Advances in Ranking
نویسندگان
چکیده
We study the standard retrieval task of ranking a fixed set of documents given a previously unseen query and pose it as the half-transductive ranking problem. The task is partly transductive as the document set is fixed. Existing transductive approaches are natural non-linear methods for this set, but have no direct out-ofsample extension. Functional approaches, on the other hand, can be applied to the unseen queries, but fail to exploit the availability of the document set in its full extent. This work introduces a half-transductive approach to benefit from the advantages of both transductive and functional approaches and show its empirical advantage in supervised ranking setups.
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