Quantitative evaluation of passage retrieval algorithms for question answering 论文

摘要

Passage retrieval is an important component common to many question answering systems. Because most evaluations of question answering systems focus on end-to-end performance, comparison of common components becomes di#cult. To address this shortcoming, we present a quantitative evaluation of various passage retrieval algorithms for question answering, implemented in a framework called Pauchok. We present three important findings: Boolean querying schemes perform well in the question answering task. The performance di#erences between various passage retrieval algorithms vary with the choice of document retriever, which suggests significant interactions between document retrieval and passage retrieval. The best algorithms in our evaluation employ density-based measures for scoring query terms. Our results reveal future directions for passage retrieval and question answering.