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<pdf width="1500px">https://ceur-ws.org/Vol-1883/invited6.pdf</pdf>
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           Semantic Search on Text and Knowledge Bases

                                                  Hannah Bast
                                              Universität Freiburg
                                               Freiburg, Germany
                                         bast@informatik.uni-freiburg.de




Abstract
I will present an overview of our current research on semantic search on text and knowledge bases. By semantic
search I mean search with meaning. Our goal is to make the search as convenient as possible without losing
transparency. On approach is to aid the user in incremental query construction. Another approach is to allow
questions in free-form natural language and provide feedback on the interpretation of the question in an easily
digestible form. I also believe that it is a good idea to combine text and knowledge bases. Structured information
is best represented in a knowledge base (the semantics is then explicit in the data) but the bulk of our knowledge
of the world will always be in the form of text. I will a show a lot of examples and demos.

Bio
Hannah Bast is a professor of computer science at the University of Freiburg at the foot of the beautiful black
forest in the southwest of Germany. She is a big fan of easy to use and powerful information systems of all kinds.
One of the algorithms from her work is used for public transit routing on Google Maps. Her CompleteSearch
engine powers the bibliography search on DBLP. She is convinced of the great potential of deep learning for
natural language understanding. She believes that the world has more pressing problems than whether AI will
eventually take over.




Copyright c by the paper’s authors. Copying permitted for private and academic purposes.
In: L. Dietz, C. Xiong, E. Meij (eds.): Proceedings of the First Workshop on Knowledge Graphs and Semantics for Text Retrieval
and Analysis (KG4IR), Tokyo, Japan, 11-Aug-2017, published at http://ceur-ws.org




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