Tech Reports
Tech Report kmi-07-03 Abstract
State of the art on Semantic Question Answering
Techreport ID: kmi-07-03
Date: 2007
Author(s): Vanessa Lopez, Enrico Motta, Victoria Uren, Marta Sabou
We analyze the contributions, challenges and dimensions of question answering on the Semantic Web by looking at the state of the art on semantic question answering systems, and the implications in traditional methods on ontology selection, mapping and semantic similarity measures to balance the heterogeneity and large scale semantic data with run time performance
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Multimedia and Information Systems is...
We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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