Turning reviews into ratings

The proliferation of websites such as Yelp and CitySearch has made it easy to find local businesses that meet common search criteria - moderately priced seafood restaurants, for example, within a quarter-mile of a particular subway stop. But what about the not-so-common criteria? How big are the portions? Are diners packed too closely together? Does the bartender make a good martini? That kind of information often turns up in reviews posted by site users, but finding it can mean skimming through pages of largely irrelevant text. A new system from the Computer Science and Artificial Intelligence Laboratory's Spoken Language Systems Group, however, automatically combs through users' reviews, extracting useful information and organizing it to make it searchable. The first thing the system does is determine the grammatical structure of the sentences that compose the reviews and sort the words used into adjective-noun pairs. If, for instance, someone has written, 'I found the martinis to be excellent,' the algorithm extracts the phrase 'excellent martinis.' As the group's name might imply, its principal area of research is computer systems that respond to spoken language, and indeed, the interface for the new system is speech-based: A user looking for seafood restaurants, for instance, simply says 'Show me seafood restaurants' into the microphone of either a computer or a cell phone. Likewise, the algorithm that does the grammatical analysis is one that Stephanie Seneff, a senior research scientist with the group, began developing 20 years ago as a component of speech-recognition systems.