The research team at Cornell University, headed by Professor Thorsten Joachims, has produced another paper relating to Surf Canyon entitled “Structured Learning of Two-Level Dynamic Rankings.” It was presented on October 26, 2011 at CIKM in Glasgow. This paper further explores the concept of “Dynamic Ranked Retrieval” by proposing a two-level dynamic ranking model:

For ambiguous queries, conventional retrieval systems are bound by two conflicting goals. On the one hand, they should diversify and strive to present results for as many query intents as possible. On the other hand, they should provide depth for each intent by displaying more than a single result. Since both diversity and depth cannot be achieved simultaneously in the conventional static retrieval model, we propose a new dynamic ranking approach. In particular, our proposed two-level dynamic ranking model allows users to adapt the ranking through interaction, thus overcoming the constraints of presenting a one-size-fits-all static ranking.

Surf Canyon is again referenced, along with our 2009 SIGIR research paper:

We argue that a key to solving the conflict between depth and diversity lies in the move to dynamic retrieval models [2] that can take advantage of user interactions. Instead of presenting a single one-size-fits-all ranking, dynamic retrieval models allow users to adapt the ranking dynamically through interaction, as is done by surfcanyon.com [5].

In February 2008, Surf Canyon launched its Dynamic Ranked Retrieval application to rave reviews. As the body of research relating to Dynamic Ranked Retrieval grows, we continue to be encouraged by the potential of this technology to vastly enhance the quality of information retrieval.