Image: A small public document set 'spatialized' using Infoscience's GeoClassifier algorithm, each dot is a document. GeoClassifier uses novel techniques to disambiguate - automatically assigning latitude and longitude points for any document. Ready to integrate in a company's GIS system. #naturallanguageprocessing #machinelearning More: http://www.infosciencetechnologies.com
GeoClassifier ® : State-of-the-art Document Spatialisation
GeoClassifier v4 uses Natural Language Processing (NLP) and Machine Learning to classify and position documents on a map. The unstructured text spatialisation includes many unique features around disambiguation and detection of the most specific latitude and longitude. Significantly improves on many existing and rather basic geotagging options in use today. #geotagging #spatialisingdocuments #georeferencing More at:... Continue Reading →
Call for abstracts: EAGE Workshop on Data Science
I am on the technical committee for the upcoming EAGE workshop on data science in Kuala Lumpur later this year. The call for abstracts has opened, details below: This workshop will discuss the foundations of Data Science and successfully integrating these techniques into critical exploration pipelines and focus on two levels: •As a workshop to... Continue Reading →
Contradictions in text
Contradictions in text: Been conducting some research on natural language processing, blending textual entailment using probabilistic language models with graph based associative text extraction. Take the two sentences: 1. Good oil shows and good poroperm values were observed in core x in the Raptor Sandstone. 2. The Raptor Sandstone was water wet. The predictive model... Continue Reading →
Friend Of A Friend (FOAF) Concepts, Rocks and Inference.
Friend Of A Friend (FOAF) concepts in Graph data structures can be useful for detective work. For example: Mr Green "knows" Mr Blue who "knows" Mr Red. Mr Green and Mr Red "stayed at" the same address in 2010. But Mr Green and Mr Red (deny that they) "know" each other. Automatically extracting people's names,... Continue Reading →
Extracting knowledge from unstructured text
NEW OpportunityFinder V4.4: Create Turtle output automatically from unstructured text. Creating a graph of subsurface & wells concepts automatically from unstructured data using Natural Language Processing (NLP). The technique of creating a graph network of entities and concepts automatically from text into a Knowledge Graph is not new. However, OpportunityFinder(R) uses a unique patented approach to... Continue Reading →
Infoscience Technologies and Aramco Collaboration
We are pleased to be collaborating with Aramco and keen to see it put Infoscience’s OpportunityFinder® Natural Language Processing (NLP) algorithm to work. This aims to help geoscientists and engineers derive meaningful insights from unstructured data to speed up workflows and reduce risks. More: http://www.infosciencetechnologies.com About Infoscience Technologies Ltd Infoscience is the market leader for Artificial... Continue Reading →
Infoscience Technologies Runner Up in UK Innovation and Entrepreneurship Award
Delighted to announce that Infoscience Technologies was Highly Commended (Runner Up) in the UK Innovation and Entrepreneurship Award at the British Computer Society 2022 IT Industry Awards last night. Congratulations to the winner CyberSmart! More at http://www.infosciencetechnologies.com
Question and Answer Digital Assistant
It’s become quite easy to deploy simple question & answer extraction tools to search unstructured text. I posed the question “What share of the UK market do electric cars have in 2022?”. This could be phrased in many ways such as “In the UK what is the electric car market share?” etc, which returns the... Continue Reading →