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
We introduce the Ranked Feature Fusion framework for information retrieval system design. Typical information retrieval formalisms such as the vector space model, the bestmatch mo...
We propose a language-model-based ranking approach for SPARQLlike queries on entity-relationship graphs. Our ranking model supports exact matching, approximate structure matching,...
We present an algorithm for updating the PageRank vector [1]. Due to the scale of the web, Google only updates its famous PageRank vector on a monthly basis. However, the Web chan...
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...