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August 13, 2026
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Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
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CDUD'11 – Concept Discovery in Unstructured Data Workshop co-located with the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC-2011), June 2011, Moscow, Russia

Issue 757. M. : Higher School of Economics Publishing House, 2011.
Academic editor: Ignatov D. I., Kuznetsov S., Poelmans J.

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 textual, form. Compared to traditional data mining techniques, human-centered instruments actively engage the domain expert in the discovery process. This volume contains the contributions to CDUD 2011, the International Workshop on Concept Discovery in Unstructured Data (CDUD) held in Moscow. The main goal of this workshop was to provide a forum for researchers and developers of data mining instruments working on issues with analyzing unstructured data. We are proud that we could welcome 13 valuable contributions to this volume. The majority of the accepted papers described innovative research on data discovery in unstructured texts. Authors worked on issues such as transforming unstructured into structured information by amongst others extracting keywords and opinion words from texts with Natural Language Processing methods. Multiple authors who participated in the workshop used methods from the conceptual structures field including Formal Concept Analysis and Conceptual Graphs. Applications include but are not limited to text mining police reports, sociological definitions, movie reviews, etc.

Chapters
Recommender System Based on Algorithm of Bicluster Analysis RecBi
Ignatov D. I., Poelmans J., Zaharchuk V. V., , in: CDUD'11 – Concept Discovery in Unstructured Data Workshop co-located with the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC-2011), June 2011, Moscow, RussiaIssue 757.: M.: Higher School of Economics Publishing House, 2011. P. 122–126.
In this paper we propose two new algorithms based on biclustering analysis, which can be used at the basis of a recommender system for educational orientation of Russian School graduates. The first algorithm was designed to help students make a choice between different university faculties when some of their preferences are known. The second algorithm ...
Added: December 3, 2012
Concept Relation Discovery and Innovation Enabling Technology (CORDIET)
Poelmans J., Elzinga P., Neznanov A. et al., , in: CDUD'11 – Concept Discovery in Unstructured Data Workshop co-located with the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC-2011), June 2011, Moscow, RussiaIssue 757.: M.: Higher School of Economics Publishing House, 2011. P. 53–62.
Concept Relation Discovery and Innovation Enabling Technology (CORDIET), is a toolbox for gaining new knowledge from unstructured text data. At the core of CORDIET is the C-K theory which captures the essential elements of innovation. The tool uses Formal Concept Analysis (FCA), Emergent Self Organizing Maps (ESOM) and Hidden Markov Models (HMM) as main artifacts ...
Added: December 3, 2012
Research Challenges of Dynamic Socio-Semantic Networks
Yavorskiy R., , in: CDUD'11 – Concept Discovery in Unstructured Data Workshop co-located with the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC-2011), June 2011, Moscow, RussiaIssue 757.: M.: Higher School of Economics Publishing House, 2011. P. 119–122.
A general model of socio-semantic network is presented in terms of state-transitions systems. We provide some examples and indicate research directions, which seem to us the most important from the application point of view. ...
Added: September 28, 2014
Research target: Electronics and Electrical Engineering Philology and Linguistics Mathematics Philosophy, Ethics, and Religious Studies
Priority areas: mathematics engineering science
Language: English
Full text
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Keywords: математикабикластеризацияразработка данных (Data Mining)информатикаnatural language processingнеструктурированная информацияанализ формальных понятийdata miningвычислительная техникаFormal Concept Analysisbiclusteringtext miningknowledge discoveryunstructured dataобнаружение знанийрекомендательные системыанализ текстовых данныхкибернетикаавтоматикаRecommender Systems
CDUD'11 – Concept Discovery in Unstructured Data Workshop co-located with the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC-2011), June 2011, Moscow, Russia
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