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Generating Semantic Aspects for Queries

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons101674

Gupta,  Dhruv
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44119

Berberich,  Klaus
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons180924

Strötgen,  Jannik
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons202668

Zeinalipour-Yazti,  Demetrios
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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gupta-dhruv-mpii-techreport.pdf
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Zitation

Gupta, D., Berberich, K., Strötgen, J., & Zeinalipour-Yazti, D.(2017). Generating Semantic Aspects for Queries (MPI–I–2017–5-001). Saarbrücken: Max-Planck-Institut für Informatik.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-002E-07DD-0
Zusammenfassung
Ambiguous information needs expressed in a limited number of keywords often result in long-winded query sessions and many query reformulations. In this work, we tackle ambiguous queries by providing automatically gen- erated semantic aspects that can guide users to satisfying results regarding their information needs. To generate semantic aspects, we use semantic an- notations available in the documents and leverage models representing the semantic relationships between annotations of the same type. The aspects in turn provide us a foundation for representing text in a completely structured manner, thereby allowing for a semantically-motivated organization of search results. We evaluate our approach on a testbed of over 5,000 aspects on Web scale document collections amounting to more than 450 million documents, with temporal, geographic, and named entity annotations as example dimen- sions. Our experimental results show that our general approach is Web-scale ready and finds relevant aspects for highly ambiguous queries.