  We describe a method for proactive information retrieval targeted at
retrieving relevant information during a writing task. In our method, the
current task and the needs of the user are estimated, and the potential next
steps are unobtrusively predicted based on the user's past actions. We focus on
the task of writing, in which the user is coalescing previously collected
information into a text. Our proactive system automatically recommends the user
relevant background information. The proposed system incorporates text input
prediction using a long short-term memory (LSTM) network. We present
simulations, which show that the system is able to reach higher precision
values in an exploratory search setting compared to both a baseline and a
comparison system.
