Transcription of Text Mining in JMP with R
{{id}} {{{paragraph}}}
Example: bankruptcy
Text Mining in JMP with R
Text Mining in JMP with R Andrew T. Karl, Senior Management Consultant, Adsurgo LLC Heath Rushing, Principal Consultant and Co-Founder, Adsurgo LLC 1. Introduction A popular rule of thumb suggests that 80% of data in most organizations is unstructured, such as text. Text Mining is the process of finding interesting and relevant information from this unstructured data and determining if there are any meaningful relationships by transforming it into a structured format and applying classical multivariate statistical techniques. Many companies use this methodology on a daily basis for pattern discovery ( warranty analysis , electronic medical records analysis ) and predictive modeling ( insurance fraud) using text from various sources such as email, survey comments, incident reports, free form data fields, websites, research reports, blogs, and social media.
3. JMP Script and Application To illustrate our script, we will analyze a collection of NTSB accident reports that are available from Miner, G., et al. (2012) Practical Text Mining and Statistical Analysis for Non-structured Text Data Application.
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
Related search queries
Text Mining: A Thematic Exploration of Don Quixote, Text Mining, And analysis, Analysis, Mining, Text, Text Mining and Analysis, Text Mining for Health Care and Medicine, Text analysis, Analysis of Voice of Customer: Text Mining, Text mining and topic models, Text mining for central banks, Text Mining Process, Techniques and Tools