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...
The CLEF 2003 Interactive Track (iCLEF) was the third year of a shared experiment design to compare strategies for cross-language search assistance. Two kinds of experiments were p...
An important trend in Web information processing is the support of multimedia retrieval. However, the most prevailing paradigm for multimedia retrieval, content-based retrieval (C...
Work on evaluating and improving the relevance of web search engines typically use human relevance judgments or clickthrough data. Both these methods look at the problem of learni...
Hao Ma, Raman Chandrasekar, Chris Quirk, Abhishek ...
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...