Title: Directory Assistance: Learning User Formulations for Business Listings

Authors: Cosmin Popovici, Marco Andorno, Pietro Laface, Luciano Fissore, Mario Nigra, Claudio Vair

Abstract: One of the main problems in automatic Directory Assistance (DA) for business listings is that customers 
formulate their requests for the same listing with a great variability. 
In this paper we show that an automatic approach allows to detect, from field data, user formulations that were not foreseen by the designers, and that can be added, as variants, to the denominations already included in the system to reduce its failures.This approach has been used to automatically detect new formulations, discover why existing formulations exhibit high rejection rates, and to compute the percentage of routed versus automated calls per phone number.

a01cp005.ps a01cp005.pdf