ARANDA CORRAL , Gonzalo A.

Sometimes we want to search for new information about topics but we can not find relevant results using our own knowledge (for example, our personal bookmarks). A potential solution could be the use of knowledge from other users to find what we are searching for. This solution implies that we can achieve some agreement on implicit...

In this paper an analysis of security ontologies, using an mereotopological interpretation of the relationship amongst their classes, based on the entailment in the ontology, is presented. The analysis is carried out by means of a graphical tool (called Paella) that implements such an interpretation and it can suggest the potential debugging of...

A problem in the phenomenological reconstruction of Complex Systems (CS) is the extraction of the knowledge that elements playing in CS use during its evolution. This problem is important because such a knowledge would allow the researcher to understand the global behavior of the system [1,2]. In this paper an approach to partially solve this...

Formal Concept Analysis (FCA) is a theory whose goal is to discover and to extract Knowledge from qualitative data. It provides tools for reasoning with implication basis (and association rules). In this paper we analyse how to apply FCA reasoning to increase confidence in sports betting, by means of detecting temporal regularities from data....

Knowledge externalization and organization is a major challenge that companies must face. Also, they have to ask whether is possible to enhance its management. Mechanical processing of information represents a chance to carry out these tasks, as well as to turn intangible knowledge assets into real assets. Machine-readable knowledge provides a...

In order to address complex systems, apply pattern recongnition on their evolution could play an key role to understand their dynamics. Global patterns are required to detect emergent concepts and trends, some of them with qualitative nature. Formal Concept Analysis (FCA) is a theory whose goal is to discover and to extract Knowledge from...

In this paper we present a multi-agent platform designed to support p2p auctions on agricultural products. Experiments show that it could be feasible to integrate a platform, which is de-centralized by nature, into the current socioeconomic environment. The reason is that this market is managed by hard-centralized ecosystem, and...

In this paper, a solution for semantic annotation of Consumers Generated Content, based on the actions of a multiagent system, is presented. This solution is designed in the context of an spin-off which was born from Minerva project for mobile services1. Our proposal aims to build a Mobile Web 2.0 platform for the dissemination of...

In order to address the study of complex systems, the detection of patterns in their dynamics could play a key role in understanding their evolution. In particular, global patterns are required to detect emergent concepts and trends, some of them of a qualitative nature. Formal concept analysis (FCA) is a theory whose goal is to discover and...

This work introduces a (qualitative) data-driven framework to extract patterns of pedestrian behaviour and synthesize Agent-Based Models. The idea consists in obtaining a rule-based model of pedestrian behaviour by means of automated methods from data mining. In order to extract qualitative rules from data, a mathematical theory called...

Junta de Andalucía TIC-6064

Amodel for lexicon emergence in social networks is presented. The model is based on a modified version of classic Naming Games, where agents' knowledge is represented by means of formal contexts. That way it is possible to represent the effect interactions have on individual knowledge as well as the dynamics of global knowledge in the network.

Formal Concept Analysis (FCA) is a theory whose goal is to discover and extract Knowledge from qualitative data. It also provides tools for sound reasoning (implication basis and association rules). The aim of this paper is to apply FCA to a new model for bounded rationality based on the implicational reasoning over contextual knowledge bases...

The present work introduces the Knowledge Harnessing, by showing its theoretical founda-tions as well as a three-way decision model to deal with it. The problem poses how toextract valid information about a specific context from conflicting or uncertain informationreceived by a system (or agent). With this aim, forgetting variable operators are...

In the Social Web, folksonomies and other similar knowledge organization techniques may suffer limitations due to both different users' tagging behaviours and semantic heterogeneity. In order to estimate how a social tagging network organizes its resources, focusing on sharing (implicit) conceptual schemes, we apply an agent-based...

Phenomenological reconstruction of a complex system (CS) from collected and selected data allows us to work with formal models (representations) of the system. The task of building a qualitative model necessitates the formalization of relationships among observations and concrete features. Formal concept analysis can help to understand the...

A hybrid approach to phenomenological reconstruction of Complex Systems (CS), using Formal Concept Analysis (FCA) as main tool for conceptual data mining, is proposed. To illustrate the method, a classic CS is selected (cellular automata), to show how FCA can assist to predict CS evolution under different conceptual descriptions (from different...

Concept Mining is one of the main challenges both in Cognitive Computing and in Machine Learning. The ongoing improve ment of solutions to address this issue raises the need to analyze whether the consistency of the learning process is preserved. This paper addresses a particular problem, namely, how the concept mining capability changes under...

Increasingly, users connect to the Internet by mobile devices and they are generating massive content through them. The lead-off projects in Mobile Web 2.0 offer the opportunity to add semantics in order to obtain structured knowledge. In this paper, we present specific challenges for tagging reasoning, into the SinNet project. SinNet is based...

Some of the most remarkable innovative technologies from the Web 2.0 are the collaborative tagging systems. They allow the use of folksonomies as a useful structure for a number of tasks in the social web, such as navigation and knowledge organization. One of the main deficiencies comes from the tagging behaviour of different users which causes...

In this paper we estimate the soundness of tagging in digital repositories within the field of Digital Humanities by studying the (semantic) conceptual structure behind the folksnonomy. The use of association rules associated to this conceptual structure (Stem and Luxenburger basis) allows to faithfully (from a semantic point of view) complete...

Qualitative representation and reasoning on Complex Systems (CS) is important for a number of human activities on CS, mainly for the understanding of both, our perception about their structure as well as their dynamics. Formal Concept Analysis can help understanding the conceptual structure behind these qualitative representations by means...

A notion of phenomenological percolation for Conceptual Structures associated to Complex Systems (CS) is proposed. This process on concept lattices (from Formal Concept Analysis) consists in the allocation of (non-previous) objects in the lattice, which can induce its extension. The aim is to study the robustness of this conceptual structure...

Qualitative Spatial Reasoning is an exciting research field of the Knowledge Representation and Reasoning paradigm whose application often requires the extension, refinement or combination of existent theories (as well as the associated calculus). This paper addresses the issue of the sound spatial interpretation of formal extensions of such...