JSM 2015 Preliminary Program

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Legend: Washington State Convention Center = CC, Sheraton Seattle = S, Grand Hyatt = GH and The Conference Center = TCC
* = applied session       ! = JSM meeting theme

Activity Details

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CE_17C Mon, 8/10/2015, 8:30 AM - 5:00 PM S-Willow B
Applied Text Analytics (ADDED FEE) — Professional Development Continuing Education Course
ASA
The explosion in sensors in the internet of things has led to a dramatic increase in data volume in the past few years. A disproportionate amount of this is unstructured data such as texts, voice recording, and images. While enterprise data may be analyzed in classic row by column format, much of the unstructured data remain unexplored in most organizations. This short course will provide an overview of new, easily implemented methods to find previously unknown relationships from a collection of text documents. Data mining techniques are also explored with text from sources such as tweets, voice-to-text translations, email, survey comments, incident reports, free-form data fields, websites, research reports, blogs, and other social media to discover potentially useful and actionable business insights. We will provide demonstrations using data sets with applications to financial services, aerospace/defense, medical, and other industries representative of ASA researchers. This will be a hands-on workshop in which participants are provided R code and packages to immediately implement text mining methods and discover meaningful structure from text fields. We will go through end-to-end examples, starting from assembling disparate text sources, followed by creating a structured database with the document term matrix, then reducing the dimensionality of the problem with a rank-reduced singular value decomposition, and concluding by applying data mining methods such as decision trees, regression, and cluster analysis to discover useful relationships to integrate into standard structured data. While relevant theory will be addressed, the focus of the course will be on giving participants an appreciation for the practical application of text mining to real-world applications. We will focus on R and demonstrate the use of SAS TextMiner, along with an integration of R into a common statistical analysis package to allow for rapid discovery.
Instructor(s): James Wisnowski, Adsurgo, LLC




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