Our CIKM 2014 paper “Time-aware rank aggregation for microblog search” by Shangsong Liang, Zhaochun Ren, Wouter Weerkamp, Edgar Meij and Maarten de Rijke is available online now.

In the paper we tackle the problem of searching microblog posts and frame it as a rank aggregation problem where we merge result lists generated by separate rankers so as to produce a final ranking to be returned to the user. We propose a rank aggregation method, TimeRA, that is able to infer the rank scores of documents via latent factor modeling. It is time-aware and rewards posts that are published in or near a burst of posts that are ranked highly in many of the lists being aggregated. Our experimental results show that it significantly outperforms state-of-the-art rank aggregation and time-sensitive micro- blog search algorithms.