Figure 1 - Increased search query traffic likely due to Coronavirus effects It is well known through sites such as Google Trends that search queries such as 'coronovirus' see a surge in usage (frequency). What is less clear as Google do not release their daily search query volumes, is the effect on overall search behaviour... Continue Reading →
With more people working from home due to Covid-19, enterprise search engines may play a more prominent role to meet information needs. Having capable search engines has always supported the digital workplace complementing discussion groups, collaboration and peer to peer communication tools. Research I conducted in 2014 with 55 geoscientists in the workplace, provides evidence that... Continue Reading →
Infoscience Technologies https://infosciencetechnologies.com Headlining in OilIT
Looking forward to presenting at the Finding Petroleum conference on the 23rd March 2020 at the Geological Society of London. http://www.findingpetroleum.com/event/Investing-in-North-Sea-projects-and-technology/f1404.aspx Abstract Most of the published literature on text mining in exploration geoscience focuses on extraction of data or concepts typically in the sentence or document 'container'. There are no known approaches that look for... Continue Reading →
The Search Insights Report 2020 is out. This has been produced by The Search Network as a service to the search community. There is no charge and no sponsorship. I was honoured to be asked to contribute an article which opens the report. Download the 54 page PDF with the link below: Search Insights 2020_The... Continue Reading →
The pace of Natural Language Processing (NLP) developments continues to accelerate. Very interesting article and research from Google released this month using their massive Colossal Clean Crawled Corpus (C4). Worth a read! Exploring Transfer Learning with T5: the Text-To-Text Transfer Transformer. https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html
First advert for the OpportunityFinder algorithm on the back cover of the new issue of Digital Energy Journal.
Predicting hydrocarbon plays from text using machine learning and natural language processing. I recently tested the OpportunityFinder Algorithm on a selection of public domain geoscience literature. Only literature published between 1990 to 2010 was used, some time before a major gas discovery was made in the area. The hypothesis was whether the algorithm could surface... Continue Reading →