Cross ontology query answering on the semantic web:an initial evaluation

PowerAqua is a Question Answering system, which takes as input a natural language query and is able to return answers drawn from relevant semantic resources found anywhere on the Semantic Web. In this paper we provide two novel contributions: First, we detail a new component of the system, the Triple Similarity Service, which is able to match queries effectively to triples found in different ontologies on the Semantic Web. Second, we provide a first evaluation of the system, which in addition to providing data about PowerAqua's competence, also gives us important insights into the issues related to using the Semantic Web as the target answer set in Question Answering. In particular, we show that, despite the problems related to the noisy and incomplete conceptualizations, which can be found on the Semantic Web, good results can already be obtained.

PowerAqua:fishing the semantic web

The Semantic Web (SW) offers an opportunity to develop novel, sophisticated forms of question answering (QA). Specifically, the availability of distributed semantic markup on a large scale opens the way to QA systems which can make use of such semantic information to provide precise, formally derived answers to questions. At the same time the distributed, heterogeneous, large-scale nature of the semantic information introduces significant challenges. In this paper we describe the design of a QA system, PowerAqua, designed to exploit semantic markup on the web to provide answers to questions posed in natural language. PowerAqua does not assume that the user has any prior information about the semantic resources. The system takes as input a natural language query, translates it into a set of logical queries, which are then answered by consulting and aggregating information derived from multiple heterogeneous semantic sources.

An integrated environment for semantic knowledge work

In this demonstration, we will present a semantic environment called the K-Box. The K-Box supports the lightweight integration of knowledge tools, with a focus on semantic tools, but with the flexibility to integrate natural language and conventional tools. We discuss the implementation of the framework, and two existing applications, including details of a new application for developers of semantic workflows. The demonstration will be of interest to developers and researchers of ontology-based knowledge management systems, and semantic desktops, and to analysts working with cross-media information. © 2011 ACM.

Ontology augmentation:combining semantic web and text resources

This work investigates the process of selecting, extracting and reorganizing content from Semantic Web information sources, to produce an ontology meeting the specifications of a particular domain and/or task. The process is combined with traditional text-based ontology learning methods to achieve tolerance to knowledge incompleteness. The paper describes the approach and presents experiments in which an ontology was built for a diet evaluation task. Although the example presented concerns the specific case of building a nutritional ontology, the methods employed are domain independent and transferrable to other use cases. © 2011 ACM.

A comparative evaluation of term recognition algorithms

Automatic Term Recognition (ATR) is a fundamental processing step preceding more complex tasks such as semantic search and ontology learning. From a large number of methodologies available in the literature only a few are able to handle both single and multi-word terms. In this paper we present a comparison of five such algorithms and propose a combined approach using a voting mechanism. We evaluated the six approaches using two different corpora and show how the voting algorithm performs best on one corpus (a collection of texts from Wikipedia) and less well using the Genia corpus (a standard life science corpus). This indicates that choice and design of corpus has a major impact on the evaluation of term recognition algorithms. Our experiments also showed that single-word terms can be equally important and occupy a fairly large proportion in certain domains. As a result, algorithms that ignore single-word terms may cause problems to tasks built on top of ATR. Effective ATR systems also need to take into account both the unstructured text and the structured aspects and this means information extraction techniques need to be integrated into the term recognition process.

An integrated multiple criteria decision making approach for resource allocation in higher education

Resource allocation is one of the major decision problems arising in higher education. Resources must be allocated optimally in such a way that the performance of universities can be improved. This paper applies an integrated multiple criteria decision making approach to the resource allocation problem. In the approach, the Analytic Hierarchy Process (AHP) is first used to determine the priority or relative importance of proposed projects with respect to the goals of the universities. Then, the Goal Programming (GP) model incorporating the constraints of AHP priority, system, and resource is formulated for selecting the best set of projects without exceeding the limited available resources. The projects include 'hardware' (tangible university's infrastructures), and 'software' (intangible effects that can be beneficial to the university, its members, and its students). In this paper, two commercial packages are used: Expert Choice for determining the AHP priority ranking of the projects, and LINDO for solving the GP model. Copyright © 2007 Inderscience Enterprises Ltd.

Integrated team working: a literature review

Introduction: This literature review was conducted to provide a background understanding of the literature around integrated health and social care prior to a research project evaluating two integrated health and social care teams in England, UK. Methods: A systematic literature search of relevant databases was employed to identify all articles relating to integrated health and social care teams produced in the last 10 years in the UK. Results: Sixteen articles were found and reviewed; all were reviewed by the first reviewer and half by the second reviewer. Discussion: Key themes identified were: drivers, barriers and benefits of integrated working; staff development; and meeting the needs of service users. Conclusion: Recommendations for integrated working include; a focus on the management of integrated teams; a need to invest in resources for the successful integration of teams; a need for the development of clear standards for monitoring the success and failure of integrated teams; and the need for further empirical evidence of the processes used by integrated teams. These findings will be valuable for practitioners who are establishing services or want to improve integrated care in their own practice.

Achieving cost competitiveness with an agent based integrated process planning and production scheduling system

From a manufacturing perspective, the efficiency of manufacturing operations (such as process planning and production scheduling) are the key element for enhancing manufacturing competence. Process planning and production scheduling functions have been traditionally treated as two separate activities, and have resulted in a range of inefficiencies. These include infeasible process plans, non-available/overloaded resources, high production costs, long production lead times, and so on. Above all, it is unlikely that the dynamic changes can be efficiently dealt with. Despite much research has been conducted to integrate process planning and production scheduling to generate optimised solutions to improve manufacturing efficiency, there is still a gap to achieve the competence required for the current global competitive market. In this research, the concept of multi-agent system (MAS) is adopted as a means to address the aforementioned gap. A MAS consists of a collection of intelligent autonomous agents able to solve complex problems. These agents possess their individual objectives and interact with each other to fulfil the global goal. This paper describes a novel use of an autonomous agent system to facilitate the integration of process planning and production scheduling functions to cope with unpredictable demands, in terms of uncertainties in product mix and demand pattern. The novelty lies with the currency-based iterative agent bidding mechanism to allow process planning and production scheduling options to be evaluated simultaneously, so as to search for an optimised, cost-effective solution. This agent based system aims to achieve manufacturing competence by means of enhancing the flexibility and agility of manufacturing enterprises.

Semantic and organization considerations in database conceptual modelling : the Semantic Conceptual Organizational Model (SECOM)

This thesis presents a new approach to designing large organizational databases. The approach emphasizes the need for a holistic approach to the design process. The development of the proposed approach was based on a comprehensive examination of the issues of relevance to the design and utilization of databases. Such issues include conceptual modelling, organization theory, and semantic theory. The conceptual modelling approach presented in this thesis is developed over three design stages, or model perspectives. In the semantic perspective, concept definitions were developed based on established semantic principles. Such definitions rely on meaning - provided by intension and extension - to determine intrinsic conceptual definitions. A tool, called meaning-based classification (MBC), is devised to classify concepts based on meaning. Concept classes are then integrated using concept definitions and a set of semantic relations which rely on concept content and form. In the application perspective, relationships are semantically defined according to the application environment. Relationship definitions include explicit relationship properties and constraints. The organization perspective introduces a new set of relations specifically developed to maintain conformity of conceptual abstractions with the nature of information abstractions implied by user requirements throughout the organization. Such relations are based on the stratification of work hierarchies, defined elsewhere in the thesis. Finally, an example of an application of the proposed approach is presented to illustrate the applicability and practicality of the modelling approach.

Computer integrated manufacturing (CIM) and the principle of business control

In response to the increasing international competitiveness, many manufacturing businesses are rethinking their management strategies and philosophies towards achieving a computer integrated environment. The explosive growth in Advanced Manufacturing Technology (AMI) has resulted in the formation of functional "Islands of Automation" such as Computer Aided Design (CAD), Computer Aided Manufacturing (CAM), Computer Aided Process Planning (CAPP) and Manufacturing Resources Planning (MRPII). This has resulted in an environment which has focussed areas of excellence and poor overall efficiency, co-ordination and control. The main role of Computer Integrated Manufacturing (CIM) is to integrate these islands of automation and develop a totally integrated and controlled environment. However, the various perceptions of CIM, although developing, remain focussed on a very narrow integration scope and have consequently resulted in mere linked islands of automation with little improvement in overall co-ordination and control. This thesis, that is the research described within, develops and examines a more holistic view of CIM, which is based on the integration of various business elements. One particular business element, namely control, has been shown to have a multi-facetted and underpinning relationship with the CIM philosophy. This relationship impacts various CIM system design aspects including the CIM business analysis and modelling technique, the specification of systems integration requirements, the CIM system architectural form and the degree of business redesign. The research findings show that fundamental changes to CIM system design are required; these are incorporated in a generic CIM design methodology. The affect and influence of this holistic view of CIM on a manufacturing business has been evaluated through various industrial case study applications. Based on the evidence obtained, it has been concluded that this holistic, control based approach to CIM can provide a greatly improved means of achieving a totally integrated and controlled business environment. This generic CIM methodology will therefore make a significant contribution to the planning, modelling, design and development of future CIM systems.

Managing uncertainty in integrated environmental modelling:the UncertWeb framework

Web-based distributed modelling architectures are gaining increasing recognition as potentially useful tools to build holistic environmental models, combining individual components in complex workflows. However, existing web-based modelling frameworks currently offer no support for managing uncertainty. On the other hand, the rich array of modelling frameworks and simulation tools which support uncertainty propagation in complex and chained models typically lack the benefits of web based solutions such as ready publication, discoverability and easy access. In this article we describe the developments within the UncertWeb project which are designed to provide uncertainty support in the context of the proposed ‘Model Web’. We give an overview of uncertainty in modelling, review uncertainty management in existing modelling frameworks and consider the semantic and interoperability issues raised by integrated modelling. We describe the scope and architecture required to support uncertainty management as developed in UncertWeb. This includes tools which support elicitation, aggregation/disaggregation, visualisation and uncertainty/sensitivity analysis. We conclude by highlighting areas that require further research and development in UncertWeb, such as model calibration and inference within complex environmental models.

Concepts and methods of quantitative assessment of risk to groundwater resources

This work presents a two-dimensional approach of risk assessment method based on the quantification of the probability of the occurrence of contaminant source terms, as well as the assessment of the resultant impacts. The risk is calculated using Monte Carlo simulation methods whereby synthetic contaminant source terms were generated to the same distribution as historically occurring pollution events or a priori potential probability distribution. The spatial and temporal distributions of the generated contaminant concentrations at pre-defined monitoring points within the aquifer were then simulated from repeated realisations using integrated mathematical models. The number of times when user defined ranges of concentration magnitudes were exceeded is quantified as risk. The utilities of the method were demonstrated using hypothetical scenarios, and the risk of pollution from a number of sources all occurring by chance together was evaluated. The results are presented in the form of charts and spatial maps. The generated risk maps show the risk of pollution at each observation borehole, as well as the trends within the study area. This capability to generate synthetic pollution events from numerous potential sources of pollution based on historical frequency of their occurrence proved to be a great asset to the method, and a large benefit over the contemporary methods.

Communities and emerging semantics in semantic link network:discovery and learning

The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the Semantic Link Network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested.

Semantic linking through spaces for cyber-physical-socio intelligence:a methodology

Humans consciously and subconsciously establish various links, emerge semantic images and reason in mind, learn linking effect and rules, select linked individuals to interact, and form closed loops through links while co-experiencing in multiple spaces in lifetime. Machines are limited in these abilities although various graph-based models have been used to link resources in the cyber space. The following are fundamental limitations of machine intelligence: (1) machines know few links and rules in the physical space, physiological space, psychological space, socio space and mental space, so it is not realistic to expect machines to discover laws and solve problems in these spaces; and, (2) machines can only process pre-designed algorithms and data structures in the cyber space. They are limited in ability to go beyond the cyber space, to learn linking rules, to know the effect of linking, and to explain computing results according to physical, physiological, psychological and socio laws. Linking various spaces will create a complex space — the Cyber-Physical-Physiological-Psychological-Socio-Mental Environment CP3SME. Diverse spaces will emerge, evolve, compete and cooperate with each other to extend machine intelligence and human intelligence. From multi-disciplinary perspective, this paper reviews previous ideas on various links, introduces the concept of cyber-physical society, proposes the ideal of the CP3SME including its definition, characteristics, and multi-disciplinary revolution, and explores the methodology of linking through spaces for cyber-physical-socio intelligence. The methodology includes new models, principles, mechanisms, scientific issues, and philosophical explanation. The CP3SME aims at an ideal environment for humans to live and work. Exploration will go beyond previous ideals on intelligence and computing.

Describing and communicating uncertainty within the semantic web

The Semantic Web relies on carefully structured, well defined, data to allow machines to communicate and understand one another. In many domains (e.g. geospatial) the data being described contains some uncertainty, often due to incomplete knowledge; meaningful processing of this data requires these uncertainties to be carefully analysed and integrated into the process chain. Currently, within the SemanticWeb there is no standard mechanism for interoperable description and exchange of uncertain information, which renders the automated processing of such information implausible, particularly where error must be considered and captured as it propagates through a processing sequence. In particular we adopt a Bayesian perspective and focus on the case where the inputs / outputs are naturally treated as random variables. This paper discusses a solution to the problem in the form of the Uncertainty Markup Language (UncertML). UncertML is a conceptual model, realised as an XML schema, that allows uncertainty to be quantified in a variety of ways i.e. realisations, statistics and probability distributions. UncertML is based upon a soft-typed XML schema design that provides a generic framework from which any statistic or distribution may be created. Making extensive use of Geography Markup Language (GML) dictionaries, UncertML provides a collection of definitions for common uncertainty types. Containing both written descriptions and mathematical functions, encoded as MathML, the definitions within these dictionaries provide a robust mechanism for defining any statistic or distribution and can be easily extended. Universal Resource Identifiers (URIs) are used to introduce semantics to the soft-typed elements by linking to these dictionary definitions. The INTAMAP (INTeroperability and Automated MAPping) project provides a use case for UncertML. This paper demonstrates how observation errors can be quantified using UncertML and wrapped within an Observations & Measurements (O&M) Observation. The interpolation service uses the information within these observations to influence the prediction outcome. The output uncertainties may be encoded in a variety of UncertML types, e.g. a series of marginal Gaussian distributions, a set of statistics, such as the first three marginal moments, or a set of realisations from a Monte Carlo treatment. Quantifying and propagating uncertainty in this way allows such interpolation results to be consumed by other services. This could form part of a risk management chain or a decision support system, and ultimately paves the way for complex data processing chains in the Semantic Web.