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Is the context-based Word2Vec representation useful to determine Question Words for Generators?

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2020

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Gesellschaft für Informatik e.V.

Zusammenfassung

Question and answer generation approaches focus on the quality and correctness of generated questions for online courses but miss to use a good question word, which is a deficiency reported by many previous studies. In this experimental setup, we explored whether the word2vec representation, which is semantic-based, can be used to predict question words. We compare two pipelines of the prediction process and observed that splitting the problem into several subproblems performs similar to feeding a neural network with all the data. Although our approach is promising to take the context-based representation into account we can see that the success rate is still low but better than guessing.

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Rüdian, Sylvio; Pinkwart, Niels (2020): Is the context-based Word2Vec representation useful to determine Question Words for Generators?. DELFI 2020 – Die 18. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V.. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-702-9. pp. 289-294. Online. 14.-18. September 2020

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