Stuart's research interests lies in the technology gap between machine learning and semantics. This includes the areas of information extraction, natural language processing, ontologies and semantic reasoning.
Information Retrieval and Semantics [Information Extraction, Natural Language Processing, Ontologies and Semantic Reasoning]
Exploring new ways to extract and use semantic information (e.g. NLP extracted relationships or OWL/SKOS/GML axioms) to intelligently search/index/link/infer information within many application domains. Semantic information extraction from both free text, structured data and numerical datasets using techniques ranging from natural language processing to data fusion. Semantic pattern matching using linguistic features, metadata and domain knowledge. Heterogeneous semantic interoperability scaling up approaches with Big Data architectures such as APACHE Storm for real-time analytics.
Machine Learning [Social Media Analytics, Trust and Veracity, Classification, Pattern Matching, Data Mining and Decision Support]
Researching innovative ways to support analysis of social media, web, dark web and other structured and unstructured information sources such as sensor networks. Cross-checking techniques for automated credibility analysis and digital text forensics, supporting human evidential processes such as verification by journalists during breaking news. Trust modelling of real-time streams of evidence, using both knowledge-based models and probabilistic models based on machine learning techniques. Interactive decision support visualizations to work with decision makers allowing verification decisions to be made in the context of the best available evidence.
Personalization [Recommender Systems and User profiling]
Personalized management and delivery of distributed media systems that can adapt to users to provide a better quality of service. Hyper-individualization and personalization of data in a social & mobile world, including approaches for geospatial visualization, intelligent automated media production, mixed-reality media systems and user modelling.
Stuart has worked on many collaborative projects across a range of sectors including media, law enforcement, sensors, environment, health, crisis management and defence.
IEEE International Conference on Intelligent Environments [IE] 2016 Posters & Short Paper Track Chair
Programme Committees / Editorial boards
ACM Transactions on Internet Technology [TOIT]
FloraGuard project : an UK ESRC funded project. FloraGuard will examine and map from a multidisciplinary perspective the criminal market in endangered plants affecting the UK. Quantitative evidence will come from a combination of surface (web forums, social media) and dark web (TOR forums) crawling of cyber-criminal activity; natural language & machine learning used to socio-economically map this activity at a community level.
Intel-Analysis DSTL : a UK DSTL funded project. Intel-Analysis DSTL uses argumentation schemes and evidential reasoning to support teams of analysts trying to evaluate conflicting hypotheses during real-time events. Evidence is obtained in real-time from a combination of human intelligence reports and information extraction from social media via natural language processing.
REVEAL project : an EU funded FP7 project. REVEAL aims to advance the necessary technologies for making a higher level analysis of social media possible. Focussed on social media verification, including digita ltext forensics, trust and credibility analytics and decision support for journalists verifying user generated content.
GRAVITATE project : an EU funded H2020 project. Focussed on supporting geometric reconstruction and semantic reunification of cultural heritage objects using techniques such as semantic enrichment using natural language processing, graph matching and 3D geometric matching.
Digital Police Officer (DPO) project : a UK WSI funded project. The DPO project aims to apply linguistic analysis to identify cyber criminals operating under pseudonyms on different online forums and within the same forum. The project will apply natural language processing techniques guided by insights from criminology.
OFERTIE project : an EU funded FP7 project. OFERTIE aims to enhance and use the OFELIA Testbed for OpenFlow Programmable Networking to run experiments to establish how programmable networks can be used to support technical solutions such as multicast and managed QoS, and what business models and value chains would be able to use these solutions in an economically sustainable fashion.
TRIDEC project : an EU funded FP7 project. Focuses on context aware semantic information retrieval and data fusion for crisis management in the Tsunami early warning and Oil rig drilling domains. Work includes geospatial sensor information fusion for decision support, task context management and context aware information filtering of real-time sensor and video event streams.
ENVIROFI project : an EU funded FP7 project. Focuses on context aware semantic information fusion and the creation of future internet environmental enablers. Work includes geospatial sensor information fusion for marine and biodiversity domains, uncertainty context management and context aware information filtering of geo-distributed heterogeneous data streams publishing sensor time series, satellite images, video and web 2.0.
DESURBS project : an EU funded FP7 project. Focussed on knowledge-based decision support tools to help planning organizations (councils, city planners, companies) better understand the vulnerabilities and design possibilities when designing safer urban spaces. Work includes semantic enrichment, personalization of best practice reports, advanced visualization and use of mapping/charting tooling.
IRMOS project : an EU funded FP7 project. Focuses on application performance modelling for use in automated Cloud resource provisioning. Work includes using semantically annotated UML diagrams to produce discrete event simulations and optimised cloud provisioning strategies.
SANY project : an EU funded FP6 project. Focuses on interoperability of in-situ sensors and sensor networks. Work includes building an OGC compliant generic sensor information fusion infrastructure and use of semantic OGC standards to handle fusion processes and application datasets.
MUPPITS and POSTMARK projects : UK TSB funded projects. Focuses on media management for post-production companies. Work includes the creation of a media data and metadata warehouse with auditable event tracking and automated media management. Later work focussed on business models and exploitation paths via media partners such as Pinewood studios.
POLYMNIA project : an EU funded FP6 project. An intelligent cross-media platform for personalised leisure and entertainment in thematic parks or venues. Work included an automated video media production tool encoding directorial knowledge for automated personalized video editing.
PrestoSpace project : an EU funded FP6 project. The project's objective is to provide technical solutions and integrated systems for a complete digital preservation of all kinds of audio-visual collections. Work included a distributed rendering system for video restoration and the overall distributed control of mixed-media restoration sub-systems.
Moretea project : an EPSRC project. Electronic notebook project to improve the information environment for chemists doing chemistry - within and beyond the lab using semantic search within a secure environment.
SCULPTEUR project : an EU funded FP5 semantic web project. A digital library system for searching and retrieval of diverse multimedia representations to support the work of professional users in the fine arts. Work included semantic search and retrieval of mixed-media archives.
GEMSS project : an EU funded FP5 medical Grid project. Six medical imaging application are supported within a secure, commercial Grid infrastructure. Work included GRID based negotiation for medical simulation quality of service.
Quickstep project : a hybrid collaborative/content-based recommender system to recommend on-line research papers. Uses kNN multi-class paper classification and an ontology to enhance the profiling process. Two trials of the system were conducted, both lasting 1.5 months with 14 and 24 subjects. The results demonstrated the utility of using an ontological approach to user profiling and how applying domain knowledge can enhance profiling.
Foxtrot project : evolution of the Quickstep recommender system. Uses pearson-r correlation to recommend and kNN classification to profile user interests. An ontological approach is taken to represent user profiles. This allows users to visualize and edit profiles encouraging direct feedback on what the system thinks they are interested in. A year long trial is in progress with hundreds of staff, postgraduates and undergraduates from the university to evaluate the utility of this approach.
See the publications link for details of the above work.
IT Innovation Centre
Electronics and Computer Science