@inproceedings{curto-etal-2014-just,
title = "{JUST}.{ASK}, a {QA} system that learns to answer new questions from previous interactions",
author = "Curto, S{\'e}rgio and
Mendes, Ana C. and
Curto, Pedro and
Coheur, Lu{\'\i}sa and
Costa, {\^A}ngela",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/130_Paper.pdf",
pages = "2603--2607",
abstract = "We present JUST.ASK, a publicly available Question Answering system, which is freely available. Its architecture is composed of the usual Question Processing, Passage Retrieval and Answer Extraction components. Several details on the information generated and manipulated by each of these components are also provided to the user when interacting with the demonstration. Since JUST.ASK also learns to answer new questions based on users feedback, (s)he is invited to identify the correct answers. These will then be used to retrieve answers to future questions.",
}
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%0 Conference Proceedings
%T JUST.ASK, a QA system that learns to answer new questions from previous interactions
%A Curto, Sérgio
%A Mendes, Ana C.
%A Curto, Pedro
%A Coheur, Luísa
%A Costa, Ângela
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 may
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F curto-etal-2014-just
%X We present JUST.ASK, a publicly available Question Answering system, which is freely available. Its architecture is composed of the usual Question Processing, Passage Retrieval and Answer Extraction components. Several details on the information generated and manipulated by each of these components are also provided to the user when interacting with the demonstration. Since JUST.ASK also learns to answer new questions based on users feedback, (s)he is invited to identify the correct answers. These will then be used to retrieve answers to future questions.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/130_Paper.pdf
%P 2603-2607
Markdown (Informal)
[JUST.ASK, a QA system that learns to answer new questions from previous interactions](http://www.lrec-conf.org/proceedings/lrec2014/pdf/130_Paper.pdf) (Curto et al., LREC 2014)
ACL