Archive for July 2017
Good Concept Detection Requires an “Almost Engine”
Is “almost” good enough? In terms of concept detection, the answer is most certainly “yes”. In another guest post by Tom Marsh, CTO at Boulder Equity Analytics, Tom argues that textual analysis using BEA’s AI software allows analysts to efficiently cull through mounds of documents to eliminate the noise. What is left are “scored” paragraphs…
Read MoreNested Calculation – A Tableau Puzzler
Tableau is a powerful tool for visualizing data. It is easy to throw data into, to start exploring data and to begin creating charts. But there is a lot going on “under the hood” and more advanced analytics requires a bit of a learning curve to get Tableau to do what you want it to…
Read MoreConcepts are Key, Not Words
Some form of textual analysis has become a standard feature among services that offer summaries of large volumes of documents. Natural Language Processing (NLP), deep learning and neural nets are buzz words we often hear. But when you look under the hood, most of the functionality is based on keywords, word counts and rigid taxonomies. …
Read MoreRead Faster? Researchers Need to Retool to Compete
Guest Author – Tom Marsh, CTO of Boulder Equity Analytics. At Boulder Equity Analytics (BEA), “Our mission is to build an intelligent, enriched and fully interactive database from all the publicly available reports to improve the productivity and insight of the analyst covering an industry sector.” We call it O.A.K.L.E.Y, collaborative artificial intelligence, a 2nd…
Read MoreBuzzword Overkill – AI is Not a Thing People, it’s a Discipline
Guest Author – Tom Marsh, CTO of Boulder Equity Analytics AI, artificial intelligence, has been through several boom and bust cycles. Today the pronouncements are everywhere with AI coming soon to everything from medicine to your underwear. For those of us laboring in the dark for years, it feels good to be the most popular…
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