November 30th, 2006 Curt Monash
One semi-flagship use for text mining is to track sentiment across news articles, websites, etc. Should this be done openly, or is there a danger of being spoofed? (I doubt it; probably no more than a few of the sites would ever be motivated to do so.) But what if you’re making many hits against the same site, to the point that your traffic is unwelcome? Or maybe the site is a direct competitor. In such cases, hiding your tracks may be more relevant.
If any of this is an issue for you, you should take a look at Anonymizer’s growing enterprise offering. Apparently, there are commercial enterprises using thousands of seats each of Anonymizer’s cloaking service.
Posted in Text mining | No Comments »
November 17th, 2006 Curt Monash
We’re going to upgrade access to our research in various cool ways in the near future.
Right now, please bear with me in what is essentially a test post. In theory, I’ve switched the feeds here over to Feedburner. Now I’m going to test if that really has happened.
EDIT: That didn’t work. I’m going to put things back the way they were.
Posted in About this blog | 1 Comment »
November 11th, 2006 Curt Monash
Most people in the text analytics market realize that text mining and search are somewhat related. But I don’t think they often stop to contemplate just how close the relationship is, could be, or someday probably will become. Here’s part of what I mean:
- Text mining powers search. The biggest text mining outfits in the world, possibly excepting the US intelligence community, are surely Google, Yahoo, and perhaps Microsoft.
- Search powers text mining. Restricting the corpus of documents to mine, even via a keyword search, makes tons of sense. That’s one of the good ideas in Attensity 4.
- Text mining and search are powered by the same underlying technologies. For starters, there’s all the tokenization, extraction, etc. that vendors in both areas license from Inxight and its competitors. Beyond that, I think there’s a future play in integrated taxonomy management that will rearrange the text analytics market landscape.
Read the rest of this entry »
Posted in Attensity, Business Objects and Inxight, Enterprise search, FAST, Google, IBM and UIMA, Ontologies and context identification, Open source text analytics, Search and text storage, Text mining | 3 Comments »