Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
Time is an important dimension of relevance for a large number of searches, such as over blogs and news archives. So far, research on searching over such collections has largely f...
Wisam Dakka, Luis Gravano, Panagiotis G. Ipeirotis
The leading web search engines have spent a decade building highly specialized ranking functions for English web pages. One of the reasons these ranking functions are effective is...
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...