Applying Commonsense Reasoning to Place Identification

Abstract

Recent mobile computing applications try to automatically identify the places visited by the user from a log of GPS readings. Such applications reverse geocode the GPS data to discover the actual places (shops, restaurants, etc.) where the user has been. Unfortunately, because of GPS errors, the actual addresses and businesses being visited cannot be extracted unambiguously and often only a list of candidate places can be obtained. Commonsense reasoning can notably help the disambiguation process by invalidating some unlikely findings (e.g., a user visiting a cinema in the morning). This paper illustrates the use of Cyc—an artificial intelligence system comprising a database of commonsense knowledge—to improve automatic place identification. Cyc allows to probabilistically rank the list of candidate places in consideration of the commonsense likelihood of that place being actually visited on the basis of the user profile, the time of the day, what happened before, and so forth. The system has been evaluated using real data collected from a mobile computing application.