IMU Experiment in IR4QA at NTCIR-8
نویسندگان
چکیده
This paper describes our work in the subtask IR4QA. Our IR system designed for this task consists of two modules: (1) query processing; (2) indexing, retrieval and re-rank. We first study the method of question classification, and the strategies of weighting based on the result of question classification. Baidu and Wanfang resources are exploited to help query expansion. Through studying the specialty of each index formats and each index unit, we create three indexes of different types: KeyFile-UnigramIndex, KeyFile-Word-Index and Indri-Word-Index. Then we use an interpolating method to re-rank the documents returned from the above three indexes. Our system achieved 0.4266 mean AP, 0.4628 mean Q and 0.6761 mean nDCG in the final evaluation, giving a strong proof of the effectiveness of our approach.
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