In this paper we present the features of a Question/Answering (Q/A) system that had unparalleled performance in the TREC-9 evaluations. We explain the accuracy of our system through the unique characteristics of its architecture: (1) usage of a wide-coverage answer type taxonomy; (2) repeated passage retrieval; (3) lexico-semantic feedback loops; (4) extraction of the answers based on machine learning techniques; and (5) answer caching. Experimental results show the eects of each feature on the overall performance of the Q/A system and lead to general conclusions about Q/A from large text collections.

SmartWeb aims to provide intuitive multimodal access to a rich selection of Web-based information services. We report on the current prototype with a smartphone client interface to the Semantic Web. An advanced ontology-based representation of facts and media structures serves as the central description for rich media content. Underlying content is accessed through conventional web service middleware to connect the ontological knowledge base and an intelligent web service composition module for external web services, which is able to translate between ordinary XML-based data structures and explicit semantic representations for user queries and system responses. The presentation module renders the media content and the results generated from the services and provides a detailed description of the content and its layout to the fusion module. The user is then able to employ multiple modalities, like speech and gestures, to interact with the presented multimedia material in a multimodal way.