I just got back from the Text Analytics Summit and it was a very good conference. I've been attending the Summit for the last three years and it has gotten better every year. This year, it seemed like there were a lot more end users and the conference had more of a business oriented approach than in previous years. Don't get me wrong—there were still technical discussions, but I liked the balance.

A major theme this year, as in previous years, was on Voice of the Customer applications. That is to be expected, in some ways, because it is still a hot application area and most of the vendors at the conference (including Attensity, Clarabridge, Lexalytics, SAS, and SPSS) focus on it in one form or another. This year, there was a lot of discussion about using social media for text analytics and VoC kinds of applications. Social media meaning blogs, twitter, and even social networks. The issue of sentiment analysis was discussed at length since it is a hard problem. Sarcasm, irony, the element of surprise, and dealing with sentiment at the feature level were all discussed. I was glad to hear it, because it is very important. SAS also made an announcement about some of its new features around sentiment analysis. I'll blog about that in a few days.

Although there was a heavy focus on the VoC type applications, we did hear from Ernst & Young on fraud applications. This was interesting because it showed how human expertise, in terms of understanding certain phrases that might appear in fraud, might be used to help automate fraud detection. Biogen Inc also presented on its use of text analytics in life sciences and biomedical research. We also heard what Monster and Facebook are doing with text analytics, which was quite interesting. I would have liked to hear more about what is happening with text analytics in media and publishing and e-Discovery. It would have also been useful to hear more about how text analytics is being incorporated into a broader range of applications. I'm seeing (and Sue Feldman, from IDC, noted this too) a large number of services springing up that use text analytics. This spans everything from new product innovation to providing real time insight to traders. As these services, along with the SaaS model, continue to explode, it would be useful to hear more about them next year.

Other observations
Here are some other observations on topics that I found interesting.

• Bringing people into the equation: While text analytics is very useful technology, it needs people to make it work. The technology itself is not Nirvana. In fact, it can be most useful when a person works together with the technology to make it zing. While people who use the technology obviously know this (there is work that has to be done by people to make text analytics work), I think that people beginning the process need to be aware of this too, for many reasons. Not only are people necessary to make the technology work, the cultural component is also critical, as it is in the adoption of any new technology. Having said this, there was discussion on the end user panel about how companies were making use of the SaaS model (or at least services), since it wasn't working out for IT (not quite sure why—either they didn't have the time or didn't have the skills).
• Managing expectations. This came up on some of the panels and in a few talks. There were two interesting comments worth noting. First, Chris Jones, from Intuit, said that some people believe that text analytics will tell you what to do, so expectations need to be set properly. In other words, people need to understand that text analytics will uncover issues and even the root cause of the issues, but it is up to a company to figure out what to do with that information. Second, there was an interesting discussion around the notion of the 85% accuracy that text analytics might provide. The end user panel was quite lively on this topic. I was especially taken with comments from Chris Bowmann, a former school superintendent of the Lafourche Parish School Board, and how he had used text analytics to try to help keep kids in school. He used the technology to cull through disciplinary records to see what patterns were emerging. Very interesting. Yes, as he pointed out, text analytics may not be 100% accurate, but think of what 85% can get you!
• Search needs to incorporate more text analytics. There were two good search talks on the agenda: Usama Fayyad, CEO of Open Insights who spoke about text analytics and web advertising as well as how text analytics might be used to help search "get things done" (i.e. like book a trip). The other speaker on the topic was Daniel Tunkelang from Endeca, who talked about text analytics and exploratory search. There were a number of comments from people in the audience as well about services like Wolfram Apha.
• Content Management. I was happy to see more about enterprise content management this year and see more people in the audience who were interested in it. There was even a talk about it from Lou Jordano from EMC.

I think anyone who attended the conference would agree that text analytics has definitely hit the main stream.