

Артемова Е. Л., Миркин Б. Г., Annals of Data Science 2015 Vol. 2 No. 1 P. 61–82

Добавлено: 27 мая 2015 г.

An approach to the problem of annotation of research publications

Артемова Е. Л., , in: Proceedings of The Eighth International Conference on Web Search and Data Mining.: NY, United States of America: ACM, 2014. Ch. 58 P. 429–434.

Добавлено: 8 декабря 2014 г.

Conceptual maps: construction over a text collection and analysis

E. Morenko, Артемова Е. Л., Миркин Б. Г., , in: Analysis of Images, Social Networks and Texts Third International Conference, AIST 2014, Yekaterinburg, Russia, April 10-12, 2014, Revised Selected PapersVol. 439.: Berlin: Springer, 2014. P. 163–169.

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Добавлено: 28 ноября 2014 г.