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

  • Han NiEmail author
  • Liansheng Lin
  • Ge Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11109)


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.


Question answer Knowledge base Entity linking Relation ranking 


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.NetDragon Websoft Inc.FuzhouChina
  2. 2.NetDragon Websoft Inc.FuzhouChina
  3. 3.Minjiang UniversityFuzhouChina

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