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Human-machine teaming for document coding

Extracting required information from documents is a common task in may research areas such as Human-Computer Interaction (HCI), Psychology, Sociology, Law, and Business. For example, in a study to understand the the decision making process in the England appeal court, the researchers need to analysis count documents like this. The needed information includes the name […]

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Visual analytic for sensemaking

The goal of this project is to understand how analysts make sense of data using data visualisation and/or machine learning. ‘Sensemaking’ is a bit broader than what is usually known as ‘data analysis’: as shown in the diagram (the ‘Pirolli-Card model’) it include: Searching for relevant data Extracting useful information Form of an understanding of […]

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Machine Learning Provenance for Hyperparameter tuning

Hyperparameters are important to the performance of machine learning models. However, some models have many parameters and each parameter has many possible values, if not infinite. As a result, finding the best set of values for the hyperparameters can be time consuming. Currently people rely on previous experiences or methods such as ‘grid search’, but […]