Detecting surprise in text : Expert Centric Digital Technology

I presented at the Finding Petroleum Expert Centric Digital Technology event at the Geological Society of London today. A big thanks to Karl Jeffery for organizing. The themes were about putting the domain expert and models at the centre of technology designs. There were many insightful presentations including those from David Bamford (Director PetroMall Ltd), Dimitris... Continue Reading →

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Oil and Gas Taxonomy

Using taxonomies and ontologies to extract knowledge from text. Domain Taxonomies can play a crucial role in many automated Machine Learning tasks. However, in one Study research showed that over 34% of concepts in a taxonomy can remain undetected (false negatives) if a taxonomy is only created manually. Augmenting the taxonomy design process with inductive... Continue Reading →

Enterprise search satisfaction

Happy New Year! A nice start to 2019, academic paper published 2nd Jan 2019 in Vol 45(1) Journal of Information Science. "Enterprise search and discovery capability: The factors and generative mechanisms for user satisfaction". Available in RGU OpenAir here and SAGE Journals subscription here

Dependency Parsing in Geoscience Text

In Natural Language Processing (NLP) the technique of Dependency Parsing has been used for many years. It is an area of ongoing research. Using Part of Speech (POS) tagging, it helps in part break up a sentence to determine 'what relates to what' to define syntactic root structures (heads and dependents). Along with other techniques... Continue Reading →

Search Term Recommendations

Search query term recommendations for Scholarly and Enterprise Search: Google Scholar recently introduced recommended search terms based on specificity of the query for scholars, a topic I published on in 2014. I have reviewed the 'search serendipity' literature in past posts, so won't go over that again, rather focus specifically on a few methods in... Continue Reading →

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