Ian is a Senior Data Scientist who joined the ONS in May 2018. He is an old school programmer who… had his first game published whilst still at school in 1984. Since then he studied computer science at Cardiff University, gaining a PhD in Computer Aided Design. Ian has over 15 years industrial experience, ranging from embedded development for early general-purpose graphics cards, 3D engines for games consoles, haptics for gynaecological training and five years developing robot-assisted stereotactic neurosurgery planning software.
Between his various roles in industry, Ian worked for 10 years as a senior research fellow at Cardiff University, lecturing ubiquitous computing and researching distributed rendering, haptic input devices and 3D display technologies. Alongside this he also collaborated with other cross-disciplinary projects such as mentoring users of a several thousand core compute cluster.
Ian enjoys the challenge of applying computer science to real-world problems across disciplines whilst using common, off-the shelf hardware; or more colloquially, squeezing a quart into (or out of) a pint pot. He is currently interested in convolutional neural networks and natural language processing.
Large volumes of unstructured, free-text data such as patent applications, contain potentially valuable information for policymakers. Here we describe the pipeline used to process such data sources.
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In this report, we focus primarily on how the pyGrams tool can be used to analyse terms through time using the time stamps in document metadata.
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We introduce pyGrams – a new Python tool for extracting, visualising and identifying emerging terms in large document collections, such as patents.
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Improving the current approach to identifying the proportion of vegetation for urban residential gardens in Great Britain.
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