International Conference on Conceptual Structures 

About: International Conference on Conceptual Structures is an academic conference. The conference publishes majorly in the area(s): Computer science & Conceptual graph. Over the lifetime, 5895 publications have been published by the conference receiving 50400 citations.

Pattern Structures and Their Projections

Abstract: Pattern structures consist of objects with descriptions (called patterns) that allow a semilattice operation on them. Pattern structures arise naturally from ordered data, e.g., from labeled graphs ordered by graph morphisms. It is shown that pattern structures can be reduced to formal contexts, however sometimes processing the former is often more efficient and obvious than processing the latter. Concepts, implications, plausible hypotheses, and classifications are defined for data given by pattern structures. Since computation in pattern structures may be intractable, approximations of patterns by means of projections are introduced. It is shown how concepts, implications, hypotheses, and classifications in projected pattern structures are related to those in original ones.

Multi-objective Flower Algorithm for Optimization

Abstract: Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, we extend this flower algorithm to solve multi-objective optimization problems in engineering. By using the weighted sum method with random weights, we show that the proposed multi-objective flower algorithm can accurately find the Pareto fronts for a set of test functions. We then solve a bi-objective disc brake design problem, which indeed converges quickly.

Distributed Anomaly Detection in Wireless Sensor Networks

Abstract: Identifying misbehaviors is an important challenge for monitoring, fault diagnosis and intrusion detection in wireless sensor networks. A key problem is how to minimise the communication overhead and energy consumption in the network when identifying misbe-haviors. Our approach to this problem is based on a distributed, cluster-based anomaly detection algorithm. We minimise the communication overhead by clustering the sensor measurements and merging clusters before sending a description of the clusters to the other nodes. In order to evaluate our distributed scheme, we implemented our algorithm in a simulation based on the sensor data gathered from the Great Duck Island project. We demonstrate that our scheme achieves comparable accuracy compared to a centralised scheme with a significant reduction in communication overhead.

Dynamic Epistemic Logic and Knowledge Puzzles

Abstract: We briefly give an overview of Dynamic Epistemic Logic (DEL), mainly in semantic terms. We focus on the simplest of epistemic actions in DEL, called public announcements. We also sketch the effect of more complex epistemic actions, and briefly show how als factual change can be modelled in the same framework. We then apply the logic of public announcements in DEL to the analysis of a knowledge puzzle, called `What Sum'.

A Triadic Approach to Formal Concept Analysis

Abstract: Formal Concept Analysis, developed during the last fifteen years, has been based on the dyadic understanding of a concept constituted by its extension and its intension. The pragmatic philosophy of Charles S. Peirce with his three universal categories, and experiences in data analysis, have suggested a triadic approach to Formal Concept Analysis. This approach starts with the primitive notion of a triadic context defined as a quadruple (G, M, B, Y) where G, M, and B are sets and Y is a ternary relation between G, M, and B, i.e. Y ⊑ G×M×B; the elements of G, M, and B are called objects, attributes, and conditions, respectively, and (g, m,b) e Y is read: the object g has the attribute m under (or according to) the condition b. A triadic concept of a triadic context (G, M, B, Y) is defined as a triple (A1, A2, A3) with A1× A2sx A3 ⊑ Y which is maximal with respect to component-wise inclusion. The triadic concepts are structured by three quasiorders given by the inclusion order within each of the three components. In analogy to the dyadic case, we discuss how the ordinal structure of the triadic concepts of a triadic context can be analysed and graphically represented. A basic result is that those structures can be understood order-theoretically as “complete trilattices” up to isomorphism.