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.

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.

Keeping citizens, companies, and organizations informed by Web KnowARR

For the main part, electronic government (or e-government for short) aims to put digital public services at disposal for citizens, companies, and organizations. To that end, in particular, e-government comprises the application of Information and Communications Technology (ICT) to support government operations and provide better governmental services (Fraga, 2002) as possible with traditional means. Accordingly, e-government services go further as traditional governmental services and aim to fundamentally alter the processes in which public services are generated and delivered, after this manner transforming the entire spectrum of relationships of public bodies with its citizens, businesses and other government agencies (Leitner, 2003). To implement this transformation, one of the most important points is to inform the citizen, business, and/or other government agencies faithfully and in an accessible way. This allows all the partaking participants of governmental affairs for a transition from passive information access to active participation (Palvia and Sharma, 2007). In addition, by a corresponding handling of the participants' data, a personalization towards these participants may even be accomplished. For instance, by creating significant user profiles as a kind of participants' tailored knowledge structures, a better-quality governmental service may be provided (i.e., expressed by individualized governmental services). To create such knowledge structures, thus known information (e.g., a social security number) can be enriched by vague information that may be accurate to a certain degree only. Hence, fuzzy knowledge structures can be generated, which help improve governmental-participants relationship. The Web KnowARR framework (Portmann and Thiessen, 2013; Portmann and Pedrycz, 2014; Portmann and Kaltenrieder, 2014), which I introduce in my presentation, allows just all these participants to be automatically informed about changes of Web content regarding a- respective governmental action. The name Web KnowARR thereby stands for a self-acting entity (i.e. instantiated form the conceptual framework) that knows or apprehends the Web. In this talk, the frameworks respective three main components from artificial intelligence research (i.e. knowledge aggregation, representation, and reasoning), as well as its specific use in electronic government will be briefly introduced and discussed.

Evaluation of a web-based application versus conventional instruction in the undergraduate curriculum of fixed prosthodontics

The present study aims to investigate the implications of web-based delivery of identical learning content for time efficiency and students' performance, as compared to conventional textbook resources.

The InterHerz project--a web-based psychological treatment for cardiac patients with depression: study protocol of a randomized controlled trial

Patients with heart disease often suffer from difficulties in psychological adaptation during cardiac rehabilitation. Mood disorders such as depression are known to be highly prevalent in cardiac patients and to have a negative impact on the progression of coronary heart disease. However, cardiac patients have difficulties to get psychological treatments due to low availability and motivational difficulties. Web-based interventions have been proven to be effective in treating depressive symptoms. Deprexis is a promising web-based psychological treatment which was devised for depressed patients. The aim of the study InterHerz is to examine if Deprexis is an effective psychological treatment to reduce stress and depression in cardiac patients.

Family satisfaction in the intensive care unit: cross-cultural adaptation of a questionnaire

PURPOSE: Family needs and expectations are often unmet in the intensive care unit (ICU), leading to dissatisfaction. This study assesses cross-cultural adaptability of an instrument evaluating family satisfaction in the ICU. MATERIALS AND METHODS: A Canadian instrument on family satisfaction was adapted for German language and central European culture and then validated for feasibility, validity, internal consistency, reliability, and sensitivity. RESULTS: Content validity of a preliminary translated version was assessed by staff, patients, and next of kin. After adaptation, content and comprehensibility were considered good. The adapted translation was then distributed to 160 family members. The return rate was 71.8%, and 94.4% of questions in returned forms were clearly answered. In comparison with a Visual Analogue Scale, construct validity was good for overall satisfaction with care (Spearman rho = 0.60) and overall satisfaction with decision making (rho = 0.65). Cronbach alpha was .95 for satisfaction with care and .87 for decision-making. Only minor differences on repeated measurements were found for interrater and intrarater reliability. There was no floor or ceiling effect. CONCLUSIONS: A cross-cultural adaptation of a questionnaire on family satisfaction in the ICU can be feasible, valid, internally consistent, reliable, and sensitive.

The Great Silk Alternative Multiple Co-Evolution of Web Loss and Sticky Hairs in Spiders

Spiders are the most important terrestrial predators among arthropods. Their ecological success is reflected by a high biodiversity and the conquest of nearly every terrestrial habitat. Spiders are closely associated with silk, a material, often seen to be responsible for their great ecological success and gaining high attention in life sciences. However, it is often overlooked that more than half of all Recent spider species have abandoned web building or never developed such an adaptation. These species must have found other, more economic solutions for prey capture and retention, compensating the higher energy costs of increased locomotion activity. Here we show that hairy adhesive pads (scopulae) are closely associated with the convergent evolution of a vagrant life style, resulting in highly diversified lineages of at least, equal importance as the derived web building taxa. Previous studies often highlighted the idea that scopulae have the primary function of assisting locomotion, neglecting the fact that only the distal most pads (claw tufts) are suitable for those purposes. The former observations, that scopulae are used in prey capture, are largely overlooked. Our results suggest the scopulae evolved as a substitute for silk in controlling prey and that the claw tufts are, in most cases, a secondary development. Evolutionary trends towards specialized claw tufts and their composition from a low number of enlarged setae to a dense array of slender ones, as well as the secondary loss of those pads are discussed further. Hypotheses about the origin of the adhesive setae and their diversification throughout evolution are provided.

The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases

This chapter presents fuzzy cognitive maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. The corresponding Web KnowARR framework incorporates findings from fuzzy logic. To this end, a first emphasis is particularly on the Web KnowARR framework along with a stakeholder management use case to illustrate the framework’s usefulness as a second focal point. This management form is to help projects to acceptance and assertiveness where claims for company decisions are actively involved in the management process. Stakeholder maps visually (re-) present these claims. On one hand, they resort to non-public content and on the other they resort to content that is available to the public (mostly on the Web). The Semantic Web offers opportunities not only to present public content descriptively but also to show relationships. The proposed framework can serve as the basis for the public content of stakeholder maps.

Promoting Local Innovations: A tool for adaptation to climate change and sustainable development in Mountains

Throughout their history mountain communities have had to adapt to changing environmental and socio-economic conditions. They have developed strategies and specialized knowledge to sustain their livelihoods in a context of adverse climatic events and constant change. As negotiations and discussions on climate change emphasize the critical need for locally relevant and community owned adaptation strategies, there is a need for new tools to capitalize on this local knowledge and endogenous potential for innovation. The toolkit Promoting Local Innovation (PLI) was designed by the Centre for Development and Environment (CDE) of the University of Bern, Switzerland, to facilitate a participatory social learning process which identifies locally available innovations that can be implemented for community development. It is based on interactive pedagogy and joint learning among different stakeholders in the local context. The tried-and-tested tool was developed in the Andean region in 2004, and then used in International Union for Conservation of Nature (IUCN) climate change adaptation projects in Thailand, Burkina Faso, Senegal, and Chile. These experiences showed that PLI can be used to involve all relevant stakeholders in establishing strategies and actions needed for rural communities to adapt to climate change impacts, while building on local innovation potential and promoting local ownership

Comparison of hepatic adaptation in extreme metabolic phenotypes observed in early lactation dairy cows on-farm

The aim was to study the variation in metabolic responses in early-lactating dairy cows (n = 232) on-farm that were pre-selected for a high milk fat content (>45 g/l) and a high fat/protein ratio in milk (>1.5) in their previous lactation. Blood was assayed for concentrations of metabolites and hormones. Liver was measured for mRNA abundance of 25 candidate genes encoding enzymes and receptors involved in gluconeogenesis (6), fatty acid β-oxidation (6), fatty acid and triglyceride synthesis (5), cholesterol synthesis (4), ketogenesis (2) and the urea cycle (2). Two groups of cows were formed based on the plasma concentrations of glucose, non-esterified fatty acids (NEFA) and β-hydroxybutyric acid (BHBA) (GRP+, high metabolic load; glucose <3.0 mm, NEFA >300 μm and BHBA >1.0 mm, n = 30; GRP-, low metabolic load; glucose >3.0 mm, NEFA <300 μm and BHBA <1.0 mm, n = 30). No differences were found between GRP+ and GRP- for the milk yield at 3 weeks post-partum, but milk fat content was higher (p < 0.01) for GRP+ than for GRP-. In week 8 post-partum, milk yield was higher in GRP+ in relation to GRP- (37.5 vs. 32.5 kg/d; p < 0.01). GRP+ in relation to GRP- had higher (p < 0.001) NEFA and BHBA and lower glucose, insulin, IGF-I, T3 , T4 concentrations (p < 0.01). The mRNA abundance of genes related to gluconeogenesis, fatty acid β-oxidation, fatty acid and triglyceride synthesis, cholesterol synthesis and the urea cycle was different in GRP+ compared to GRP- (p < 0.05), although gene transcripts related to ketogenesis were similar between GRP+ and GRP-. In conclusion, high metabolic load post-partum in dairy cows on-farm corresponds to differences in the liver in relation to dairy cows with low metabolic load, even though all cows were pre-selected for a high milk fat content and fat/protein ratio in milk in their previous lactation.