From Unstructured Text to a Graph Visualization in 60 minutes..

From a collection of documents to a Graph Visualization in 60 minutes using OpenSource. As a quick exploratory view of a collection of documents too vast to read, these techniques may be useful. Using tools like Python, create n-grams (bi-grams, tri-grams to make it quicker) from your text, terms are nodes, spaces are edges, frequency... Continue Reading →

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Geohealth: Using Text Analytics to Test Hypotheses

Geohealth: Text Analytics can be useful to test hypotheses and exploratory data analysis. I've taken the cosine similarity between word vectors of all US States and 'Cadmium' in 100 years of economic geology literature. Above the average shown in orange, below average in blue. This is combined with health data from national databases per US... Continue Reading →

Chemical Element Entity Extraction from Economic Geology Journals: Combining word frequency in text with measured numerical data

Finding trends and patterns in unstructured text can be possible without combining with other data sources. However, combining derived structured data from text analytics with measured real world data can also lead to differentiating insights. Figure 1 shows the frequency of occurrence of chemical elements in the text of 100 years of the Society of... Continue Reading →

Unsupervised Machine Learning: Clustering Geoscience Text Using Co-occurrence windows and Principal Component Analysis (PCA).

Unsupervised machine learning techniques exploit latent patterns in text (in layman's terms - normally some form of complex word co-occurrence) rather than rules driven by human labelled data. As this is essentially an inductive technique, it can be useful to stimulate ideas and questions that the information professional or geoscientist a priori, may not have... Continue Reading →

Using Search Term Word Co-Occurrence for Browsing Search Results: What is most popular is not necessarily the most interesting.

I conducted some exploratory search research with geoscientists and engineers in numerous oil & gas companies back in 2014-2015, which I have recently revisited. Unlike lookup/known item search where a user is seeking something specific, an existing need, something they know exists where there is a 'right answer', exploratory search tasks are more loosely defined.... Continue Reading →

Applying Natural Language Processing (NLP) to Scholarly Geoscience Literature.

Presenting research on Artificial Intelligence (AI) in academic publishing 26-27 Sep, Washington DC, along with Google, Web of Science, SAGE, Taylor & Francis etc at the Silverchair technology platform conference. https://www.silverchair.com/community/platform-strategies/ In my talk I'll be covering unsupervised machine learning, supervised machine learning, rule based methods (and hybrids) with actual examples of how each technique... Continue Reading →

Machine Learning in the Subsurface

Excited to be presenting at the Machine Learning in the Subsurface seminar on 20th September in Stavanger, Norway. Organised by the Norwegian Petroleum Directorate (NPD), ConocoPhillips, Repsol, Equinor and AkerBP. More here

Extracting Knowledge from Text using AI

Thoroughly enjoyed two days workshops with the¬†Oil and Gas Technology Centre (OGTC) this week in Aberdeen. The OGTC's goal is to maximise economic recovery from the UK Continental Shelf, supported by Government. As well as participating in workshops, I also shared some results of my research on predictive geoscience sentiment analysis and its role to... Continue Reading →

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