We consider the problem of identifying the consensus ranking for the results of a query, given preferences among those results from a set of individual users. Once consensus ranki...
Paul N. Bennett, David Maxwell Chickering, Anton M...
This paper proposes a demo of the TopX search engine, an extensive framework for unified indexing, querying, and ranking of large collections of unstructured, semistructured, and ...
Adapting to rank address the the problem of insufficient domainspecific labeled training data in learning to rank. However, the initial study shows that adaptation is not always...
Keke Chen, Jing Bai, Srihari Reddy, Belle L. Tseng
Some machine learning applications are intended to learn properties of data sets where the correct answers are not already known to human users. It is challenging to test such ML ...
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...