Gonzalo A. Aranda-Corral

Reconciling knowledge in social tagging web services

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 semantics used by the other users We call it Reconciliation of Knowledge The aim of this paper is to show an agent-based method which lets us reconcile two different knowledge basis (associated with tagging systems) into a common language, obtaining a new one that allows the reconcilitiation of (part of) this knowledge The agents use Formal Concept Analysis concepts and tools and it has been implemented on the JADE multiagent platform.

Complex concept lattices for simulating human prediction in sport

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 extract knowledge from qualitative data (organized in concept lattices). In complex environments, such as sport competitions, the large amount of information currently available turns concept lattices into complex networks. The authors analyze how to apply FCA reasoning in order to increase confidence in sports predictions by means of detecting regularities from data through the management of intuitive and natural attributes extracted from publicly available information. The complexity of concept lattices -considered as networks with complex topological structure- is analyzed. It is applied to building a knowledge based system for confidence-based reasoning, which simulates how humans tend to avoid the complexity of concept networks by means of bounded reasoning skills.

Agent-mediated shared conceptualizations in tagging services

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 semantic heterogeneity in tagging. As a consequence a user cannot benefit from the adequate tagging of others. In order to solve the problem, an agent-based reconciliation knowledge system, based on Formal Concept Analysis, is applied to facilitate the semantic interoperability between personomies. This article describes experiments that focus on conceptual structures produced by the system when it is applied to a collaborative tagging service, Delicious. Results will show the prevalence of shared tags in the sharing of common resources in the reconciliation process.

Confidence-based reasoning with local temporal formal contexts

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. It is applied to build a Knowledge based system for confidence reasoning.

Mereotopological Analysis of Formal Concepts in Security Ontologies

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 anomalies. The analysis also suggests how to interpret the representational anomalies.

Toward Semantic Mobile Web 2.0 through Multiagent Systems

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 services. Our proposal aims to build a Mobile Web 2.0 platform for the dissemination of interesting events, captured by users through mobile phones. The multiagent system creates an agent for each event, which suggests and manages several semantic features linked to an Ontology related to events.

Qualitative Reasoning on Complex Systems from Observations

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 observable features of the CS).

Bounded Rationality for Data Reasoning Based on Formal Concept Analysis

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 which are obtained from contextual selections. A contextual selection is a selection of events and attributes about them which induces partial contexts from a global formal context. In order to avoid inconsistencies, association rules are selected as reasoning engine. The model is applied to forecast sport results.

Social Ontology Documentation for Knowledge Externalization

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 basis to enhance knowledge management. A promising approach is the empowering of Knowledge Externalization by the community (users, employees). In this paper, a social semantic tool (called OntoxicWiki) for enhancing the quality of knowledge is presented.

Conservative Retractions of Propositional Logic Theories by Means of Boolean Derivatives: Theoretical Foundations

We present a specialised (polynomial-based) rule for the propositional logic called the Independence Rule , which is useful to compute the conservative retractions of propositional logic theories. In this paper we show the soundness and completeness of the logical calculus based on this rule, as well as other applications. The rule is defined by means of a new kind of operator on propositional formulae. It is based on the boolean derivatives on the polynomial ring