In the era of Big Data, knowledge integration is key for tasks such as social media aggregation, opinion mining, and cyber-issue detection. The integration of different kinds of knowledge coming from multiple sources, however, is often a problematic issue as it either requires a lot of manual effort in defining aggregation rules or suffers from noise generated by automatic integration technique...

The goal of conceptual clustering is to build a set of embedded classes, which cluster objects based on their similarities. Knowledge organization aims at generating the set of most specific classes: the Generalization Space. It has applications in the field of data mining, knowledge indexation or knowledge acquisition. Efficient algorithms have been proposed for data described in <attribute, v...

Exploring art from a different culture without prior knowledge of the domain is difficult. Though traditionally experts are required to guide people through the unknown knowledge base, the use of linked data can help consumers to explore for themselves. In this paper, we use clustering methods to create a faceted hierarchy for the exploration and recommendation of Japanese artists to tourists v...

In this paper, we propose an effective and efficient approach for compressing Bengali Text. This paper focuses on a methodical study on Bengali text compression techniques. The main target of this research is to provide a framework for Bengali text compression; which ensures a simple and computationally inexpensive effective scheme for Bengali text compression. The proposed Bengali text compres...

Change of attitude of organizations’ managers toward human forces (as human capitals and resources) as well as technological advancement and accumulation of information in organizations reflects the necessity of valuing knowledge management. On the other hand, extraction of necessary, appropriate information and turning them into the knowledge required by organizations for making decisions, vis...

FCA is a mathematical formalism having many applications in data mining and knowledge discovery. Originally it deals with binary data tables. However, there is a number of extensions that enrich standard FCA. In this paper we consider two important extensions: fuzzy FCA and pattern structures, and discuss the relation between them. In particular we introduce a scaling procedure that enables rep...

FCA is a mathematical formalism having many applications in data mining and knowledge discovery. Originally it deals with binary data tables. However, there is a number of extensions that enrich standard FCA. In this paper we consider two important extensions: fuzzy FCA and pattern structures, and discuss the relation between them. In particular we introduce a scaling procedure that enables rep...

Since its development attribute exploration was successfully applied in different fields, proving itself as a strong tool for knowledge acquisition. However, the disadvantage of this method is that it can be applied only for binary data. The growing number of applications of fuzzy logic in numerous domains including formal concept analysis makes it a natural wish to generalise the powerful tech...