paper, we describe our system implemented for the NTCIR-8 CCLQA task. The system consists of a question translation model and a general question answering system for both factoid and complex questions. The translation model combines a translation engine and an online dictionary, which can provide more accurate translations of named entities in the questions. With regard to the question answering system, a PLSA based approach is introduced for answer sentence acquisition. For answer ranking, our system expands the question set by summarizing relevant sentences from a web knowledge base and leverages both semantic and statistical information of questions. In the official evaluation results, our system achieves 18.41% F- score in English to Chinese subtask and 25.66% in monolingual Chinese subtask.
['Han Ren', 'Donghong Ji', 'Jing Wan']
WHU Question Answering System at NTCIR-8 ACLIA Task