Selecting the Best Mobile Information Service with Natural Language User Input

Abstract

Information services accessed via mobile phones provide information directly relevant to subscribers’ daily lives and are an area of dynamic market growth worldwide. Although many information services are currently offered by mobile operators, many of the existing solutions require a unique gateway for each service, and it is inconvenient for users to have to remember a large number of such gateways. Furthermore, the Short Message Service (SMS) is very popular in China and Chinese users would prefer to access these services in natural language via SMS. This chapter describes a Natural Language Based Service Selection System (NL3S) for use with a large number of mobile information services. The system can accept user queries in natural language and navigate it to the required service. Since it is difficult for existing methods to achieve high accuracy and high coverage and anticipate which other services a user might want to query, the NL3S is developed based on a Multi-service Ontology (MO) and Multi-service Query Language (MQL). The MO and MQL provide semantic and linguistic knowledge, respectively, to facilitate service selection for a user query and to provide adaptive service recommendations. Experiments show that the NL3S can achieve 75–95% accuracies and 85–95% satisfactions for processing various styles of natural language queries. A trial involving navigation of 30 different mobile services shows that the NL3S can provide a viable commercial solution for mobile operators.