In this paper, we present our submission to the CLEF-2020 shared task on Comparative Argument Retrieval. We propose several approaches based on state-of-the-art NLP techniques such as Seq2Seq, Transformer, and BERT embedding. In addition to these models, we use features that describe the comparative structures and comparability of text. For the set of given topics, we retrieve the corresponding responses and rank them using these approaches. Presented solutions could help to improve the performance of processing comparative queries in information retrieval and dialogue systems.
|Journal||CEUR Workshop Proceedings|
|Publication status||Published - 2020|
|Event||11th Conference and Labs of the Evaluation Forum, CLEF 2020 - Thessaloniki, Greece|
Duration: 22 Sep 2020 → 25 Sep 2020