Thursday, 6th of May 2021, 12:00 – 1:00

Open question answering in temporal news article collections

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Adam Jatowt
Researcher at DiSC, University of Innsbruck


 The fields of automatic question answering and reading comprehension have been recently advancing quite rapidly. Open-domain question answering, in particular, assumes answering arbitrary user questions from large document collections such as Wikipedia. We can already observe open-domain question answering in practice when web search engines answer directly our questions instead of requiring us to read through the returned search results. This talk will be about our latest efforts in automatic question answering over temporal news collections which typically contain millions of news articles published during several decades long time frames. To locate the correct answer in such collections one needs first to find candidate documents that may contain the answer. We propose a re-ranking approach for news articles by utilizing temporal information embedded in documents and in the collection, thus combining solutions from Temporal Information Retrieval and Natural Language Processing.


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