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Knowledge Infused Information Retrieval

By integrating external knowledge originating from taxonomies, ontologies, or knowledge graphs into the information retrieval process, we aim to improve the outcomes in terms of relevance and completeness.
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Related Publications

Taxonomy-Enhanced Document Retrieval with Dense Representations

Type: Conference Paper

Venue: iDSC 2023

Authors: Victor Mireles, Artem Revenko, Ioanna Lytra, Anna Breit, and Julia Klezl

Proposal for PORQUE, a Polylingual Hybrid Question Answering System

Type: Poster

Venue: SEMANTiCS 2022  

Authors: Victor Mireles, Artem Revenko, Nikit Srivastava, Daniel Vollmers, Anna Breit and Diego Moussallem

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Related Projects

PORQUE: Polylingual Hybrid Question Answering 1

PORQUE: Polylingual Hybrid Question Answering

finished
Dec 1, 2020 Nov 30, 2023

PORQUE will develop and evaluate an extensible platform for polylingual question answering by relying on knowledge graphs and text. We will deliver a prototype, which will be evaluated through commercial solutions in three domains (open data, publishing, energy).

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