Making Sense of Unstructured Content in the Oil & Gas Industry – New Video Interview Featuring Expert System by Oil and Gas Expert Mark LaCour
July 7 – ModalPoint
Consider the following sentence: I bought 10,000 shares of stock in Apple computer. You understand exactly what Apple and stock mean in this sentence. I have 10,000 apples in stock. There is a change in context here and now both stock and apple take on new meaning. The oil & gas industry has its own unique language, and a large problem the industry faces is finding that information and making sense of it, or rather, making it readable. Most companies use keyboard technology or a statistics-based technology to break down data. Expert System uses semantic analysis of content to look at both structured and unstructured words in context. Recently Bryan Bell, Expert System Executive Vice President, sat down with Modalpoint’s Mark LaCour, one of the foremost oil & gas industry experts, to discuss how Expert System’s technology adds dynamic metadata to unstructured content and its importance within the oil & gas industry.
In the interview, Mark discusses with Bryan specifically how the industry is using this technology and why it has become so valuable. For example, one big deployment within the oil & gas industry is analyzing network shared drives. Oil & gas organizations have shared network drives around the world with a lot of valuable content, but they fail to leverage the content’s full potential. Semantic technology such as that form Expert System, addresses this problem by reading the data like a person would and understanding where it fits. By using a combination of linguistics and semantics, the unstructured and structured data can be comingled. It makes a huge impact on an organization’s bottom line – making content findable and reusable while understanding the contextual relevance of the terminology.
Looking a real life example, take the recent Health, Safety & Environment (HSE) project. A company was trying to determine what types of accidents were occurring at well sites. The company was finding a lot of information about burns; however, there were different types of burns (hot, cold, etc.). A company would prevent each type of accident differently. The technology enables the company to look at the information more accurately and analyze and decipher the content correctly.
To listen to Bryan’s entire interview, visit http://modalpoint.com/cognitive-computing-interview-with-expert-systems/