tailieunhanh - Báo cáo khoa học: "Language-independent Probabilistic Answer Ranking for Question Answering"

This paper presents a language-independent probabilistic answer ranking framework for question answering. The framework estimates the probability of an individual answer candidate given the degree of answer relevance and the amount of supporting evidence provided in the set of answer candidates for the question. Our approach was evaluated by comparing the candidate answer sets generated by Chinese and Japanese answer extractors with the re-ranked answer sets produced by the answer ranking framework. . | Language-independent Probabilistic Answer Ranking for Question Answering Jeongwoo Ko Teruko Mitamura Eric Nyberg Language Technologies Institute School of Computer Science Carnegie Mellon University jko teruko ehn @ Abstract This paper presents a language-independent probabilistic answer ranking framework for question answering. The framework estimates the probability of an individual answer candidate given the degree of answer relevance and the amount of supporting evidence provided in the set of answer candidates for the question. Our approach was evaluated by comparing the candidate answer sets generated by Chinese and Japanese answer extractors with the re-ranked answer sets produced by the answer ranking framework. Empirical results from testing on NT-CIR factoid questions show a 40 performance improvement in Chinese answer selection and a 45 improvement in Japanese answer selection. 1 Introduction Question answering QA systems aim at finding precise answers to natural language questions from large document collections. Typical QA systems Prager et al. 2000 Clarke et al. 2001 Harabagiu et al. 2000 adopt a pipeline architecture that incorporates four major steps 1 question analysis 2 document retrieval 3 answer extraction and 4 answer selection. Question analysis is a process which analyzes a question and produces a list of keywords. Document retrieval is a step that searches for relevant documents or passages. Answer extraction extracts a list of answer candidates from the retrieved documents. Answer selection is a 784 process which pinpoints correct answer s from the extracted candidate answers. Since the first three steps in the QA pipeline may produce erroneous outputs the final answer selection step often entails identifying correct answer s amongst many incorrect ones. For example given the question Which Chinese city has the largest number of foreign financial companies the answer extraction component produces a ranked list of five answer .