Search

In this paper we present the digital library assistant (DiLiA). The system aims at augmenting the search in digital libraries in several dimensions. In the project advanced information visualisation methods are developed for user controlled interactive search. The interaction model has been designed in a way that it is transparent to the user and easy to use. In addition, information extraction (IE) methods have been developed in DiLiA to make the content more easily accessible, this includes the identification and extraction of technical terms (TTs) – single and multi word terms – as well as the extraction of binary relations based on the extracted terms. In DiLiA we follow a hybrid information extraction approach – a combination of metadata and document processing. [ABSTRACT FROM AUTHOR]

The Semantic Desktop is a means to support users in Personal Information Management (PIM). It provides an excellent test bed for Semantic Web technology: resources (e. g., persons, projects, messages, documents) are distributed amongst multiple systems, ontologies are used to link and annotate them. Finding information is a core element in PIM. For the end user, the search interface has to be intuitive to use, natural language queries provide a simple mean to express requests. State of the art semantic search engines focus on fact retrieval or on semantic document retrieval. We combine both approaches to search the Semantic Desktop exploiting all available information. Our semantic search engine, built on semantic teleporting and spreading activation, is able to answer natural language queries with facts, e. g., a specific phone number, and/or relevant documents. We evaluated our approach on ESWC 2007 data in comparison with Google site search. [ABSTRACT FROM AUTHOR]