In today’s world of instant gratification, consumers want – and expect – immediate answers to their questions. Quite often, that help comes in the form of a live chat session with a customer service agent. The logs from these chats provide a unique analysis opportunity. Like a call center transcript, […]
Recently, I have been thinking about how search can play more of a part in discovery and exploration with SAS Text Miner. Unsupervised text discovery usually begins with a look at the frequent or highly weighted terms in the collection, perhaps includes some edits to the synonym and stop lists, […]
Analyzing text is like a treasure hunt. It is hard to tell what you will end up with before you start digging and the things you find out can be quite unique, invaluable and in many cases full of surprises. It requires a good blend of instruments like business knowledge, […]
When I ask people what they know about Denmark they often mention Hans Christian Andersen. He was born in Denmark in 1805 and is one of the most adored children’s authors of all time. Many of his fairy tales are known worldwide as they have been translated into more than […]
The post Detect the expected and discover the unexpected - Text analytics in health care appeared first on The Text Frontier.
~ This article is co-authored by Biljana Belamaric Wilsey and Teresa Jade, both of whom are linguists in SAS' Text Analytics R&D. When I learned to program in Python, I was reminded that you have to tell the computer everything explicitly; it does not understand the human world of nuance […]
The post Text analytics through linguists’ eyes: When is a period not a full stop? appeared first on The Text Frontier.
A while ago, I started this series on natural language processing (NLP), and discussed some of the challenges of computers interpreting meaning in human language based on strings of characters. I also mentioned that today’s NLP systems can do some amazing things, including enabling the transformation of unstructured data into […]
The post Behind the scenes in natural language processing: Overcoming key challenges of rule-based systems appeared first on The Text Frontier.
A super hot topic in most organizations is how to make the most of the troves of social data available.
This Post-It Note author isn't specific about the SAS solution that is being used, so I'm going to speculate that he or she is taking advantage of SAS Text Miner, SAS Text Analytics and/or SAS Social Network Analyis. Justin Plumley wrote a fantastic blog post (Voices in the Crowd) about how he mined and categorized the social media discussions that occurred during the 2012 London Olympic Games. In a followup post, Dan Zaratsian shows how to follow social chatter through to the social networks beyond - finding influencers. He uses Social Network Analysis - also an excellent way to track fraudsters.
Finally, if you are already a using SAS Text Miner, check out these great updates in the new release - Text Miner 12.1.
Has your company been working to gather information from the social sphere? What methods are you using? Are you thinking of writing a paper for SAS Global Forum about your results!?! GO for it!!