Better late than never … but here’s a quick report on the 3rd London Text Analytics meetup, which took place in early March at Fizzback’s offices on the Strand. I was particularly pleased to make this meeting a success as kick-starting the group was one of my resolutions for 2011… I’m convinced that there is significant potential for such a group in bringing together the nascent text analytics community in London.
First up was Adam Wyner of Liverpool University, who described his work in applying text analytics to legal cases. Lawyers, it seems, are very text-oriented in their work, and much of their activity is based on the interpretation of legal precedent established through analysis of previous cases. This analysis takes the form of comparison based on a variety of legal factors, which are used in the argumentation and reasoning underpinning a given case. Clearly, if tools could be provided to reliably extract or identify such factors in natural language text, then the potential for facilitating the legal process (and providing tools for trainee lawyers) is considerable. Adam’s approach is based on a bottom-up process that identifies patterns of co-occurrence of specific legal concepts and terms, which are then mapped onto a taxonomy of 27 base-level factors. He’ll be talking more about this at the upcoming ICAIL workshop on Applying Human Language Technologies to the Law.
Next up was Adi Andrei who presented an intriguing account of how to use text analytics as a catalyst for new product generation. His core idea was essentially that product features or “themes” that sell well within a certain category (of product) can be productively applied to a new category to generate novel product ideas. The core process seems to something be this:
- Identify themes T that sell well in Category C
- Introduce these themes in a new Category
- Repeat for all T & C
He presented some quite plausible data showing how the themes of “sleep” and “sustainability” (as represented by their natural language descriptions in the product specifications and marketing material) had been extended to diverse products such as Tea and Laundry products. I know it sounds too good to be true – and no doubt my account has skipped over some of the key details – but I was encouraged to see that Adi had previously applied similar techniques at NASA and was able to present further data and a plausible rationale to back up his account. This is one application of text analytics I shall definitely watch with interest.
So all in all, a productive evening, and good to see a full house. In fact, we’ll probably re-use the same formula going at future events: a research-oriented talk, a practitioner oriented talk, then drinks in a local pub. I’m already on the lookout for speakers for our next event, so if you’re amenable to having your arm twisted in such a way, drop me a line.