Lexalytics Offers Tunable Text Mining
May 13, 2015
Want to do text mining without some of the technical hassles? if so, you will want to read about Lexalytics “the industry’s most tunable and configurable text mining technology.” Navigate to “Lexalytics Unveils Industry’s First Wizard for Text Mining and Sentiment Analysis.” I learned that text mining can be fun, easy, and intuitive.” I highlighted this quote from the news story as an indication that one does not need to understand exactly what’s going on in the text mining process:
“Before, our customers had to understand the meaning of things like ‘alpha-numeric content threshold’ and ‘entities confidence threshold,'” Jeff continued. “Lexalytics provides the most knobs to turn to get the results exactly as you want them, and now our customers don’t even have to think about them.”
Text mining, the old-fashioned way, required understanding of what was required, what procedures were appropriate, and ability to edit or write scripts. There are other skills that used to be required as the entry fee to text mining. The modern world of interfaces allows anyone to text mine. Do users understand the outputs? Sure. Perfectly.
As I read the story, I recalled a statement in “A Review of Three Natural Language Processors, AlchemyAPI, OpenCalais, and Semantria.” Here is the quote I noted in that July 2014 write up by Marc Clifton:
I find the concept of Natural Language Processing intriguing and that it holds many possibilities for helping to filter and analyze the vast and growing amount of information out there on the web. However, I’m not quite sure exactly how one uses the output of an NLP service in a productive way that goes beyond simple keyword matching. Some people will of course be interested in whether the sentiment is positive or negative, and I think the idea of extracting concepts (AlchemyAPI) and topics (Semantria) are useful in extracting higher level abstractions regarding a document. NLP is therefore an interesting field of study and I believe that the people who provide NLP services would benefit from the feedback of users to increase the value of their service.
Perhaps the feedback was, “Make this stuff easy to do.” Now the challenge is to impart understanding to what a text mining system outputs. That might be a bit more difficult.
Stephen E Arnold, May 13, 2015
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