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In this paper, we report about the current state of ToscanaJ, the latest member of the family of TOSCANA programs, that have been used for conceptual data analysis and knowledge discovery. After presenting the tool itself, we shortly describe the planned Tockit framework surrounding ToscanaJ, that will provide an Open Source toolset for programs based on Formal Concept Analysis and the planning for future development.

In the last years, the main orientation of Formal Concept Analysis (FCA) has turned from mathematics towards computer science.

this paper we propose a semiotic conceptual framework which is compatible with Peirce's definition of signs and uses formal concept analysis for its conceptual structures. The goal of our research is to improve the use of formal languages such as ontology languages and programming languages. Even though there exist a myriad of theories, models and implementations of formal languages, in practice it is often not clear which strategies to use. AI ontology language research is in danger of repeating mistakes that have already been studied in other disciplines (such as linguistics and library science) years ago

In this paper we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge Processing. Conceptual Knowledge Processing is based on the mathematical theory of Formal Concept Analysis which has become a successful theory for data analysis during the last two decades. CKDD aims to support a human-centered process of discovering knowledge from data by visualizing and analyzing the conceptual structure of the data. We dicuss how the management system TOSCANA for conceptual information systems supports CKDD, and illustrate it by two applications in database marketing and flight movement analysis. Finally, we present a new tool for conceptual deviation discovery, Chianti. 1

Abstract: We apply the graph decomposition method known as rooted level aware breadth first search to partition graph-connected formal contexts and examine some of the consequences for the corresponding concept lattices. In graph-theoretic terms, this lattice can be viewed as the lattice of maximal bicliques of the bipartite graph obtained by symmetrizing the object-attribute pairs of the input formal context. We find that a rooted breadth-first search decomposition of a graph-connected formal context leads to a closely related partition of the concept lattice, and we provide some details of this relationship. The main result is used to describe how the concept lattice can be unfolded, according to the information gathered during the breadth first search. We discuss potential uses of the results in data mining applications that employ concept lattices, specifically those involving association rules.

Abstract. Information systems must establish trust to cooperate effectively in open environments. We are developing an agent-based approach for establishing trust, where information systems are modeled as agents that provide and consume services. Agents can help each other find trustworthy parties by providing referrals to those that they trust. We propose a graph-based representation of services for modeling the trustworthiness of agents. This representation captures natural relationships among service domains and provides a simple means to accommodate the accrual of trust placed in a given party. When interpreted as a lattice, it enables less important services (e.g., low-value transactions) to be used as gates to more important services (e.g., high-value transactions). We first show that, where applicable, this approach yields superior efficiency (needs fewer messages) and effectiveness (finds more providers) than a vector representation that does not capture the relationships between services. Next, we study trade-offs between various factors that affect the performance of this approach. 1

Abstract. The Discovery of association rules is a non-supervised task of data mining. Its mostly hard step is to look for the frequent itemsets embedded into large amounts of data. Based on the theory of Formal Concept Analysis, we suggest that the notion of Formal Concept generalizes the notion of itemset, since it takes into account the itemset (as the intent) and the support (as the cardinality of the extent). Accordingly, we propose a new approach to mine interesting item-sets as the optimal concepts covering a binary table (concept coverage). This approach uses a new quality-criteria of a rule: the gain that generalizes the support criteria. 1

Abstract: Authentication lets a system know who you are, while authorization controls your resources access rights and what operations you are allow to perform. Resources have owners to whom the resources belong to. The owner knows best who is allowed to access her resources at any one time. Distribution of concerns and responsibilities can be effectively used for efficient management of enterprise wide authorization. A collection of users with similar rights to a resource can be logically grouped. Managing user groups, recourse groups, access relationships and permissions is tedious due to complex inter-relationships between actors and among actions. A Web-based application which implements a higher level abstraction of access management that mappes specific low level operating system access control can be deployed to access local manager to manage their resource access effectively and economically, which in turn will increase the system’s security level of the entire organization.

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