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...