State-of-the-art question answering (QA) systems employ termdensity ranking to retrieve answer passages. Such methods often retrieve incorrect passages as relationships among ques...
Hang Cui, Renxu Sun, Keya Li, Min-Yen Kan, Tat-Sen...
This paper describes a framework for defining domain specific Feature Functions in a user friendly form to be used in a Maximum Entropy Markov Model (MEMM) for the Named Entity Re...
We examine the problem of retrieving the top-m ranked items from a large collection, randomly distributed across an n-node system. In order to retrieve the top m overall, we must ...
We present a strategy for answering fact-based natural language questions that is guided by a characterization of realworld user queries. Our approach, implemented in a system cal...
In this paper, we introduce the notion of ranking robustness, which refers to a property of a ranked list of documents that indicates how stable the ranking is in the presence of ...