Learning to Attend, Copy, and Generate for Session-Based Query Suggestion

Our paper "Learning to Attend, Copy, and Generate for Session-Based Query Suggestion", with Sascha Rothe, Enrique Alfonseca, and Pascal Fleury, has been accepted as a long paper at the international Conference on Information and Knowledge Management (CIKM'17). This paper is on the outcome of my internship at Google Research. \o/ Users interact with search engines […]

Share your Model instead of your Data!

Our paper "Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking", with Hosein Azarbonyad, Jaap Kamps, and Maarten de Rijke, has been accepted at Neu-IR: SIGIR Workshop on Neural Information Retrieval (NeuIR'17). \o/ Deep neural networks demonstrate undeniable success in several fields and employing them is taking o for information retrieval […]

Modeling Retrieval Problem using Neural Networks

Despite the buzz surrounding deep neural networks (DNN) models for information retrieval, the literature is still lacking a systematic basic investigation on how generally we can model the retrieval problem using neural networks. Modeling the retrieval problem in the context of neural networks means the general way that we frame the problem with regards to […]