The Changing Face of Text Analytics

So, it's been a while since I penned a blog post, and in this case that's a good thing, because its been a pretty busy summer. As I haven't blogged in a while, I thought it would be a good time for a "State of the State" sort of post, so without further delay...

Sentiment: A true tale of when bad was good

Sentiment is usually categorized into three buckets: positive, negative and neutral. It often get's presented looking something like this:

Why it's crucial to make sense of "Twitter speak"

Jeff Catlin provided ZDNet's Jennifer Leggio a guest post on why companies need to be thinking about twitter speak and how it can be analyzed. Check it out here.

Stuck in Neutral

Recently I had one of those unfortunate circumstances where a customer of ours was unhappy with the results of the sentiment produced by Salience and contacted us to help tune the engine.

Coming soon: Service Pack 1

As with any software, as soon as we released Acquisition 6.4 and Salience 4.1 we started looked at all the features we'd put in, and the features that were left on the editing room floor so to spea

Taking a gamble on automated text analytics

At one of the sessions at the Text Analytics Summit 09, moderated by Katey Wood of 451 Group, several panelists engaged in a lively discussion about accuracy in text and sentiment analysis software.

Text Analytics Summit 09

As the Text Analytics Summit draws to a close, I am watching many of the familiar faces that approached our exhibit table to learn more about Lexalytics grab their last cup of coffee and snack before heading out. We were happy to host a workshop this year, introducing the beta of our LexaScope product, due out in early July.

Went to Enterprise Search Summit last week

I attended the Enterprise Search Summit in New York last week, and there is no debating the fact that the economy is affecting attendance at conference events. I’ve been to ESS a couple of other times, and the decline in attendance this year was noticeable.

What is Text Analytics - Final

This will be the final piece on the basics of Text Analytics. I’ve covered the basics of categorization/classification, sentiment analysis and finally I’ll spend some time on entity extraction.

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