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Research

At the Legal Innovation Centre, researchers, legal practitioners and technologists work together to advance the frontier of legal technology, bringing new levels of process efficiency.

A core vision of the Legal Innovation Centre is on the research and development of computational law which is a branch of legal informatics focused on the automation and mechanization of legal analysis. We are also looking into automating information retrieval as it can reduce cost and often outperform manual searches in terms of accuracy.

Many of our projects focus on building systems, which allow stakeholders in the legal domain to connect and collaborate more efficiently. We achieve this through building on advances in the field of computer science with a wider goal of providing economic and social benefits by streamlining the interactions of law professionals in delivering legal services.

A current project is that automated fact checking of legal documents using computational intelligence techniques where the aim is to extract and verify each fact in specific legal texts. We have identified that knowledge acquisition rules, based on the linguistic treatment of specific aspects of legal documents will be key to improving the results in this task. Additionally, domain knowledge representation can provide an even broader set of possibilities. This research will create language models for addressing Information Extraction from texts in the legal domain combined with external publically accessible document silos in order to verify statements. Automatic fact checking of legal documents allows for improvements in legal information retrieval system effectiveness.

This project builds on Ulster University's prior research into automated subtitling and language identification where we developed hidden markov models, lexicons and phoneme bi/tri-gram sequences for any natural language modelled (e.g. English). A core outcome was language models generated from lexicons, grammars and phoneme databases with training on spoken dialogue data.