Sequence to Sequence Learning for Query Expansion

As fas as we are aware, using sequence to sequence algorithms for query expansion hasnot been explored yet in Information Retrievalliterature nor in Question-Answering's. We tried to fill this gap in the literature with a custom Query Expansion system trained and tested on open datasets. One specificity of our engine compared to classic ones is that it does not need the documents to expand the introduced query. We test our expansions on three different tasks: Information Retrieval, Answer preselection and Text classification. Our method yielded a slight improvement in performance in the three tasks .