A5024107224- Service-Oriented Architecture and Web Services
- Semantic Web and Ontologies
- Multi-Agent Systems and Negotiation
- Business Process Modeling and Analysis
- Distributed and Parallel Computing Systems
- Logic, Reasoning, and Knowledge
- Mobile Agent-Based Network Management
- Auction Theory and Applications
- Scientific Computing and Data Management
- Distributed systems and fault tolerance
- Biomedical Text Mining and Ontologies
- Advanced Database Systems and Queries
- Topic Modeling
- AI-based Problem Solving and Planning
- Human Mobility and Location-Based Analysis
- Context-Aware Activity Recognition Systems
- Data Quality and Management
- Natural Language Processing Techniques
- Peer-to-Peer Network Technologies
- Image Retrieval and Classification Techniques
- Data Mining Algorithms and Applications
- Data Stream Mining Techniques
- Recommender Systems and Techniques
- Digital Innovation in Industries
- Game Theory and Voting Systems
University of Liverpool
2015-2024
Groote Schuur Hospital
2024
Institute of Electrical and Electronics Engineers
2018
University of Southampton
1999-2009
University of Aberdeen
1997-2008
Carnegie Mellon University
1999-2005
SRI International
2005
University of Roehampton
2004
University of Pittsburgh
2002
Intelligent machines have reached capabilities that go beyond a level human being can fully comprehend without sufficiently detailed understanding of the underlying mechanisms. The choice moves in game Go (generated by Deep Mind?s Alpha Zero [1]) are an impressive example artificial intelligence system calculating results even expert for hardly retrace [2]. But this is, quite literally, toy example. In reality, intelligent algorithms encroaching more and into our everyday lives, be it...
Competency Questions (CQs) are a form of ontology functional requirements expressed as natural language questions. Inspecting CQs together with the axioms in an provides critical insights into intended scope and applicability ontology. also underpin number tasks development ontologies e.g. reuse, testing, requirement specification, definition patterns that implement such requirements. Although integral to majority engineering methodologies, practice publishing alongside ontological artefacts...
Given the plethora of available solutions, choosing an appropriate Deep Reinforcement Learning (DRL) model for dynamic pricing poses a significant challenge practitioners. While many DRL solutions claim superior performance, there lacks standardized framework their evaluation. Addressing this gap, we introduce novel and set metrics to select assess models systematically. To validate utility our framework, critically compared three representative models, emphasizing performance in tasks....
In order to support semantic interoperation in open environments, where agents can dynamically join or leave and no prior assumption be made on the ontologies align, different involved need agree semantics of terms used during interoperation.Reaching this agreement only come through some sort negotiation process.Indeed, will differ domain they commit to; their perception world, hence choice vocabulary represent concepts.We propose an approach for supporting creation exchange arguments, that...
In recent years interface agents have been developed to assist users with various tasks. Some systems employ machine learning techniques allow the agent adapt user's changing requirements. With increase in volume of data on Internet emerged that are able monitor and learn from their identify topics interest. One such described here has filter mail messages. We examine issues involved constructing an autonomous employs a component explore use two different this context.
The transition from laboratory science to in silico e-science has facilitated a paradigmatic shift the way we conduct modern science. We can use computationally based analytical models simulate and investigate scientific questions such as those posed by high-energy physics bioinformatics, yielding high-quality results discoveries at an unprecedented rate. However, while experimental media have changed, methodologies processes choose for conducting experiments are still relevant. As lab...
Background: Medical robots are increasingly used for a variety of applications in healthcare. Robots have mainly been to support surgical procedures, and assistive uses dementia elderly care. To date, there has limited debate about the potential opportunities risks robotics other areas palliative, supportive end-of-life Aim: The objective this article is examine possible future impact medical on care Specifically, we will discuss strengths, weaknesses, threats (SWOT) technology. Methods: A...
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The UK e-Science programme is relying on the evolution of paper lab book into a pervasive data gathering system. To date take up existing commercial or research replacement systems has not been great. In this paper, we reconsider both role in experimental cycle, as well its affective and experiential properties an artefact, order to design that will be acceptable scientists who use it. end combined extended analysis models assess artefact functionally experientially. We present approach...
Presents the guest editorial for this issue of publication.
Multiagent systems evolved from a need for knowledge-aware, distributed, problem-solving mechanisms. These are formally grounded using theoretical approaches, including those that assume mentalistic notions. As result, much of this research into multiagent has provided formal proofs or proof-of-concept demonstrators (such as example prototypes). It only limited, pragmatic support (systems, software, and tools) the user community. Research Web services, in contrast, focused on community,...
Web services promise to revolutionize the way computational resources and business processes are offered invoked in open, distributed systems, such as Internet. These described using machine-readable metadata, which enables consumer applications automatically discover provision suitable for their workflows at run-time. However, current approaches have typically assumed service descriptions accurate deterministic, so neglected account fact that these open systems inherently unreliable...
Recommendation systems are crucial in navigating the vast digital market. However, user data’s dynamic and non-stationary nature often hinders their efficacy. Traditional models struggle to adapt evolving preferences behaviours inherent interaction data, posing a significant challenge for accurate prediction personalisation. Addressing this, we propose novel theoretical framework, transformer, designed effectively capture leverage temporal dynamics within data. This approach enhances...