Most existing information retrieval (IR) systems do not take much advantage of natural language processing (NLP) techniques due to the complexity and limited observed effectivenes...
This paper is concerned with relevance ranking in search, particularly that using term dependency information. It proposes a novel and unified approach to relevance ranking using ...
The paper proposes identifying relevant information sources from the history of combined searching and browsing behavior of many Web users. While it has been previously shown that...
One current direction to enhance the search accuracy in visual object retrieval is to reformulate the original query through (pseudo-)relevance feedback, which augments a query wi...
We investigate the problem of learning to rank for document retrieval from the perspective of learning with multiple objective functions. We present solutions to two open problems...
Krysta Marie Svore, Maksims Volkovs, Christopher J...