Find and discover geoscience knowledge not documents. An example of how organisations are exploiting the output from OpportunityFinder(R), generated by applying the algorithm to their unstructured text such as PDF, PPT, Word, Excel, XML/JSON, image files etc. on file shares and document management systems   This company has used Microsoft PowerBI over the top of... Continue Reading →

A very Merry Christmas to all our clients, followers and supporters, very much appreciated! Great to see growing interest in geoscience text analytics. The graph below shows visitors to the Infoscience Technologies website since the technology start-up was founded in 2018. http://www.infosciencetechnologies.com

Discover new insights in geoscience documents, using patterns in unstructured text to detect petroleum, mineral, hydro, geothermal and hydrogen exploration opportunities. First-of-a-kind OpportunityFinderⓇ and GeoClassifierⓇ algorithms are now integrated. Teaching machines about geoscience.  Apply to deep archives, documents on your shared drive, or in Microsoft Sharepoint or Document Management Systems. Apply to external geoscience subscription reports and... Continue Reading →

Enjoyed giving the lecture on search & text analytics to over 40 MSc Business Analytics students at RGU today. Great questions and a knowledgeable and enthusiastic audience. Thanks to Dr Ebuka Ibeke for a warm welcome as usual! More on the MSc course here: https://www.rgu.ac.uk/study/courses/1177-pgcert-pgdip-msc-business-analytics

The OpportunityFinder Python based Natural Language Processing (NLP) algorithm has been extended to detect clues for porphyry copper in text. Launched in early 2020 and used by organisations for petroleum and native hydrogen exploration, the algorithm uses hundreds of thousands of lexicons, taxonomies and labelled data for machine learning models. The novel Patented method combines... Continue Reading →

GeoClassifier® can automatically classify sentences, paragraphs and documents to geoscience categories and detect well/borehole names in text. GeoClassifier® uses over 250,000 labelled public geoscience sentences to train deep learning models to achieve this. When an organisation licenses the algorithm they also receive the actual training data, so can build and train their own ML models... Continue Reading →

Due to the performant way the patented algorithm has been designed, it can check through millions of permutations in every sentence in a document extremely quickly. In a large corpus of text this equates to trillions of permutations.  Run on nothing more sophisticated than a standard i7 high street laptop, the algorithm processed 1 Million... Continue Reading →

Honoured to be reviewing for the British Computer Society Search Industry Awards next month.  https://www.bcs.org/membership/member-communities/information-retrieval-specialist-group/

Delighted to guest author an article on Natural Language Processing (NLP) in the Geosciences for Halliburton’s September Issue of Subsurface Insights. This month's issue is a minerals special. To access the article you can sign up free to Halliburton's magazine: https://geoweb.neftex.com/account/accessrequest Infoscience Technologies website is: http://www.infosciencetechnologies.com

Detecting entities such as well names in unstructured text can be useful for many aspects of information discovery. Lookup lists from corporate databases and regular expression pattern rules can be useful. They do have limitations though, it can be difficult to predict sometimes what may lie within thousands of old reports and documents. Having a... Continue Reading →