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Recently α-cut irreducible and δ1δ2-multi-adjoint concept lattices have been introduced as two different methodologies focus on reducing the size of a given fuzzy concept lattice. The philosophy of both methodologies is completely different and so, the obtained lattices too. This paper analyzes the differences and proposes that the best is to combine both methodologies in order to obtain new procedures...
Formal concept analysis is a mathematics research field introduced in the beginning of the 1980s by Rudolf Wille, that has been applied in several different knowledge areas, including Computer Science. FCA is a data analysis theory that identifies conceptual structures within data sets or formal contexts. In this work, we propose an FCA-based approach to build minimal implication rules-based computational...
We describe our web-based system for the analysis of students' results on the course Fundamentals of Electrical Engineering by applying the method of Formal Concept Analysis. We have focused on the students' answers and constructed their concept lattices or taxonomies of the subject matter. Finally, we have shown that this approach corresponds well with the actual students' overall results and final...
We study the novel problem of finding new, prominent situational facts, which are emerging statements about objects that stand out within certain contexts. Many such facts are newsworthy—e.g., an athlete's outstanding performance in a game, or a viral video's impressive popularity. Effective and efficient identification of these facts assists journalists in reporting, one of the main goals of computational...
The design of class models for information systems, databases or programming is a delicate process in which experts of the domain and designers have to identify and agree on the domain concepts. Formal Concept Analysis (FCA) has been proposed for supporting this collaborative work and fostering the emergence of higher level entities and the factorization of descriptions and behaviors. More recently,...
Association rule discovery, as the kernel task of data mining, has been studied widely. However, most algorithms based on frequent item sets have to scan databases many times. This reduces the algorithms' efficiency. Formal concept analysis is a useful tool in many fields. In this paper, an association rule mining algorithm is proposed based on the formal concept analysis. Through analysis the relationship...
Preserving data quality is an important issue in data collection management. One of the crucial issues hereby is the detection of duplicate objects (called coreferent objects) which describe the same entity, but in different ways. In this paper we present a method for detecting coreferent objects in metadata, in particular in XML schemas. Our approach consists in comparing the paths from a root element...
This paper introduces a method for head expert identification in a social network based on local community detection and formal concept analysis. There are several methods for expert identification, but most of these methods try to find an expert for a particular area. In this paper, we propose a novel approach to identify a head expert. This person is in the background and most of the time he is...
Galois lattices' (GLs) definition is defined for a binary table (called context). Therefore, in the presence of continuous data, a discretization step is needed. Discretization is classically performed before the lattice construction in a global way. However, local discretization is reported to give better classification rates than global discretization when used jointly with other symbolic classification...
In this paper we describe incremental algorithm for generalized one-sided concept lattices based on the Galois connections within Formal Concept Analysis (FCA) framework, which allows to analyse object-attribute models with different structures for truth values of attributes. Therefore, this method provide interesting opportunity for researcher or data analyzer to work with any type of attributes...
Product horizontal link library is composed of the found the library, the update of the library, irrelative data entry, as well as data update. We use granular computing in design process of the library. Each module needs to interact with the category tree, which is essential to the realization of the system. Category tree's establishment contains two steps: first, reduction attributes; secondly,...
Conceptual Landscapes is a paradigm of Knowledge Representation which is grounded on Conceptual Knowledge Processing. Using the mathematical apparatus of Formal Concept Analysis, we discuss several issues related to the study of adverse drug reactions in oncology using conceptual landscapes. We propose a new approach in investigating adverse drug reactions based on the paradigm of Conceptual Knowledge...
The properties of data and activities in business processes can be used to greatly facilitate several relevant tasks performed at design-and run-time, such as fragmentation, compliance checking, or top-down design. Business processes are often described using workflows, and we present an approach to mechanically infer business domain-specific attributes of workflow components, including data items,...
The theories of concept lattice expansion and recovery were presented in this paper. Firstly, a formal context can be reduced from the viewpoint of objects or attributes by inclusion reduction, and its corresponding concept lattice can be constructed. And then, the concept lattice can be expanded dynamically according to the need, thus, the concept lattice of original formal context can be recovered...
We study the problem of factor analysis of three-way binary data, i.e. data described by a 3-dimensional binary matrix I, describing a relationship between objects, attributes, and conditions. The problem consists in finding a decomposition of I into three binary matrices, an object-factor matrix A, an attribute-factor matrix B, and a condition-factor matrix C, with the number of factors as small...
Concept lattice (Galois lattice) is an efficient tool for data analysis and rule extraction from multidimensional space. This paper introduces some definitions of concept lattice, and compares two methods of data inductive: AOI and concept lattice. After introduce the context, actual medical data is discretized and concept lattice and Hasse diagram are constructed to generate the concept hierarchy,...
In this paper, a similarity evaluating model based on rough formal concept analysis and information content similarity is proposed which evaluates the similarity degree between the concepts. We use the information content approach to automatically obtain part of similarity scores of two concepts which makes up the normal featural and structural evaluating models. Then through our model, the similarity...
XML (eXtensible Markup Language) documents are the main format for publishing and interchanging data on the Web. Integrity constraints are essential in data design. Functional dependencies are the most important semantic constraints. Functional dependencies satisfied by XML data have been introduced recently. Formal Concept Analysis (FCA) is a mathematical theory of concept hierarchies which is based...
This paper describes a convenient method of processing and contextualizing information extracted from social networking systems such as Myspace, Facebook or Hi5 users in real-time by using the Yahoo! Pipes feed mash-up service and formal concept analysis. Interests referring to media consumption (favorite movies, favorite music, favorite books or role models) declared by users can be expanded into...
The intelligent help system (IHS) is an important assistant platform, especially in online teaching system. At present most search methods of the help systems are mainly based on keyword matches in database query or hierarchical classifications. The outstanding problem is that users are required to have a certain ability of organizing Keywords, otherwise insufficient keywords would limit the query,...
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