Nicholas Gibbins

Agent-based Semantic Web Services

Abstract The Web Services world consists of loosely-coupled distributed systems which adapt to changes by the use of service descriptions that enable ad-hoc, opportunistic service discovery and reuse. At present, these service descriptions are semantically impoverished, being concerned with describing the functional signature of the services rather than characterising their meaning. In the Semantic Web community, the DAML Services effort attempts to rectify this by providing a more expressive way of describing Web Services using ontologies. However, this approach does not separate the domain-neutral communicative intent of a message (considered in terms of speech acts) from its domain-specific content, unlike similar developments from the multi-agent systems community. We describe our experiences of designing and building an ontologically motivated Web Services system for situational awareness and information triage in a simulated humanitarian aid scenario. In particular, we discuss the merits of using techniques from the multi-agent systems community for separating the intentional force of messages from their content, and the implementation of these techniques within the DAML Services model.

Linked Open Government Data: Lessons from Data.gov.uk

A project to extract value from open government data contributes to the population of the linked data Web with high-value data of good provenance.

Engineering Knowledge in the Age of the Semantic Web

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.

Agent-based semantic web services

The Web Services world consists of loosely-coupled distributed systems which adapt to ad-hoc changes by the use of service descriptions that enable opportunistic service discovery. At present, these service descriptions are semantically impoverished, being concerned with describing the functional signature of the services rather than characterising their meaning. In the Semantic Web community, the DAML Services effort attempts to rectify this by providing a more expressive way of describing Web services using ontologies. However, this approach does not separate the domain-neutral communicative intent of a message (considered in terms of speech acts) from its domain-specific content, unlike similar developments from the multi-agent systems community.In this paper, we describe our experiences of designing and building an ontologically motivated Web Services system for situational awareness and information triage in a simulated humanitarian aid scenario. In particular, we discuss the merits of using techniques from the multi-agent systems community for separating the intentional force of messages from their content, and the implementation of these techniques within the DAML Services model.

Contextualising tags in collaborative tagging systems

Collaborative tagging systems are now popular tools for organising and sharing information on the Web. While collaborative tagging offers many advantages over the use of controlled vocabularies, they also suffer from problems such as the existence of polysemous tags. We investigate how the different contexts in which individual tags are used can be revealed automatically without consulting any external resources. We consider several different network representations of tags and documents, and apply a graph clustering algorithm on these networks to obtain groups of tags or documents corresponding to the different meanings of an ambiguous tag. Our experiments show that networks which explicitly take the social context into account are more likely to give a better picture of the semantics of a tag.

Decentralized approaches for self-adaptation in agent organizations

Self-organizing multi-agent systems provide a suitable paradigm for developing autonomic computing systems that manage themselves. Towards this goal, we demonstrate a robust, decentralized approach for structural adaptation in explicitly modeled problem solving agent organizations. Based on self-organization principles, our method enables the autonomous agents to modify their structural relations to achieve a better allocation of tasks in a simulated task-solving environment. Specifically, the agents reason about when and how to adapt using only their history of interactions as guidance. We empirically show that, in a wide range of closed, open, static, and dynamic scenarios, the performance of organizations using our method is close (70–90%) to that of an idealized centralized allocation method and is considerably better (10–60%) than the current state-of-the-art decentralized approaches.

Telling experts from spammers: expertise ranking in folksonomies

With a suitable algorithm for ranking the expertise of a user in a collaborative tagging system, we will be able to identify experts and discover useful and relevant resources through them. We propose that the level of expertise of a user with respect to a particular topic is mainly determined by two factors. Firstly, an expert should possess a high quality collection of resources, while the quality of a Web resource depends on the expertise of the users who have assigned tags to it. Secondly, an expert should be one who tends to identify interesting or useful resources before other users do. We propose a graph-based algorithm, SPEAR (SPamming-resistant Expertise Analysis and Ranking), which implements these ideas for ranking users in a folksonomy. We evaluate our method with experiments on data sets collected from Delicious.com comprising over 71,000 Web documents, 0.5 million users and 2 million shared bookmarks. We also show that the algorithm is more resistant to spammers than other methods such as the original HITS algorithm and simple statistical measures.

CS AKTive space: representing computer science in the semantic web

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.

Managing Reference: Ensuring Referential Integrity of Ontologies for the Semantic Web

The diversity and distributed nature of the resources available in the semantic web poses significant challenges when these are used to help automatically build an ontology. One persistent and pervasive problem is that of the resolution or elimination of coreference that arises when more than one identifier is used to refer to the same resource. Tackling this problem is crucial for the referential integrity, and subsequently the quality of results, of any ontology-based knowledge service. We have built a coreference management service to be used alongside the population and maintenance of an ontology. An ontology based knowledge service that identifies communities of practice (CoPs) is also used to maintain the heuristics used in the coreference management system. This approach is currently being applied in a large scale experiment harvesting resources from various UK computer science departments with the aim of building a large, generic web-accessible ontology.

Tag Meaning Disambiguation through Analysis of Tripartite Structure of Folksonomies

Collaborative tagging systems are becoming very popular recently. Web users use freely-chosen tags to describe shared resources, resulting in a folksonomy One problem of folksonomies is that tags which appear in the same form may carry multiple meanings and represent different concepts. As this kind of tags are ambiguous, the precisions in both description and retrieval of the shared resources are reduced. We attempt to develop effective methods to disambiguate tags by studying the tripartite structure of folksonomies. This paper describes the network analysis techniques that we employ to discover clusters of nodes in networks and the algorithm for tag disambiguation. Experiments show that the method is very effective in performing the task.