Abstract
This paper presents a deep learning based dialogue system which has been trained to answer user queries posed as questions during a conversation. The proposed system, though generative, takes advantage of domain specific knowledge for generating valid answers. The evaluation analysis shows that the proposed system obtained a promising result.
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Acknowledgments
Kolawole J. Adebayo has received funding from the Erasmus Mundus Joint International Doctoral (Ph.D.) programme in Law, Science and Technology. Luigi Di Caro have received funding from the European Union’s H2020 research and innovation programme under the grant agreement No 690974 for the project “MIREL: MIning and REasoning with Legal texts”.
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John, A.K., Di Caro, L., Robaldo, L., Boella, G. (2017). Legalbot: A Deep Learning-Based Conversational Agent in the Legal Domain. In: Frasincar, F., Ittoo, A., Nguyen, L., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2017. Lecture Notes in Computer Science(), vol 10260. Springer, Cham. https://doi.org/10.1007/978-3-319-59569-6_32
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