Three crucial issues in text analytics
As so often happens in life, I have gotten the job of fixing something that I was complaining about. Specifically, I’ve been asked to run the Marketing panel at the Text Analytics Summit in Newton, MA, June 12-13. In connection with this, organizer Ravi Virpal has asked me to come up with three major points or themes I feel we should address. For the purpose of this panel, I’m defining “text analytics” to be anything that performs or relies on what the computational linguists call “fact/knowledge/information extraction,” or that has the same effect via a different technical approach (e.g., clustering). This includes but is not quite limited to text mining, where “text mining” is defined by Ramana Rao’s phrase “statistics about statements.”
I think a lot of the most important questions can indeed be clustered into three groups, namely:
- Which application segments are the biggest? Which are growing the fastest?
- How is the “whole product” shaping up in each market sector you pursue? I.e., what combination of your technology, your services, partner technology, and partner services is best meeting the customer’s needs?
- Which marketing pitches do customers, prospects, and influencers agree with? Which true ones can you make that you feel they unfortunately don’t or wouldn’t buy into? And in general, what do IT departments think about text analytics?
If you have any thoughts on these subjects, please share them in the comment thread! (One catch: Comment spam is really bad these days, often overflowing Akismet’s measly 150 message spam buffer. If your post somehow gets lost in the trash, I apologize deeply in advance and implore you to contact me directly.) Please also see last year’s post-Summit thread on text analytics marketing, and this observation on major text mining applications.
One other thing — if you’re interested in going to the Summit, please contact me. Ravi has given me a special registration discount I can hand out.
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4 Responses to “Three crucial issues in text analytics”
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curt,
count me in. We at SAS are continuing to see evidence that
the text analytics and search may be converging.
the traditional market for SAS is on the innovative analytic
investigative application to enhance business (or research).
with our new growth in BI and DI we are attracting the attention
of many more IT audiences and it is they who are seeing potential
for our text mining product in the area of search.
Expected collaborative filtering / memory-based reasoning
are two examples of technical topics
which are progressing due to share approaches from the
two sides of the fence.
Hi Mary!!!!
Could you say more about the text mining/search interaction that’s occurring in the SAS customer base?
CAM
[…] I tried to invite Jay Henderson so speak on the Text Analytics Summit marketing panel, but got no answer to my e-mail. The company phone directory didn’t work so well for him either. I sent e-mail to a general PR company e-mail address, and that didn’t get returned. And Ravi tells me he has had similar difficulties reaching them. […]
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