Showing papers by "Nigel Shadbolt published in 2004"

Ontological user profiling in recommender systems

Abstract: We explore a novel ontological approach to user profiling within recommender systems, working on the problem of recommending on-line academic research papers. Our two experimental systems, Quickstep and Foxtrot, create user profiles from unobtrusively monitored behaviour and relevance feedback, representing the profiles in terms of a research paper topic ontology. A novel profile visualization approach is taken to acquire profile feedback. Research papers are classified using ontological classes and collaborative recommendation algorithms used to recommend papers seen by similar people on their current topics of interest. Two small-scale experiments, with 24 subjects over 3 months, and a large-scale experiment, with 260 subjects over an academic year, are conducted to evaluate different aspects of our approach. Ontological inference is shown to improve user profiling, external ontological knowledge used to successfully bootstrap a recommender system and profile visualization employed to improve profiling accuracy. The overall performance of our ontological recommender systems are also presented and favourably compared to other systems in the literature.

FIRE: an integrated trust and reputation model for open multi-agent systems

Abstract: Trust and reputation are central to effective interactions in open multi-agent systems in which agents, that are owned by a variety of stakeholders, can enter and leave the system at any time. This openness means existing trust and reputation models cannot readily be used. To this end, we present FIRE, a trust and reputation model that integrates a number of information sources to produce a comprehensive assessment of an agent's likely performance. Specifically, FIRE incorporates interaction trust, role-based trust, witness reputation, and certified reputation to provide a trust metric in virtually all circumstances. FIRE is empirically benchmarked and is shown to help agents effectively select appropriate interaction partners.

Developing an integrated trust and reputation model for open multi-agent systems

Abstract: Trust and reputation are central to effective interactions in open multi-agent systems in which agents, that are owned by a variety of stakeholders, can enter and leave the system at any time. This openness means existing trust and reputation models cannot readily be used. To this end, we present FIRE, a trust and reputation model that integrates a number of information sources to produce a comprehensive assessment of an agent’s likely performance. Specifically, FIRE incorporates interaction trust, role-based trust, witness reputation, and certified reputation to provide a trust metric in most circumstances. FIRE is empirically benchmarked and is shown to help agents effectively select appropriate interaction partners.

Engineering Knowledge in the Age of the Semantic Web

Abstract: Ontologies: Mappings and Translation.- The Theory of Top-Level Ontological Mappings and Its Application to Clinical Trial Protocols.- Generating and Integrating Evidence for Ontology Mappings.- Ontology Translation Approaches for Interoperability: A Case Study with Protege-2000 and WebODE.- Ontologies: Problems and Applications.- On the Foundations of UML as an Ontology Representation Language.- OWL Pizzas: Practical Experience of Teaching OWL-DL: Common Errors & Common Patterns.- Using a Novel ORM-Based Ontology Modelling Method to Build an Experimental Innovation Router.- Ontology-Based Functional-Knowledge Modeling Methodology and Its Deployment.- Ontologies: Trust and E-learning.- Accuracy of Metrics for Inferring Trust and Reputation in Semantic Web-Based Social Networks.- Semantic Webs for Learning: A Vision and Its Realization.- Ontology Maintenance.- Enhancing Ontological Knowledge Through Ontology Population and Enrichment.- Refactoring Methods for Knowledge Bases.- Applications to Medicine.- Managing Patient Record Instances Using DL-Enabled Formal Concept Analysis.- Medical Ontology and Virtual Staff for a Health Network.- Portals.- A Semantic Portal for the International Affairs Sector.- OntoWeaver-S: Supporting the Design of Knowledge Portals.- Knowledge Acquisition.- Graph-Based Acquisition of Expressive Knowledge.- Incremental Knowledge Acquisition for Improving Probabilistic Search Algorithms.- Parallel Knowledge Base Development by Subject Matter Experts.- Designing a Procedure for the Acquisition of Probability Constraints for Bayesian Networks.- Invented Predicates to Reduce Knowledge Acquisition.- Web Services and Problem Solving Methods.- Extending Semantic-Based Matchmaking via Concept Abduction and Contraction.- Configuration of Web Services as Parametric Design.- Knowledge Modelling for Deductive Web Mining.- On the Knowledge Level of an On-line Shop Assistant.- A Customer Notification Agent for Financial Overdrawn Using Semantic Web Services.- Aggregating Web Services with Active Invocation and Ensembles of String Distance Metrics.- Search, Browsing and Knowledge Acquisition.- KATS: A Knowledge Acquisition Tool Based on Electronic Document Processing.- SERSE: Searching for Digital Content in Esperonto.- A Topic-Based Browser for Large Online Resources.- Knowledge Formulation for AI Planning.- Short Papers.- ConEditor: Tool to Input and Maintain Constraints.- Adaptive Link Services for the Semantic Web.- Using Case-Based Reasoning to Support Operational Knowledge Management.- A Hybrid Algorithm for Alignment of Concept Hierarchies.- Cultural Heritage Information on the Semantic Web.- Stepper: Annotation and Interactive Stepwise Transformation for Knowledge-Rich Documents.- Knowledge Management and Interactive Learning.- Ontology-Based Semantic Annotations for Biochip Domain.- Toward a Library of Problem-Solving Methods on the Internet.- Supporting Collaboration Through Semantic-Based Workflow and Constraint Solving.- Towards a Knowledge-Aware Office Environment.- Computing Similarity Between XML Documents for XML Mining.- A CBR Driven Genetic Algorithm for Microcalcification Cluster Detection.- Ontology Enrichment Evaluation.- KAFTIE: A New KA Framework for Building Sophisticated Information Extraction Systems.- From Text to Ontology: The Modelling of Economics Events.- Discovering Conceptual Web-Knowledge in Web Documents.- Knowledge Mediation: A Procedure for the Cooperative Construction of Domain Ontologies.- A Framework to Improve Semantic Web Services Discovery and Integration in an E-Gov Knowledge Network.- Knowledge Organisation and Information Retrieval with Galois Lattices.- Acquisition of Causal and Temporal Knowledge in Medical Domains. A Web-Based Approach.

CS AKTive Space, or how we learned to stop worrying and love the semantic Web

Abstract: We discuss about the CS AKTive Space which addresses many core semantic Web challenges to offer an integrated information overview of who's doing what and where in UK computer science research.

CS AKTive space: representing computer science in the semantic web

Abstract: We present a Semantic Web application that we callCS AKTive Space. The application exploits a wide range of semantically heterogeneousand distributed content relating to Computer Science research in theUK. This content is gathered on a continuous basis using a variety of methods including harvesting and scraping as well as adopting a range models for content acquisition. The content currently comprises aroundten million RDF triples and we have developed storage, retrieval andmaintenance methods to support its management. The content is mediated through an ontology constructed for the application domainand incorporates components from other published ontologies. CS AKTive Spacesupports the exploration of patterns and implications inherent in the content and exploits a variety of visualisations and multi dimensional representations. Knowledge services supported in the applicationinclude investigating communities of practice: who is working, researching or publishing with whom. This work illustrates a number ofsubstantial challenges for the Semantic Web. These include problems of referential integrity, tractable inference and interaction support. Wereview our approaches to these issues and discuss relevant related work.

Acquiring domain knowledge for negotiating agents: a case of study

Abstract: In this paper, we employ the fuzzy repertory table technique to acquire the necessary domain knowledge for software agents to act as sellers and buyers using a bilateral, multiissue negotiation model that can achieve optimal results in semi-competitive environments. In this context, the seller's domain knowledge that needs to be acquired is the rewards associated with the products and restrictions attached to their purchase. The buyer's domain knowledge that is acquired is their requirements and preferences on the desired products. The knowledge acquisition methods we develop involve constructing three fuzzy repertory tables and their associated distinctions matrixes. The first two are employed to acquire the seller agent's domain knowledge; and the third one is used, together with an inductive machine learning algorithm, to acquire the domain knowledge for the buyer agent.

Trust strategies for the semantic web

Abstract: Enabling trust on the Semantic Web to ensure more efficient agent interaction is an important research topic. Current research on trust seems to focus on developing computational models, semantic representations, inference techniques, etc. However, little attention has been given to the plausible trust strategies or tactics that an agent can follow when interacting with other agents on the Semantic Web. In this paper we identify five most common strategies of trust and discuss their envisaged costs and benefits. The aim is to provide some guidelines to help system developers appreciate the risks and gains involved with each trust strategy.

Enhancing Services and Applications with Knowledge and Semantics

Abstract: Publisher Summary This chapter introduces the motivations, technologies, and research challenges that underlie knowledge both on and for the Grid. It focuses on the aspects involved in building a knowledge-rich Grid in which services and applications are able at all levels to benefit from a coordinated and distributed collection of knowledge services founded upon the explicit representation and the explicit use of different forms of knowledge For a computational entity to interact fully with any other entity, making informed intelligent and possibly autonomous decisions, it must be able to exploit knowledge about those entities. Rich declarative models of knowledge are relevant to making decisions in the Grid environment and must be uniformly available to the system at any point. Intelligent reasoners access these knowledge sources to make informed decisions about requirements, resources, and processing and to reformulate such decisions in light of changes in the highly dynamic Grid environment, where execution failures and new resources are commonplace. Knowledge-oriented Grids are increasingly recognized as an important stage in the evolution of Grid computing, with their promise of semantic interoperability, intelligent automation and guidance, and smart reuse. By exploiting knowledge-rich models of information it can be hoped that Grid middleware may become more flexible and more robust.

The Network Effect

Abstract: Social networks are affecting the development of computer science and might be the key to the Semantic Web's success.

Nature-inspired computing

Abstract: Increased understanding of biological systems will lead to breakthroughs in computing and artificial intelligence.

MIAKT: Combining Grid and Web Services for Collaborative Medical Decision Making

Abstract: Providing semantic web technologies in a medical domain has its obvious advantages. Having distributed services using shared domain vocabularies provides a great impetus for the integration of disparate hospital information sytems, as well as the possibility of providing more accurate diagnoses and a well organised knowledge base for sharing, tutoring and researching. Using such disparate systems requires careful consideration both technicaly, medically and ethically. This paper describes the way the ssytem we have developed offers evidence of the promise of such enhancements in the specific area of screening for breast cancer.

The Use of Ontologies in Contextually Aware Environments

Abstract: In this paper we outline work in progress related to the construction of contextually aware pervasive computing environments, through the use of semantic and knowledge technologies. Key to this activity is modelling both where and what a user is doing at any given time. We present a prototype application to illustrate this work and describe part of its implementation.

Semantic Web based Content Enrichment and Knowledge Reuse in e-Science

Abstract: We address the life cycle of semantic web based knowledge management from ontology modelling to instance generation and reuse. We illustrate through a semantic web based knowledge management approach the potential of applying semantic web technologies in GEODISE, an e-Science pilot project in the domain of Engineering Design Search and Optimization (EDSO). In particular, we show how ontologies and semantically enriched instances are acquired through knowledge acquisition and resource annotation. This is illustrated not only in Protege with an OWL plug-in, but also in a light weight function annotator customized for resource providers to semantically describe their own resources to be published. In terms of reuse, advice mechanisms, in particular a knowledge advisor based on semantic matching, are designed to consume the semantic information and facilitate service discovery, assembly and configuration in a real problem solving environment. An implementation has demonstrated the integration of the advisor in a text mode domain script editor and a GUI mode workflow composition environment. Our research work shows the potential of using semantic web technology to manage and reuse knowledge in e-Science.

Multimedia Distributed Knowledge Management in MIAKT

Abstract: Digital media facilitates tight integration of multi-modal information and networking allows this richly textured knowledge to be shared. We present the system we have developed in the MIAKT (Medical Imaging with Advanced Knowledge Technologies) project that provides knowledge management, and facilities for semantic annotations on mammographic images in the context of clinical and histopathological information. This paper also describes the novel generic architecture we have built on semantic web technologies to facilitate the annotation of images with ontological concepts, and storage thereof, in any domain. Functionality of a specific domain application is provided through web-resources, which are called through a task invocation system which abstracts the actual service implementation from the client application implementation.

CS AKTiveSpace: Building a Semantic Web Application

Abstract: In this paper we reflect on the lessons learned from deploying the award winning [1] Semantic Web application, CS AKTiveSpace. We look at issues in service orientation and modularisation, harvesting, and interaction design for supporting this 10million-triple-based application. We consider next steps for the application, based on these lessons, and propose a strategy for expanding and improving the services afforded by the application.

Using Protege for automatic ontology instantiation

Abstract: This paper gives an overview on the use of Protege in the Artequakt system, which integrated Protege with a set of natural language tools to automatically extract knowledge about artists from web documents and instantiate a given ontology. Protege was also linked to structured templates that generate documents from the knowledge fragments it maintains.

Empowering Resource Providers to Build the Semantic Grid

Abstract: The future success of Grid-enabled e-Science depends on the availability of semantic/knowledge-rich resources on the Grid, i.e., the so-called semantic Grid. This requires not only novel knowledge modelling and representation formalisms but also a shift of knowledge acquisition and population from a limited number of specialised knowledge engineers to resource providers. To this end we have developed a lightweight ontology-enabled tool, "Function Annotator", to support resource providers in capturing and publishing resource semantics and knowledge. Function Annotator takes a different line to most knowledge acquisition tools in that it is designed for use by resource providers, probably in the absence of a knowledge engineer. Its aim is to facilitate large scale knowledge population on the Grid. Function Annotator is built on the state-of-the-art of semantic web technologies, such as ontologies, OWL, instance store and DL-based reasoning, thus ensuring flexibility and scalability on the Grid. This paper describes the tool's role in a Grid-oriented resource lifecycle, its underlying technologies and implementation. It also illustrates the usage of the tool in the context of engineering design search and optimisation.

Managing Semantic Metadata for the Semantic Grid

Abstract: Research on the Semantic Web and Web/Grid resource description, discovery and composition is booming but there is currently little effort on a systematic and integrated approach to the management of resources’ Semantic Metadata (SMD), nor on key tools that add, store and reuse SMD. In this paper we propose a generic framework for managing resource SMD, in which ontologies are used for metadata modeling and the Web Ontology Language (OWL) for semantic representation. Generated resource SMD are archived in a knowledge repository enhanced with Description Logic (DL) based reasoning capability. A raft of tools, mechanisms and APIs are developed to support SMD management lifecycle, including metadata generation, semantic annotation, knowledge storage and semantic reuse. Both the framework and its supporting technologies have been applied to a large existing e-Science project, which has produced a working resource management prototype. While SMD can be exploited in many ways with regards to resource discovery, provenance and trust, we illustrate their usage through a knowledge advisor that assists resource assembly and configuration in the context of engineering design search and optimisation.

Collaborative Tools in the Semantic Grid

Abstract: The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for distributed e-Science. The project is integrating several knowledge based and hypertext tools into existing collaborative environments, and through use of a shared ontology to exchange structure, promotes enhanced process tracking and navigation of resources before, after, and while a meeting occurs. This paper provides an overview of the CoAKTinG tools, the ontology that connects them, and current research activities.

Ontology-based Decision Support for Multi- Disciplinary Management of Breast Cancer.

Abstract: A coating composition comprises a dispersion of a fluorocarbon polymer in an inert diluent having dissolved, or preferably dispersed, therein a low molecular weight (RV less than 0.25) polyethersulphone or precursor thereto.

Applying the Semantic Web to Manage Knowledge on the Grid

Abstract: Geodise [2] uses a toolbox of Grid enabled Matlab functions as building blocks on which higher-level problem solving workflows can be built The aim is to help domain engineers utilize the Grid and engineering design search packages to yield optimized designs more efficiently In order to capture the knowledge needed to describe the functions & workflows so that they may be best reused by other less experienced engineers we have developed a layered semantic infrastructure A generic knowledge development and management environment (OntoView) that is used to develop an ontology encapsulating the semantics of the functions and workflows, and that underpins the domain specific components These include: an annotation mechanism used to associate concepts with functions (Function Annotator); a semantic retrieval mechanism and GUI that allows engineers to locate suitable functions based on a list of ontology-driven searching criteria; and a GUI-based function advisor that uses the functions’ semantic information in order to help function configuration and recommend semantically compatible candidates for function assembly and workflow composition (Domain Script Editor and Workflow Construction Advisor) This paper describes this infrastructure, which we plan to extend to include the semantic reuse of workflows as well as functions

The Use of Ontologies for Knowledge Acquisition

Abstract: Ontologies are explicit conceptualisations of subject domains, and this chapter examines the use and value of ontologies for knowledge acquistion. It takes three approaches to the exploitation of ontologies, and examines them critically with respect to a number of issues, such as task-relativity, or the aim of providing tools and techniques that can be used (semi-)independently of knowledge engineers. We illustrate these ideas with four systems which exploit or could exploit ontological insights in the context of knowledge acquisition.

Advanced Knowledge Technologies at the Midterm: Tools and Methods for the Semantic Web

Abstract: Our private senses are not closed systems but are endlessly translated into each other in that experience which we call consciousness. Our extended senses, tools, technologies, through the ages, have been closed systems incapable of interplay or collective awareness. Now, in the electric age, the very instantaneous nature of co-existence among our technological instruments has created a crisis quite new in human history. Our extended faculties and senses now constitute a single field of experience which demands that they become collectively conscious. Our technologies, like our private senses, now demand an interplay and ratio that makes rational co-existence possible. As long as our technologies were as slow as the wheel or the alphabet or money, the fact that they were separate, closed systems was socially and psychically supportable. This is not true now when sight and sound and movement are simultaneous and global in extent. (McLuhan 1962, p.5, emphasis in original)

Acquiring tradeoff preferences for automated negotiations: A case study

Abstract: A wide range of algorithms have been developed for various types of automated negotiation. In developing such algorithms the main focus has been on their efficiency and their effectiveness. However, this is only part of the picture. Agents typically negotiate on behalf of their owner and for this to be effective, the agent must be able to adequately represent their owners' preferences. However, the process by which such knowledge is acquired is typically left unspecified. To remove this shortcoming, we present a case study indicating how the knowledge for a particular negotiation algorithm can be acquired. Specifically, we devise new knowledge acquisition techniques for obtaining information about a user's tradeoffs between various negotiation issues and develop knowledge acquisition tools to support this endeavour.

Chain ReAKTing: Collaborative Advanced Knowledge Technologies in the CombeChem Grid

Abstract: The CoAKTinG (Collaborative Advanced Knowledge Technologies in the Grid) project has developed a set of integrated tools to enhance collaboration between e-Scientists. As one of three case studies, these tools are being applied within the Combechem e-Science pilot project. Two levels of integration are being explored: straightforward deployment of generic CoAKTinG tools, and a “deep” integration between these tools and the Combechem grid. The deeper integration supports the publication at source research objective of Combechem, in which a digital record is maintained through the information processing chain that starts in the laboratory, supporting retrospective use in the e-Science process. In this paper we provide an overview of the tools and we focus in particular on the adaptation of one of the tools for the Combechem application.

Managing Patient Record Instances Using DL-Enabled Formal Concept Analysis

Abstract: In this paper we describe a general logic-enabled Formal Concept Analysis (FCA) approach to manage patient record instances. In particular, the conceptual model of the domain is represented as a breast cancer imaging ontology using a Description Logic (DL)-based web ontology modelling language, DAML+OIL. Patient records are treated as instances with regard to the ontology. We studied a knowledge base (KB) with 1,500 anonymous cases (2,200 abnormality instances), whose routine management functionalities, e.g. instance retrieval, instance introduction, KB visualisation and navigation, are driven by a DL-enabled FCA engine. We demonstrate that our approach is capable of conveying not only the syntactic but also the semantic information, presenting direct visual correlations between logic formulae (intent) and instants (extent) in the knowledge base and facilitating a user-friendly graphic interface easing the knowledge management processes for people with limited expertise on knowledge engineering.