Big Data Meets Text Mining

• Activity Number: 640
• Type: Topic Contributed
• Date/Time: Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistical Computing
• Author(s): Zheng Zhao*+ and James Cox and Russell Albright
• Companies: SAS Institute and SAS Institute and SAS Institute
• Keywords: Text Mining ; Big Data

Abstract

Learning from your customers and your competitors has become a real possibility because of the massive amount of web and social media data available. However, this abundance of data requires significantly more time and computer memory to perform analytical tasks. This paper introduces high-performance text mining technology for SAS® High-Performance Analytics. Text parsing, text filtering, and dimension reduction are performed using the new HPTMINE and HPTMSCORE procedures in SAS® High-Performance Analytics Server and are accessed conveniently from within SAS® High-Performance Enterprise MinerT. The paper demonstrates and discusses the advantages of this new SAS® functionality and provides real-world examples of the types of performance improvements you can expect.