A distributed, semiotic-inductive and human-Oriented approach to web-scale knowledge retrieval

Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.

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.

Developing a Web-Based Course in Phases

Introduction: Distance education has grown in popularity and usage. At the same time, enrollments at postsecondary institutions continue to increase. This places significant growth pressures on institutions of higher learning. Institutions providing nursing education have historically faced limited faculty resources. This has made it difficult to meet demand for distance education; and an “all-at-once” approach to course development does little to ease this problem. In this approach, resources are expended up front before a course is offered. [See PDF for complete abstract].

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.

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.

Outcomes in Advanced Head and Neck Cancer Treated with Up-front Neck Dissection prior to (Chemo)Radiotherapy.

OBJECTIVE Our aim was to compare outcomes with and without up-front neck dissection prior to (chemo)radiotherapy in head and neck squamous cell carcinoma. STUDY DESIGN Case series with chart review. SETTING Tertiary referral center. SUBJECTS AND METHODS Outcomes of oropharyngeal, laryngeal, and hypopharyngeal squamous cell carcinoma cases with neck lymph node metastases treated from January 2001 to March 2012 were analyzed. Due to imbalances in baseline characteristics between groups treated with (n = 129) and without (n = 95) up-front neck dissection, propensity score matching was performed. RESULTS Median follow-up was 48 months (range, 12-148). With up-front neck dissection, the hazard ratio for the primary end point, disease-free survival, was 0.63 (95% confidence interval: 0.37-1.06, P = .08). Up-front neck dissection reduced acute grade ≥3 toxicity significantly when xerostomia was excluded (odds ratio: 0.40, 95% confidence interval: 0.20-0.82, P = .012). CONCLUSION Our results indicate less acute treatment toxicity without any significant difference in terms of oncologic outcome with up-front neck dissection prior to (chemo)radiotherapy as compared with (chemo)radiotherapy alone. Well-designed randomized trials are required to verify this result and further investigate the impact of this strategy on late toxicity and oncologic outcome.

Implementing and evaluating a Web -based close call reporting system at an urban hospital

Medical errors and close calls are pervasive in health care. It is hypothesized that the causes of close calls are the same as for medical errors; therefore learning about close calls can help prevent errors and increase patient safety. Yet despite efforts to encourage close call reporting, close calls as well as medical errors are under-reported in health care. The purpose of this dissertation was to implement and evaluate a web-based anonymous close call reporting system in three units at an urban hospital. ^ The study participants were physicians, nurses and medical technicians (N = 187) who care for patients in the Medical Intermediate Care Unit, the Surgical Intermediate Care Unit, and the Coronary Catheterization Laboratory in the hospital. We provided educational information to the participants on how to use the system and e-mailed and delivered paper reminders to report to the participants throughout the 19-month project. We surveyed the participants at the beginning and at the end of the study to assess their attitudes and beliefs regarding incident reporting. We found that the majority of the health care providers in our study are supportive of incident reporting in general but in practice very few had actually reported an error or a close call, semi-structured interview 20 weeks after we made the close call reporting system available. The purpose of the interviews was to further assess the participants' attitudes regarding incident reporting and the reporting system. Our findings suggest that the health care providers are supportive of medical error reporting in general, but are not convinced of the benefit of reporting close calls. Barriers to close call reporting cited include lack of time, heavy workloads, preferring to take care of close calls "on the spot", and not seeing the benefits of close call reporting. Consequently only two = close calls were reported via the system by two separate caregivers during the project. ^ The findings suggest that future efforts to increase close call reporting must address barriers to reporting, especially the belief among care givers that it is not worth taking time from their already busy schedules to report close calls. ^

Abundance and biomass of zooplankton from 1986-1994 collected in front of Constanta city, Black Sea

The Est Constanta 1986-1994 dataset contains zooplankton data collected allong a 5 station transect in front of the city Constanta (44°10'N, 28°41.5'E - EC1; 44°10'N, 28°47'E - EC2; 44°10'N, 28°54'E - EC3; 44°10'N, 29°08'E - EC4; 44°10'N, 29°22'E - EC5). Zooplankton sampling was undertaken at 5 stations where samples were collected using a Juday closing net in the 0-10, 10-25, 25-50m layer (depending also on the water masses). The dataset includes samples analysed for mesozooplankton species composition and abundance. Sampling volume was estimated by multiplying the mouth area with the wire length. Taxon-specific mesozooplankton abundance was count under microscope. Total abundance is the sum of the counted individuals. Total biomass Fodder, Rotifera , Ctenophora and Noctiluca was estimated using a tabel with wet weight for each species an stage.