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Nowadays Information Retrieval (IR) is difficult because of huge amount of information published on the Internet. So it is very relevant to organize documents based on its content. The proposed work address this issue by generating concepts from the documents and these documents are grouped based on a data mining approach. To generate the concept, keywords are extracted from the documents but the...
Expertise retrieval has already gained significant interest in the area of information retrieval due to multitude of concrete application contexts where search for specific experts is required. In this paper, we introduce a formal concept analysis approach for clustering of a group of experts with respect to given subject areas. Initially, the domain of interest is presented at some level of abstraction...
This paper presents a new method for automatically extracting smartphone users' contextual behaviors from the digital traces collected during their interactions with their devices. Our goal is in particular to understand the impact of users' context (e.g., location, time, environment, etc.) on the applications they run on their smartphones. We propose a methodology to analyze digital traces and to...
In a world full of connections between people and objects, new needs arise requiring multidisciplinary analysis of these new networks. This work presents a approach to analyze an Internet Service Provider (ISP) database using a minimal cover of implications extracted from formal concept analysis and complex network techniques. Our goal is to analyze access to the 25 most visited websites to find access...
With an increased interest in machine processable data, many datasets are now published in RDF (Resource Description Framework) format in Linked Data Cloud. These data are distributed over independent resources which need to be centralized and explored for domain specific applications. This paper proposes a new approach based on interactive data exploration paradigm using Pattern Structures, an extension...
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...
The goal of feature extraction in multimedia mining is to discover important features for represented into a form that can represent information of multimedia data. Sequential pattern is one form of data representation formed of a number of elements that appear in sequence. The goal of this study is to analyze sequential pattern representation performancy to improve accuracy and efficiency. Analysis...
Formal concept analysis and rough set theory have both similarities and differences. Although both are on the base of some data table, they provide two different methods for data mining and knowledge acquisition. At first, this paper discusses differences and relations between the extension of formal concepts in formal concept analysis and the equivalence classes of the rough set theory. Then, by...
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...
Recently, there has been rapid growth in the volume of digital data from semi-structured and unstructured sources, such as web pages, images, videos, tweets, blog posts, and emails. The volume of data increases daily, making it difficult to access the data efficiently. To tackle the problems, we can represent the data in a summarised form using fuzzy formal concept lattices. In a situation where data...
Formal Concept Analysis is a theoretical framework which structures a set of objects described by properties. Formal Concept Analysis is a classification technique that takes data sets of objects and their attributes, and extracts relations between these objects according to the attributes they share. This structure reveals and categorizes commonalities and variability in a canonical form. From this...
Feature location is an activity to identify correspondence between features in a system and program elements in source code. After a feature is located, developers need to understand implementation structure around the location from static and/or behavioral points of view. This paper proposes a semi-automatic technique both for locating features and exposing their implementation structures in source...
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...
As a new tool of data analysis and knowledge processing, formal concept analysis has drawn more and more attention in various fields. This research focuses on prescriptions of GuiZhi Decoction, which is from Zhongjing Zhang's Treatise on Cold Pathogenic Diseases. First, we constructed the database for prescriptions of GuiZhi Decoction based on the prescriptions' names, the concept extraction and formal...
In conventional approaches, documents are represented by the vector whose dimensionalities are equivalent to the terms extracted from a document set. These approaches, called bag-of-term approaches, ignore the conceptual relationships between terms such as synonyms, hypernyms and hyponyms. In the past, researches have applied thesauri such as Word Net to solve this problem. However, thesauri such...
Concept lattices are being used in the area of knowledge discovery and data mining. Since the information used to create a formal context may have some uncertainty associated with it, a variety of methods have been proposed to create fuzzy formal contexts and to transform these into fuzzy concept lattices. This paper reviews two of these methods to creating fuzzy concept lattices: the one-sided thresholding...
Crosscutting concerns cannot be well modularized in object-oriented software. The implementation of a crosscutting concern is typically scattered over many locations and tangled with the implementation of other concerns. The presence of crosscutting concerns is one of the major problems in software understanding and evolution. Aspect-oriented programming offers mechanisms to factor them out into a...
Knowledge discovery is important for systems that have computational intelligence in helping them learn and adapt to changing environments. By representing, in a formal way, the context in which an intelligent system operates, it is possible to discover knowledge through an emerging data technology called Formal Concept Analysis (FCA). This paper describes a tool called FcaBedrock that converts data...
The notions and algorithms of generating basis for exactness rules and the proper basis for conditional rules of redescription database are presented using closure operator of Galois connection based on the operations of formal concept analysis (FCA). It is demonstrated that constructed rules of redescription database are minimal non-redundant. At the same time, a new algorithm, i.e. non-redundant...
Triadic concept analysis departs from the dyadic case by taking into account modi, such as time instances or conditions, under which objects have attributes. That is, instead of a two-dimensional table filled with 0s and 1s (equivalently, binary relation or two-dimensional binary matrix) which represents the input data to (dyadic) formal concept analysis, the input data to triadic concept analysis...
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