Gathering Preference Data from Restricted Natural Language

The Resource Description Framework provides elaborate methods of specifying semantic information for automated aggregation and other types of processing; however, RDF is too complicated for most casual computer and internet users who prefer instead to communicate in natural language text form. Recently, much progress has been made in the area of extracting semantic data from unrestricted natural language, such as automatic document classification; however, much of the content of natural language texts still remains inaccessible for automated semantic processing. In this work a restricted natural language approach to the expression of preferences is proposed that sacrifices freedom of expression for accurateness of semantic translation. A limited number of grammatical constructs for the expression of preferences is described, and an application to the expression of cinema and movie related preferences is outlined. It is shown that with a moderate amount of restriction on natural language at least in the domain of preference specification a large amount of semantic information can be extracted while maintaining a level of user-friendliness suitable for more wide-spread application beyond the limited number of RDF experts.

Authors and Affiliations

1. Institute for Information Business, Vienna University of Economics and Business Administration, Augasse 2–6, A-1090, Vienna, Austria

   Johann Mitlöhner

Editors and Affiliations

1. School of Engineering and Advanced Technology, Massey University, Private Bag 756, Wellington, New Zealand

   Roland Kaschek

2. Institute of Applied Informatics Research Group Application Engineering, Alpen-Adria-Universität Klagenfurt, Universitätsstraße 65-67, 9020, Klagenfurt, Austria

   Christian Kop , Claudia Steinberger  & Günther Fliedl ,  & 

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