A Relateness-Based Ranking Method for Knowledge-Based Question Answering

摘要：

　　In this paper,we report technique details of our approach for the NLPCC 2018 shared task knowledge-based question answering.Our system uses a word-based maximum matching method to find entity candidates.Then,we combine editor distance,character overlap and word2vec cosine similarity to rank SRO triples of each entity candidate.Finally,the object of the top 1 score SRO is selected as the answer of the question.The result of our system achieves 62.94%of answer exact matching on the test set.

关键词： Question answer Knowledge base Entity linking Relation ranking

作者: Han Ni Liansheng Lin Ge Xu

作者单位: NetDragon Websoft Inc.,Fuzhou,China Minjiang University,Fuzhou,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 393-400

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）