Time-Aware Rank Aggregation for Microblog Search

CIKM 2014

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 microblog search algorithms.



    The doi link – “http://doi.acm.org/10.1145/1645953.1646215” – in the bibtex points to a different paper:

      Edgar Meij

      Yes, you’re right, thanks!

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