How L.U.E Can Improve with every use

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We’ve trained the L.U.E App to analyse and understand the way you express your legal problems to get you on the right path to resolution, our machine learning capability means L.U.E can learn how expressions change overtime for the same type of legal problem.

In the first national research of its kind in the UK, we collaborated with the University of Westminster to understand how consumers and small businesses express their legal problems. This research was funded by the European Regional Development Fund (EURDF) and Legal Utopia to see if individual legal problem expressions can be classified by machine learning algorithms to remove the need to consult a legal professional to identify a legal problem.

The School of Computer Science and Engineering at the University of Westminster led the feasibility study, this was informed by data retrieved by Westminster Law School and Legal Utopia from legal services providers across the UK in 2018 and 2019. This data concerned natural language files (non-jargonistic text) of individuals explaining or describing their legal problem, or perceived legal problem, in English. 

These data files were manually classified to identify the applicable domain and sub-domain of English law at scale, this produced a database of training data to train classifier algorithms to predict the applicable domain and sub-domain of English law autonomously. 

L.U.E is the solution vehicle that delivers a unique on-demand legal checker capability by leveraging these predictive algorithms to help consumers and small businesses identify legal problems without the pre-requisite of legal knowledge, documents or lawyers. 

However, as society changes so does the language we use to explain the same or similar aspects of it. This includes the way we express legal problems and a continuous re-calibration needs to take place to add value. 

Our predictive algorithms are capable of more than just predicting the applicable areas of law, they are capable of learning how individual expressions change over time to express the same thing differently. This method of automatic maintenance, enhancement, and value to its predictive capabilities is what subsequently drives its performance to better serve users. 

L.U.E gets better with every use because each use is a different way of explaining the same legal problem, understanding the similarities and differences of words used means our predictive capability can re-calibrate to identify legal problems at the same pace as society changes and develops. 

You can find out more on our research study here.

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