Abstract
Nowadays, the volume of legal information available is continuously growing. As a result, browsing and querying this huge legal corpus in search of specific information is currently a tedious task exacerbated by the fact that data presentation does not usually meet the needs of professionals in the sector. To satisfy these ever-increasing needs, we have designed an appropriate solution to provide an adaptive and intelligent solution for the automatic answer of questions of legal content based on the computation of reinforced co-occurrence, i.e. a very demanding type of co-occurrence that requires large volumes of information but guarantees good results. This solution is based on the pattern-based methods that have been already successfully applied in information extraction research. An empirical evaluation over a dataset of legal questions seems to indicate that this solution is promising.
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Although we foresee learning the parameters of our system as future work.
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This research work has been supported by the Austrian Ministry for Transport, Innovation and Technology, the Federal Ministry of Science, Research and Economy, and the State of Upper Austria in the frame of the COMET center SCCH.
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Martinez-Gil, J., Freudenthaler, B., Tjoa, A.M. (2019). Multiple Choice Question Answering in the Legal Domain Using Reinforced Co-occurrence. In: Hartmann, S., Küng, J., Chakravarthy, S., Anderst-Kotsis, G., Tjoa, A., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2019. Lecture Notes in Computer Science(), vol 11706. Springer, Cham. https://doi.org/10.1007/978-3-030-27615-7_10
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