Interpretation of Fuzzy Attribute Subsets in Generalized One-Sided Concept Lattices

In this paper we describe possible interpretation and reduction of fuzzy attributes in Generalized One-sided Concept Lattices (GOSCL). This type of concept lattices represent generalization of Formal Concept Analysis (FCA) suitable for analysis of datatables with different types of attributes. FCA as well as generalized one-sided concept lattices represent conceptual data miningmethods. With growing number of attributes the interpretation of fuzzy subsets may become unclear, hence another interpretation of this fuzzy attribute subsets can be valuable. The originality of the presented method is based on the usage of one-sided concept lattices derived from submodels of former object-attribute model by grouping attributes with the same truth value structure. This leads to new method for attribute reduction in GOSCL environment

Generalization of One-Sided Concept Lattices

We provide a generalization of one-sided (crisp-fuzzy) concept lattices, based on Galois connections. Our approach allows analysis of object-attribute models with different structures for truth values of attributes. Moreover, we prove that this method of creating one-sided concept lattices is the most general one, i.e., with respect to the set of admissible formal contexts, it produces all Galois connections between power sets and the products of complete lattices. Some possible applications of this approach are also included

Distributed Computation of Generalized One-Sided Concept Lattices on Sparse Data Tables

In this paper we present the study on the usage of distributed version of the algorithm for generalized one-sided concept lattices (GOSCL), which provides a special case for fuzzy version of data analysis approach called formal concept analysis (FCA). The methods of this type create the conceptual model of the input data based on the theory of concept lattices and were successfully applied in several domains. GOSCL is able to create one-sided concept lattices for data tables with different attribute types processed as fuzzy sets. One of the problems with the creation of FCA-based models is their computational complexity. In order to reduce the computation times, we have designed the distributed version of the algorithm for GOSCL. The algorithm is able to work well especially for data where the number of newly generated concepts is reduced, i.e., for sparse input data tables which are often used in domains like text-mining and information retrieval. Therefore, we present the experimental results on sparse data tables in order to show the applicability of the algorithm on the generated data and the selected text-mining datasets

USE OF E-PARTICIPATION TOOLS FOR SUPPORT OF POLICY MODELLING AT REGIONAL LEVEL

This paper describes application-specific and technology specifications related to ICT-based approach for the support of policy modelling as proposed in the EU funded FP7 ICT OCOPOMO project. In this particular approach strategic planning is supported by a combination of narrative scenarios, agent-based modelling, and e-Participation tools (all integrated via an ICT e-Governance platform). The policy model for a given domain is created iteratively using cooperation of several stakeholder groups (decision makers, analysts, companies, civic society, and the general public). In this paper we will provide principles and key concepts of collaborative policy modelling, but the main focus is on the discussion of high-level architecture of ICT tools and software components, envisioned platform functionality and preliminary view of detailed architecture and technological details for implementation and integration of software components. An overall approach is presented also from the view of a particular pilot application, built around development of a strategy of renewable energy use. The process of development of a new strategy is described using standard BPMN. The process models correspond to AS-IS and TO-BE (i.e. after incorporation of scenario generation and policy modelling) situations

DESIGN OF AN APPLICATION FOR AN EXPERIMENTAL IDENTIFICATION OF A SYSTEM IN MATLAB/SIMULINK ENVIRONMENT

This paper focuses on creating an application in the MATLAB/Simulink environment for experimental identification of a system. It theoretically characterizes the experimental identification of a system and the choice and classification of identification methods. It also describes chosen methods of experimental identification (deterministic methods, neural networks) in details. A proposal of an application consisting of a user interface and a generated model scheme are also mentioned. The testing results on data from a small turbojet engine MPM-20 are shown. Based on the comparison of real measured values and output values of the model the application evaluates the accuracy of each of the identification methods. The main contribution of the proposed application is an automatization and simplification of the experimental identification process in MATLAB

Use of Concept Lattices for Data Tables with Different Types of Attributes

In this paper we describe the application of Formal Concept Analysis (FCA) for analysis of data tables with different types of attributes. FCA represents one of the conceptual data mining methods. The main limitation of FCA in classical case is the exclusive usage of binary attributes. More complex attributes then should be converted into binary tables. In our approach, called Generalized One-Sided Concept Lattices, we provide a method which deal with different types of attributes (e.g., ordinal, nominal, etc.) within one data table. Therefore, this method allows to create same FCA-based output in form of concept lattice with the precise many-valued attributes and the same interpretation of concept hierarchy as in the classical FCA, without the need for specific unified preprocessing of attribute values

Interaktívna vizualizácia hierarchických štruktúr

V súčasnosti existuje množstvo dát v digitálnej podobe. Tieto dáta obsahujú informácie, ktoré môžu byť potencionálne užitočné napr. pre spoloč-nosti pri podpore rozhodovania. Na extrakciu informácií z dát je možné použiť širokú škálu metód analýzy dát. Problémom pri analýze dát je interpretácia jej výsledkov koncovým používateľom, tak aby získané informácie dokázali po-chopiť a následne vhodným spôsobom využiť. Jednou z možností ako čo naj-rýchlejšie porozumieť výsledkom je ich transformácia do grafickej podoby. Preto sa v tomto článku zameriame na prezentáciu rozličných vizualizačných techník určených na vizualizáciu výsledkov získaných z hierarchických metód analýzy dát akou je napr. formálna konceptová analýza

Hierarchické prístupy k modelovaniu témy v dokumentoch

Digitálne textové dáta predstavujú v dnešnej dobe dôležitý zdroj in-formácií. Avšak v súčasnosti je ich počet taký obrovský, že ich manuálne spra-covanie a extrakcii informácií by bola časovo veľmi náročná. Existuje niekoľko spôsobov automatickej analýzy textových dát, jednou z nich je modelovanie témy, ktoré ponúka nové možnosti na vyhľadávanie, prehľadávanie a sumarizá-ciu textových dokumentov. Preto je hlavným cieľom tohto článku predstaviť rôzne metódy hierarchického modelovania téma a taktiež porovnanie vybraných modelov z pohľadu kvality budovania hierarchie tém