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Champion: George Gkotsis
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Participant(s):Maria Liakata, Carlos Pedrinaci, Karen Stepanyan, John Domingue

Similar Technologies:CARRE

Timeline:01 Jul 2014 - 01 Oct 2014



Automatic Community-based Question Answering

ACQUA is looking at the discretised version of linguistic features of each candidate answer and predicts which answer is going to be marked as "accepted". Past knowledge such as user reputation or future knowledge, such as score of the answers is not taken into account. Hence, ACQUA can predict which answer is going to get accepted in real-time settings with minimum resources.

ACQUA makes use of the StackExchange API, fetches all answers and analyses them. Our web service is then highlighting one answer indicating it as the "accepted".

This work has been funded by the CARRE project.


Publications | Visit External Site for Details  

Gkotsis, G., Liakata, M., Pedrinaci, C., Stepanyan, K. and Domingue, J. (2015) ACQUA: Automated Community-based Question Answering through the Discretisation of Shallow Linguistic Features, The Journal of Web Science, 1, 1

Publications | Visit External Site for Details Publications | doi 

Gkotsis, G., , k., Pedrinaci, C., Domingue, J. and Liakata, M. (2014) It's all in the Content: State of the art Best Answer Prediction based on Discretisation of Shallow Linguistic Features, ACM Web Science 2014 Conference, Indiana University, Bloomington, USA, pp. 9

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Marie Curie Early Stage Researcher

Knowledge Media Institute (KMi)
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The Knowledge Media Institute invites applications for an Early Stage Researcher to work in the area of bias in Artificial Intelligence. The researcher will work within the interdisciplinary...


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