October 5th, 2007 Curt Monash
Besides asking them technical questions, I surveyed Attensity and Clarabridge last week about text mining application trends, getting generously detailed answers from Michelle De Haaff of Attensity and Justin Langseth of Clarabridge. Perhaps the most important point to emerge was that it’s not just about particular apps. Enterprises are doing text mining POCs (Proofs of Concept) around specific apps, commonly in the CRM area, but immediately structuring the buying process in anticipation of a rollout across multiple departments in the enterprise.
Other highlights of what they said included:
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Posted in Application areas, Attensity, Clarabridge, ClearForest and Reuters, Factiva and Dow Jones, Investment research and trading, Text mining, Voice of the Customer, Voice of the Market/competitive intelligence | 3 Comments »
October 5th, 2007 Curt Monash
Michelle DeHaaff, Attensity’s VP of Marketing, just introduced me to a nice phrase — Voice of the Market, obviously related to Voice of the Customer. As Michelle put it:
We’ve also expanded into what we call Voice of the Market data - providing a combination of analysis on external and internal data
- this is how we’ve heard our customers put it:
*Customer feedback comes in many forms……when customers don’t know you are listening (blogs, public web forums) it is important to hear what they say.
*When customers purposely tell you something (via emails, in surveys, captured in customer service notes) it is not only important, but expected….
The first of those would be Voice of the Market, while the second would be Voice of the Customer.
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Posted in Application areas, Attensity, Text mining, Voice of the Customer, Voice of the Market/competitive intelligence | 2 Comments »
October 5th, 2007 Curt Monash
I’ve been emailing and/or talking with both Clarabridge and Attensity this week. Since they’re the two big proponents of exhaustive extraction, I naturally asked whether there are any cases exhaustive extraction should not be used. In Clarabridge’s case, it turns out exhaustive extraction is the default, and no customer has ever turned this default off. However, their current high end is several million documents* per year. They suspect that in some current projects with much higher volumes the default may finally be turned off. Read the rest of this entry »
Posted in Attensity, Clarabridge, Comprehensive or exhaustive extraction, Text mining | 1 Comment »
October 5th, 2007 Curt Monash
David Bean of Attensity is rightly one of the most popular explainers of text mining, for his clarity and personality alike. I shot a question to him about how Attensity’s exhaustive extraction strategy handled sentiment and so on. He responded with an email that contains the best overall explanation of sentiment analysis in text mining I’ve seen anywhere. Naturally, this is rolled into an Attensity-specific worldview and sales pitch — but so what?
Our exhaustive extraction approach doesn’t compromise detection of qualifiers* because we recognize the qualifications while we have access to the complete linguistic information of the input. Much of that information is later stripped away, since it’s way more information than a user would want. We make sure we project qualifications like you mention in the final representations. In fact, we’ve put a lot of effort into recognizing “voicing,” i.e. distinguishing among negations, conditional statements, and variations in the degree of sentiment.
Examples will help here:
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Posted in Attensity, Comprehensive or exhaustive extraction, Text mining | No Comments »
June 14th, 2007 Curt Monash
If there was one theme to this year’s Text Analytics Summit, it’s “Voice of the Customer.” Attensity’s pre-conference press release was about a Voice of the Customer offering. Clarabridge’s sponsored user talk was about a Voice of the Customer app. SPSS’s marketing materials emphasized Voice of the Customer. Sentiment analysis and Web/blog scraping were frequently mentioned, in contexts such as “customer care,” “reputation management,” and/or “competitive intelligence.”
But above all, it was “Voice of the Customer.” I know it’s till June, but I think we have our text analytics industry buzzphrase of the year.
Technorati Tags: text mining, customer care, voice of the customer
Posted in Attensity, Clarabridge, SPSS, Text Analytics Summit, Text mining, Voice of the Customer | 3 Comments »
May 23rd, 2007 Curt Monash
After missing what seems to have been an uninformative press conference anyway, I hooked up later with the Business Objects folks on the phone. I say that it was probably uninformative because in the short call, it was pointed out to me that they really weren’t at liberty to say much anyway. Here are a couple of tidbits I picked up even so.
- Business Objects’ text mining partnerships have been more demo/sales-cycle than actual sales up until now. That said, they have a few deals each with Attensity and Inxight (but not with ClearForest, which pulled in its horns prior to being acquired by Reuters). I still think they’re the leading BI vendor in integrating with text mining, SAS perhaps aside (who if nothing else have a lot of fun using text mining for data cleaning). The working Inxight partnership, by the way, was all about the specific app of email compliance, with the demo being based on the publicly available Enron corpus.
- Inxight’s visualization technology is in the form of an SDK anyway. So integrating it into BOBJ’s product line should be straightforward. Note: Through the Excelsius acquisition, BOBJ has been trying to gain competitive advantage in the cool-visualization area.
- Inxight’s “federation” capability for search is pretty primitive (my term and opinion of course, not theirs). It takes in search result sets from various sources, then clusters and/or refilters them. What it does NOT do is the much harder task of taking actual relevancy rankings from various engines and somehow arbitrating between them. Nor, I’m guessing, does it even assign higher or lower weights to various corpuses or anything like that. Thus, it does not sound terribly competitive with the distributed search capabilities built into any state-of-the-art enterprise search engine.
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Posted in Attensity, Business Objects and Inxight, ClearForest and Reuters, Enterprise search, SAS, Search and text storage, Text mining | 5 Comments »
March 26th, 2007 Curt Monash
Text mining newbie Clarabridge gave me the all-too-customary “Please let us brief you, but then don’t write about it for a while” routine. Now that it’s OK to post, what I’m up for offering is a few salient points in bullet form.
- The closest analogy to what Clarabridge does is Attensity’s new(ish) strategy – extract “facts” from documents and dump them into a relational database management system. In particular, Clarabridge and Attensity alike make the case “Our categorization is more flexible because it’s applied only after the extraction happens.”
- Clarabridge’s sweet spot is extracting user opinions from short documents. E.g., the customer uses cases they talk about are customer feedback forms, public blog postings, etc. about A. hotels and B. consumer software products.
- Clarabridge has a strong business intelligence mentality, describing the product as “ETL for unstructured data.” But then, it’s spun out of a BI consultancy that itself was founded by Microstrategy veterans.
- Clarabridge uses a different database schema than Attensity. Attensity’s fact-relationship network (FRN) is basically just two thin, long tables. Clarabridge, however, uses a Microstrategy-like star schema, in which different kinds of things that you can tokenize correspond to different dimensions.
Frankly, if somebody wants an alternative to the Attensity/Teradata/Business Objects partnership they could do worse than talk with Clarabridge.
Technorati Tags: Attensity, Clarabridge, text mining
Posted in Attensity, BI integration, Clarabridge, Comprehensive or exhaustive extraction, Text mining | No Comments »
March 21st, 2007 Curt Monash
We’ve now solidified the membership of the Text Analytics Summit marketing panel. It is:
- Curt Monash, President, Monash Information Services
- Dave Kellogg, CEO, Mark Logic Corporation
- Michelle De Haaff, VP Marketing, Attensity Corporation
- Michel Lemay, VP Marketing, nstein Technologies
- Mary Crissey, SAS Analytics Marketing Manager, SAS Institute
Michelle, Michel, and Mary are all obvious choices, responsible for marketing at leading text mining vendors. In addition, Mary has excelled on the same panel in the past, Michel sent me e-mail with some brilliant thoughts on the panel subject, and Attensity has one of the most interesting strategies in the text analytics market.
As for Dave — he’s simply one of the most astute marketing theorists working in software today. And he runs a very interesting text technology company. And he used to be most senior marketing guy in all of business intelligence, when he was SVP at Business Objects. In his copious free time, he writes a really cool blog.
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Posted in Attensity, Mark Logic, SAS, Text Analytics Summit, Text mining, nStein | 3 Comments »
December 27th, 2006 Curt Monash
So far as I can tell, Attensity’s strategy when the company was originally founded was rather like ClearForest’s strategy today – and vice-versa. That said, here’s where they seem to stand at this time:
- Attensity wants to make text analytics very easy to integrate into business intelligence and data mining – at the moment, they’re not too focused on the differences between those two disciplines – and is trying to deliver the best possible fact extraction consistent with that charter.
- ClearForest wants to provide really great information extraction — to the limits of what can be done without excessive knowledge engineering – and is trying to integrate as well as possible with other technologies, the better to serve the customers who need what they offer.
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Posted in Attensity, ClearForest and Reuters, Mark Logic, TEMIS, Text mining | No Comments »
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.
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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 »