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.

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.

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.

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.