Foundations of Fuzzy Logic and Semantic Web Languages

This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic

Foundations of Fuzzy Logic and Semantic Web Languages

This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic

A semantic web model for ad hoc context-aware communities : Application to the Smart Place Scenario

International audienceIn this paper, we propose a model for an open framework that allows mobile users to create and to participate to context-aware virtual communities. The model we propose and implement is a generic data model fully compliant with the semantic web data model RDF. This model is suited to let mobile end-users use, create and customize virtual communities. We combine fundamentals for a decentralized semantic web social network with context-aware virtual communities and services. Smart cities scenarios are typically targeted with this approach. It can be implemented in places like metro stations, museums, squares, cinemas, etc. to provide ad hoc context-aware information services to mobile users

LexMa: Tabular data to knowledge graph matching using lexical techniques

With the fundamentals of lives dependent upon the extensive use of the internet-based searches for common life items, there is an ever-growing demand of the quick and meaningful search query systems. This has given the rise of the concept called Semantic Web. There are many challenges in developing the Semantic Web however one fundamental challenge is to design systems to enable the semantic access to the information in tabular data (e.g., Web tables). In this paper, we discuss one such system which has been developed for the automatic annotation of the tabular data using a knowledge graph. We call this system LexMa. Our system is based on lexical matching techniques. LexMa has participated in the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2020)

I'm sorry to say, but your understanding of image processing fundamentals is absolutely wrong

The ongoing discussion whether modern vision systems have to be viewed as visually-enabled cognitive systems or cognitively-enabled vision systems is groundless, because perceptual and cognitive faculties of vision are separate components of human (and consequently, artificial) information processing system modeling.Comment: To be published as chapter 5 in "Frontiers in Brain, Vision and AI", I-TECH Publisher, Viena, 200

Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa