A framework for automated construction of resource space based on background knowledge

Resource Space Model is a kind of data model which can effectively and flexibly manage the digital resources in cyber-physical system from multidimensional and hierarchical perspectives. This paper focuses on constructing resource space automatically. We propose a framework that organizes a set of digital resources according to different semantic dimensions combining human background knowledge in WordNet and Wikipedia. The construction process includes four steps: extracting candidate keywords, building semantic graphs, detecting semantic communities and generating resource space. An unsupervised statistical language topic model (i.e., Latent Dirichlet Allocation) is applied to extract candidate keywords of the facets. To better interpret meanings of the facets found by LDA, we map the keywords to Wikipedia concepts, calculate word relatedness using WordNet's noun synsets and construct corresponding semantic graphs. Moreover, semantic communities are identified by GN algorithm. After extracting candidate axes based on Wikipedia concept hierarchy, the final axes of resource space are sorted and picked out through three different ranking strategies. The experimental results demonstrate that the proposed framework can organize resources automatically and effectively.©2013 Published by Elsevier Ltd. All rights reserved.

Background and foreground knowledge in dynamic ontology construction

Ontologies have become a key component in the Semantic Web and Knowledge management. One accepted goal is to construct ontologies from a domain specific set of texts. An ontology reflects the background knowledge used in writing and reading a text. However, a text is an act of knowledge maintenance, in that it re-enforces the background assumptions, alters links and associations in the ontology, and adds new concepts. This means that background knowledge is rarely expressed in a machine interpretable manner. When it is, it is usually in the conceptual boundaries of the domain, e.g. in textbooks or when ideas are borrowed into other domains. We argue that a partial solution to this lies in searching external resources such as specialized glossaries and the internet. We show that a random selection of concept pairs from the Gene Ontology do not occur in a relevant corpus of texts from the journal Nature. In contrast, a significant proportion can be found on the internet. Thus, we conclude that sources external to the domain corpus are necessary for the automatic construction of ontologies.

World knowledge in the process of translation

The paper illustrates the role of world knowledge in comprehending and translating texts. A short news item, which displays world knowledge fairly implicitly in condensed lexical forms, was translated by students from English into German. It is shown that their translation strategies changed from a first draft which was rather close to the surface structure of the source text to a final version which took situational aspects, texttypological conventions and the different background knowledge of the respective addressees into account. Decisions on how much world knowledge has to be made explicit in the target text, however, must be based on the relevance principle. Consequences for teaching and for the notions of semantic knowledge and world knowledge are discussed.

Doing business in India

On its independence in 1947, India was among the two most industrialized nations in Asia. Since then it adopted a “mixed economy” approach that hindered its national growth and the optimum utilization of its immense resources (both natural and human). To re-establish itself as an economic force in the region, India liberalized its economy in early 1990s. The adoption of the “free market economy” model has created great opportunities for foreign businesses. This article provides useful information on the complex business environment, aimed to help foreign businessmen and investors to develop a good understanding on key background knowledge for being successful in India. It reviews Indian historical development, political structure and climate, international relations, and economy and foreign trade. India's infrastructure, legal framework, socio-cultural set-up, competitive environment, as well as market structure and potential are also analyzed. © 2001 John Wiley & Sons, Inc.

Doing business in... Indonesia

Indonesia's long stability of over three decades came to a sudden end after the regional economic crisis of 1997–1998. The economic crisis not only shattered the Indonesian economy but also resulted in political turmoil. The national leadership has changed three times over the last five years. In such conditions, the confidence of foreign investors is very low. The present government has initiated a number of steps to restore political stability and economic recovery. This article provides useful information on the complex business environment, aimed to help foreign investors to develop a good understanding on key background knowledge for being successful in Indonesia. It reviews Indonesian historical development, political structure and climate, regional relations, and economy and foreign trade. Indonesia's infrastructure, legal framework, sociocultural setup, as well as market structure and potential, are also analyzed.

Doing business in... Sri Lanka

Having a well-developed human resource base and a relatively well-developed capital market infrastructure, Sri Lanka offers a liberal and dynamic investment environment. Over the years, macrostability has been achieved and considerable reforms have been implemented, contributing to a healthy economic growth. This article provides useful information on the business environment and is intended to help foreign businessmen and investors to develop a good grasp of essential background knowledge for being successful in Sri Lanka. It reviews the Sri Lankan political structure, climate, and economy. Sri Lanka's infrastructure, legal framework, and socioculturel set-up, as well as market structure and potential, are also analyzed. © 2005 Wiley Periodicals, Inc.

Ontology-based protein-protein interactions extraction from literature using the hidden vector state model

This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural language understanding. It is built upon the existing work on relation extraction using the Hidden Vector State (HVS) model. The HVS model belongs to the category of statistical learning methods. It can be trained directly from un-annotated data in a constrained way whilst at the same time being able to capture the underlying named entity relationships. However, it is difficult to incorporate background knowledge or non-local information into the HVS model. This paper proposes to represent the HVS model as a conditionally trained undirected graphical model in which non-local features derived from PPI ontology through inference would be easily incorporated. The seamless fusion of ontology inference with statistical learning produces a new paradigm to information extraction.

Overcoming schema heterogeneity between linked semantic repositories to improve coreference resolution

Schema heterogeneity issues often represent an obstacle for discovering coreference links between individuals in semantic data repositories. In this paper we present an approach, which performs ontology schema matching in order to improve instance coreference resolution performance. A novel feature of the approach is its use of existing instance-level coreference links defined in third-party repositories as background knowledge for schema matching techniques. In our tests of this approach we obtained encouraging results, in particular, a substantial increase in recall in comparison with existing sets of coreference links.

TRial of an Educational intervention on patients' knowledge of Atrial fibrillation and anticoagulant therapy, INR control, and outcome of Treatment with warfarin (TREAT)

Background Atrial fibrillation (AF) patients with a high risk of stroke are recommended anticoagulation with warfarin. However, the benefit of warfarin is dependent upon time spent within the target therapeutic range (TTR) of their international normalised ratio (INR) (2.0 to 3.0). AF patients possess limited knowledge of their disease and warfarin treatment and this can impact on INR control. Education can improve patients' understanding of warfarin therapy and factors which affect INR control. Methods/Design Randomised controlled trial of an intensive educational intervention will consist of group sessions (between 2-8 patients) containing standardised information about the risks and benefits associated with OAC therapy, lifestyle interactions and the importance of monitoring and control of their International Normalised Ratio (INR). Information will be presented within an 'expert-patient' focussed DVD, revised educational booklet and patient worksheets. 200 warfarin-naïve patients who are eligible for warfarin will be randomised to either the intervention or usual care groups. All patients must have ECG-documented AF and be eligible for warfarin (according to the NICE AF guidelines). Exclusion criteria include: aged < 18 years old, contraindication(s) to warfarin, history of warfarin USE, valvular heart disease, cognitive impairment, are unable to speak/read English and disease likely to cause death within 12 months. Primary endpoint is time spent in TTR. Secondary endpoints include measures of quality of life (AF-QoL-18), anxiety and depression (HADS), knowledge of AF and anticoagulation, beliefs about medication (BMQ) and illness representations (IPQ-R). Clinical outcomes, including bleeding, stroke and interruption to anticoagulation will be recorded. All outcome measures will be assessed at baseline and 1, 2, 6 and 12 months post-intervention. Discussion More data is needed on the clinical benefit of educational intervention with AF patients receiving warfarin. Trial registration ISRCTN93952605

A knowledge-based system for process planning in a seamless steel tube plant

The thesis describes the work carried out to develop a prototype knowledge-based system 'KBS-SETUPP' to generate process plans for the manufacture of seamless tubes. The work is specifically related to a plant in which hollows are made from solid billets using a rotary piercing process and then reduced to required size and finished properties using the fixed plug cold drawing process. The thesis first discusses various methods of tube production in order to give a general background of tube manufacture. Then a review of the automation of the process planning function is presented in terms of its basic sub-tasks and the techniques and suitability of a knowledge-based system is established. In the light of such a review and a case study, the process planning problem is formulated in the domain of seamless tube manufacture, its basic sub-tasks are identified and capabilities and constraints of the available equipment in the specific plant are established. The task of collecting and collating the process planning knowledge in seamless tube manufacture is discussed and is mostly fulfilled from domain experts, analysing of existing manufacturing records specific to plant, textbooks and applicable Standards. For the cold drawing mill, tube-drawing schedules have been rationalised to correspond with practice. The validation of such schedules has been achieved by computing the process parameters and then comparing these with the drawbench capacity to avoid over-loading. The existing models cannot be simulated in the computer program as such, therefore a mathematical model has been proposed which estimates the process parameters which are in close agreement with experimental values established by other researchers. To implement the concepts, a Knowledge-Based System 'KBS- SETUPP' has been developed on Personal Computer using Turbo- Prolog. The system is capable of generating process plans, production schedules and some additional capabilities to supplement process planning. The system generated process plans have been compared with the actual plans of the company and it has been shown that the results are satisfactory and encouraging and that the system has the capabilities which are useful.

Cues and knowledge structures used by mental-health professionals when making risk assessments

Background: Research into mental-health risks has tended to focus on epidemiological approaches and to consider pieces of evidence in isolation. Less is known about the particular factors and their patterns of occurrence that influence clinicians’ risk judgements in practice. Aims: To identify the cues used by clinicians to make risk judgements and to explore how these combine within clinicians’ psychological representations of suicide, self-harm, self-neglect, and harm to others. Method: Content analysis was applied to semi-structured interviews conducted with 46 practitioners from various mental-health disciplines, using mind maps to represent the hierarchical relationships of data and concepts. Results: Strong consensus between experts meant their knowledge could be integrated into a single hierarchical structure for each risk. This revealed contrasting emphases between data and concepts underpinning risks, including: reflection and forethought for suicide; motivation for self-harm; situation and context for harm to others; and current presentation for self-neglect. Conclusions: Analysis of experts’ risk-assessment knowledge identified influential cues and their relationships to risks. It can inform development of valid risk-screening decision support systems that combine actuarial evidence with clinical expertise.

Using XML and XSLT for flexible elicitation of mental-health risk knowledge

Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge. © 2007 Informa UK Ltd All rights reserved.

Knowledge acquisition and research evidence in autism:researcher and practitioner perspectives and engagement

Background: Government policy and national practice guidelines have created an increasing need for autism services to adopt an evidence-based practice approach. However, a gap continues to exist between research evidence and its application. This study investigated the difference between autism researchers and practitioners in their methods of acquiring knowledge. Methods: In a questionnaire study, 261 practitioners and 422 researchers reported on the methods they use and perceive to be beneficial for increasing research access and knowledge. They also reported on their level of engagement with members of the other professional community. Results: Researchers and practitioners reported different methods used to access information. Each group, however, had similar overall priorities regarding access to research information. While researchers endorsed the use of academic journals significantly more often than practitioners, both groups included academic journals in their top three choices. The groups differed in the levels of engagement they reported; researchers indicated they were more engaged with practitioners than vice versa. Conclusions: Comparison of researcher and practitioner preferences led to several recommendations to improve knowledge sharing and translation, including enhancing access to original research publications, facilitating informal networking opportunities and the development of proposals for the inclusion of practitioners throughout the research process.