I mentioned last time that the technique we use to determine topics is a variant of something that has been around for fifty years. In this part I will talk about the intriguing history of this technique, and in the process, I hope to illuminate what we are doing and
We’ve all heard the notion that it costs more to acquire a customer than to retain one. There are few that can beat the communications industry where it can cost up to 15 times more to acquire a customer. Last week I read countless stories about the latest and greatest
Topic Modeling of documents is hot in the research community. Conferences are filled with different ways of determining topic models and how to apply them. The prestigious data mining conference KDD has in recent years had entire sections on topic modeling. The leading algorithms all have three-letter acronyms and sound
Those of you who have seen the new version of SAS Text Miner know that we are transitioning from a “document clustering” approach towards a “topics in documents” approach. I have received a lot of questions about this, so I thought I would address some of them in a multi-part
Attending the Predictive Analytics World (PAW) Conference is truly a rewarding experience. Compliments go to Eric Siegel and the conference organizers for assembling such an interesting cast of case studies and speakers. Day 2 kicked off with a key note from Kim Larsen from Charles Schwab & Co. on net
Manya Mayes, a Solutions Architect and Chief Text Mining Strategist at SAS, just gave a wonderful presentation about using SAS Text Miner with SAS Content Categorization. Both products have been used successfully by SAS customers for some time. But Manya and our clients are now using them to solve old
Wow--attending the 5th annual Text Analytics Summit was truly an enriching experience. My compliments to Seth Grimes and the conference organizers for convening such interesting speakers and content. Day 2 started with Sue Feldman and Hadley Reynolds of IDC. Key takeaways from their keynote, Text Analytics Market Report: Think about
I asked around for some 2009 predictions and meant to post them here a few weeks ago, but time got away from me. We still have 11 and 1/3 months left of the year, so I don't think it's too late to predict. Do you? My colleague in external communications,
When I first heard the word metadata, I didn't get it. This was in 1999. I was new at SAS and writing an article about data warehousing. The definition, "data about data," meant nothing to me. (Plus, I've always had trouble with the meta prefix in general. Go read the
Last week I saw a slide from a customer presentation that said 85 percent of that company's data is unstructured data. This isn't usual, either. But what does it mean? First and foremost, it means the data we're all collecting at unprecedented rates is no longer stored strictly in spreadsheets
