In this paper we report on our natural language information retrieval (NLIR) project as related to the recently concluded 5th Text Retrieval Conference (TREC-5). The main thrust o...
Tomek Strzalkowski, Fang Lin, Jose Perez Carballo,...
Long-term search history contains rich information about a user's search preferences. In this paper, we study statistical language modeling based methods to mine contextual i...
As web search providers seek to improve both relevance and response times, they are challenged by the ever-increasing tax of automated search query traffic. Third party systems in...
Gregory Buehrer, Jack W. Stokes, Kumar Chellapilla
Children want to find information about their world, but there are barriers to finding what they seek. Young people have varying abilities to formulate complex queries and compreh...
Allison Druin, Elizabeth Foss, Hilary Hutchinson, ...
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 ...