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TextOre Energy Analytics Applying Text Mining Solutions Toward Extraction of Energy Related Data from Local Records.

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Presentation on theme: "TextOre Energy Analytics Applying Text Mining Solutions Toward Extraction of Energy Related Data from Local Records."— Presentation transcript:

1 TextOre Energy Analytics Applying Text Mining Solutions Toward Extraction of Energy Related Data from Local Records

2 Introduction TextOre, Inc. offers a suite of highly advanced text-mining and data analytics software to search, identify, extract, and mine meaningful information from large amounts of unstructured text. The Energy arena offers multiple opportunities for the mining and extraction of large amounts of energy data to pinpoint relevant and critical data.

3 The Opportunity Large amounts of data (such as mineral rights information) exist in currently unretrievable formats (handwritten documents, poorly scanned or photocopied data, etc.) throughout local repositories.

4 The Market The data analytics market for the petroleum industry is currently valued at more than $1.7 billion with some research predicting this sector to be worth more than $4.7 billion by 2018. (http://www.prweb.com/releases/utility- analytics-energy/analytics- market/prweb10848527.htm)

5 The Solution TextOre, Inc. has a suite of technologies that spun out of the US intelligence arena and can easily refine multiple sources of energy data in a wide array of formats. Ability to search, identify, and extract critical data in real time from multiple sources (static data such as local records, streaming news and information from global sources, multi-language and multi-source. Ability to dominate the energy analytics market if we can gain access to the source data.

6 The Process Gain access to energy related information or documents that need to be processed for efficient information extraction. Compile the data on servers for processing by the TextOre suite of analytical products. Normalize the data (put into the same format) for preparation and early processing.

7 The Process II Normalization of documents involves converting original documents to digital text files and extracting information from hard to read court documents and land deeds. Use customized OCR (Optical Character Recognition) software to clean up all files and produce clean documents for ingestion into the TextOre Information Refinery.

8 Document Normalization Original Scan Normalized Scan

9 The Process III Ingest cleaned up documents into TextOre for processing. Identify key information elements to be extracted and enter those concepts into TextOre for extraction of relevant data from the ingested documents. Apply ingested documents into TextOre for mining text mining and extraction of key data.

10 Key Terms

11 The Process IV TextOre will produce a matrix of all possible and interesting intersections of data. Those files or records that are of interest are extracted for additional processing. Relevant documents of importance are sorted and any key data elements are automatically entered into a customized database for use by the client.

12 TextOre Matrix

13 Pinpointing Data

14

15 The Process V Data is then entered into customized databases or sold to the client as is through the TextOre interface. Ability to query additional information sources to verify legal records, location of mineral rights owners, recent sales of mineral rights, etc. or to cross reference important information.


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