A Concept of Semantics Extraction from Web Data by Induction of Fuzzy Ontologies

Traditionally, ontologies describe knowledge representation in a denotational, formalized, and deductive way. In addition, in this paper, we propose a semiotic, inductive, and approximate approach to ontology creation. We define a conceptual framework, a semantics extraction algorithm, and a first proof of concept applying the algorithm to a small set of Wikipedia documents. Intended as an extension to the prevailing top-down ontologies, we introduce an inductive fuzzy grassroots ontology, which organizes itself organically from existing natural language Web content. Using inductive and approximate reasoning to reflect the natural way in which knowledge is processed, the ontology’s bottom-up build process creates emergent semantics learned from the Web. By this means, the ontology acts as a hub for computing with words described in natural language. For Web users, the structural semantics are visualized as inductive fuzzy cognitive maps, allowing an initial form of intelligence amplification. Eventually, we present an implementation of our inductive fuzzy grassroots ontology Thus,this paper contributes an algorithm for the extraction of fuzzy grassroots ontologies from Web data by inductive fuzzy classification.

Applying Fuzzy Ontologies to Implement the Social Semantic Web

Because the knowledge in the World Wide Web is continuously expanding, Web Knowledge Aggregation, Representation and Reasoning (abbreviated as KR) is becoming increasingly important. This article demonstrates how fuzzy ontologies can be used in KR to improve the interactions between humans and computers. The gap between the Social and Semantic Web can be reduced, and a Social Semantic Web may become possible. As an illustrative example, we demonstrate how fuzzy logic and KR can enhance technologies for cognitive cities. The underlying notion of these technologies is based on connectivism, which can be improved by incorporating the results of digital humanities research.

A hypoxia complement differentiates the muscle response to endurance exercise

Metabolic stress is believed to constitute an important signal for training-induced adjustments of gene expression and oxidative capacity in skeletal muscle. We hypothesized that the effects of endurance training on expression of muscle-relevant transcripts and ultrastructure would be specifically modified by a hypoxia complement during exercise due to enhanced glycolytic strain. Endurance training of untrained male subjects in conditions of hypoxia increased subsarcolemmal mitochondrial density in the recruited vastus lateralis muscle and power output in hypoxia more than training in normoxia, i.e. 169 versus 91% and 10 versus 6%, respectively, and tended to differentially elevate sarcoplasmic volume density (42 versus 20%, P = 0.07). The hypoxia-specific ultrastructural adjustments with training corresponded to differential regulation of the muscle transcriptome by single and repeated exercise between both oxygenation conditions. Fine-tuning by exercise in hypoxia comprised gene ontologies connected to energy provision by glycolysis and fat metabolism in mitochondria, remodelling of capillaries and the extracellular matrix, and cell cycle regulation, but not fibre structure. In the untrained state, the transcriptome response during the first 24 h of recovery from a single exercise bout correlated positively with changes in arterial oxygen saturation during exercise and negatively with blood lactate. This correspondence was inverted in the trained state. The observations highlight that the expression response of myocellular energy pathways to endurance work is graded with regard to metabolic stress and the training state. The exposed mechanistic relationship implies that the altitude specificity of improvements in aerobic performance with a 'living low-training high' regime has a myocellular basis.

Ethnosciences - A step towards the integration of scientific and non-scientific forms of knowledge in the management of natural resources for the future

Integration of indigenous knowledge and ethnoscientific approaches into contemporary frameworks for conservation and sustainable management of natural resources will become increasingly important in policies on an international and national level. We set the scene on how this can be done by exploring the key conditions and dimensions of a dialogue between ‘ontologies’ and the roles, which ethnosciences could play in this process. First, the roles which ethnosciences in the context of sustainable development were analysed, placing emphasis on the implications arising when western sciences aspire to relate to indigenous forms of knowledge. Secondly, the contributions of ethnosciences to such an ‘inter-ontological dialogue’ were explored, based on an ethnoecological study of the encounter of sciences and indigenous knowledge in the Andes of Bolivia, and reviewed experiences from mangrove systems in Kenya, India and Sri Lanka, and from case-studies in other ecosystems world-wide.

Focal adhesion kinase is a load-dependent governor of the slow contractile and oxidative muscle phenotype

Striated muscle exhibits a pronounced structural-functional plasticity in response to chronic alterations in loading. We assessed the implication of focal adhesion kinase (FAK) signalling in mechano-regulated differentiation of slow-oxidative muscle. Load-dependent consequences of FAK signal modulation were identified using a multi-level approach after electrotransfer of rat soleus muscle with FAK-expression plasmid vs. empty plasmid-transfected contralateral controls. Muscle fibre-targeted over-expression of FAK in anti-gravitational muscle for 9 days up-regulated transcript levels of gene ontologies underpinning mitochondrial metabolism and contraction in the transfected belly portion. Concomitantly, mRNA expression of the major fast-type myosin heavy chain (MHC) isoform, MHC2A, was reduced. The promotion of the slow-oxidative expression programme by FAK was abolished after co-expression of the FAK inhibitor FAK-related non-kinase (FRNK). Elevated protein content of MHC1 (+9%) and proteins of mitochondrial respiration (+165-610%) with FAK overexpression demonstrated the translation of transcript differentiation in targeted muscle fibres towards a slow-oxidative muscle phenotype. Coincidentally MHC2A protein was reduced by 50% due to protection of muscle from de-differentiation with electrotransfer. Fibre cross section in FAK-transfected muscle was elevated by 6%. The FAK-modulated muscle transcriptome was load-dependent and regulated in correspondence to tyrosine 397 phosphorylation of FAK. In the context of overload, the FAK-induced gene expression became manifest at the level of contraction by a slow transformation and the re-establishment of normal muscle force from the lowered levels with transfection. These results highlight the analytic power of a systematic somatic transgene approach by mapping a role of FAK in the dominant mechano-regulation of muscular motor performance via control of gene expression.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. The author focuses on the Social Web and possibilities of its integration with the Semantic Web as resource for a semi-automated tracking of online reputations using imprecise natural language terms. The inherent structure of natural language supports humans not only in communication but also in the perception of the world. Thereby fuzziness is a promising tool for transforming those human perceptions into computer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management. For readers interested in the cross-over field of computer science, information systems, and social sciences, this book is an ideal source for becoming acquainted with the evolving field of fuzzy online reputation management in the Social Semantic Web area. ​

A Restriction-Centered Theory of Reasoning and Computation to materialize a Web 3.0

Researchers suggest that personalization on the Semantic Web adds up to a Web 3.0 eventually. In this Web, personalized agents process and thus generate the biggest share of information rather than humans. In the sense of emergent semantics, which supplements traditional formal semantics of the Semantic Web, this is well conceivable. An emergent Semantic Web underlying fuzzy grassroots ontology can be accomplished through inducing knowledge from users' common parlance in mutual Web 2.0 interactions [1]. These ontologies can also be matched against existing Semantic Web ontologies, to create comprehensive top-level ontologies. On the Web, if augmented with information in the form of restrictions andassociated reliability (Z-numbers) [2], this collection of fuzzy ontologies constitutes an important basis for an implementation of Zadeh's restriction-centered theory of reasoning and computation (RRC) [3]. By considering real world's fuzziness, RRC differs from traditional approaches because it can handle restrictions described in natural language. A restriction is an answer to a question of the value of a variable such as the duration of an appointment. In addition to mathematically well-defined answers, RRC can likewise deal with unprecisiated answers as "about one hour." Inspired by mental functions, it constitutes an important basis to leverage present-day Web efforts to a natural Web 3.0. Based on natural language information, RRC may be accomplished with Z-number calculation to achieve a personalized Web reasoning and computation. Finally, through Web agents' understanding of natural language, they can react to humans more intuitively and thus generate and process information.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

Towards an Emergent Semantic Web

In his in uential article about the evolution of the Web, Berners-Lee [1] envisions a Semantic Web in which humans and computers alike are capable of understanding and processing information. This vision is yet to materialize. The main obstacle for the Semantic Web vision is that in today's Web meaning is rooted most often not in formal semantics, but in natural language and, in the sense of semiology, emerges not before interpretation and processing. Yet, an automated form of interpretation and processing can be tackled by precisiating raw natural language. To do that, Web agents extract fuzzy grassroots ontologies through induction from existing Web content. Inductive fuzzy grassroots ontologies thus constitute organically evolved knowledge bases that resemble automated gradual thesauri, which allow precisiating natural language [2]. The Web agents' underlying dynamic, self-organizing, and best-effort induction, enable a sub-syntactical bottom up learning of semiotic associations. Thus, knowledge is induced from the users' natural use of language in mutual Web interactions, and stored in a gradual, thesauri-like lexical-world knowledge database as a top-level ontology, eventually allowing a form of computing with words [3]. Since when computing with words the objects of computation are words, phrases and propositions drawn from natural languages, it proves to be a practical notion to yield emergent semantics for the Semantic Web. In the end, an improved understanding by computers on the one hand should upgrade human- computer interaction on the Web, and, on the other hand allow an initial version of human- intelligence amplification through the Web.

Managing Things and Services with Semantics: A Survey

This paper presents a survey on the usage, opportunities and pitfalls of semantic technologies in the Internet of Things. The survey was conducted in the context of a semantic enterprise integration platform. In total we surveyed sixty-one individuals from industry and academia on their views and current usage of IoT technologies in general, and semantic technologies in particular. Our semantic enterprise integration platform aims for interoperability at a service level, as well as at a protocol level. Therefore, also questions regarding the use of application layer protocols, network layer protocols and management protocols were integrated into the survey. The survey suggests that there is still a lot of heterogeneity in IoT technologies, but first indications of the use of standardized protocols exist. Semantic technologies are being recognized as of potential use, mainly in the management of things and services. Nonetheless, the participants still see many obstacles which hinder the widespread use of semantic technologies: Firstly, a lack of training as traditional embedded programmers are not well aware of semantic technologies. Secondly, a lack of standardization in ontologies, which would enable interoperability and thirdly, a lack of good tooling support.