[1]LUO Ling,LI Shuokai,HE Qing,et al.Winter Olympic Q & A system based on knowledge map, TF-IDF and BERT model[J].CAAI Transactions on Intelligent Systems,2021,16(4):819-826.[doi:10.11992/tis.202105047]
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Winter Olympic Q & A system based on knowledge map, TF-IDF and BERT model

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 16 Number of periods: 2021 4 Page number: 819-826 Column: 吴文俊人工智能科学技术奖论坛 Public date: 2021-07-05
Title:
Winter Olympic Q & A system based on knowledge map, TF-IDF and BERT model
Author(s):
LUO Ling1; 2;  LI Shuokai1; 2;  HE Qing1; 2;  YANG Chengqi2;  WANG Yuyangheng2;  CHEN Tianyu2
1. Key Lab of Intelligent Information Processing, Institute of Computing Technology of Chinese Academy of Sciences, Beijing 100190, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China
Keywords:
Intelligent Q &;  A; Winter Olympics Q &;  A; dialogue model; knowledge map; TF-IDF; BERT
CLC:
TP391
DOI:
10.11992/tis.202105047
Abstract:
With the advent of the information age, traditional information retrieval technology can no longer meet people’s requirements for the efficiency in information acquisition, so intelligent question answering systems are proposed and have become a very important research hotspot in natural language processing. This paper proposes three Winter Olympics Q&A system models based on knowledge graph, TFIDF and BERT for the Chinese Winter Olympics Q&A, constructing the Winter Olympics Q&A data set for the first time and integrating the above three methods into the Winter Olympics Q&A. Users can use this system to quickly and accurately obtain the Q&A knowledge related to the Winter Olympics content. Furthermore, this paper evaluates the effects of the three models and measures the acceptance rate of each model. The experimental results show that overall the BERT model is slightly better than the knowledge graph and TDIDF model. The acceptance rate of the BERT model for each of the three types of questions exceeds 96%. The knowledge graph and TDIDF model are not so effective as the BERT model for the answer to the composite statistical question and answer pair.
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