曹明宇,李青青,杨志豪,王磊,张音,林鸿飞,王健. 基于知识图谱的原发性肝癌知识问答系统[J]. 中文信息学报, 2019, 33(6): 88-93.
CAO Mingyu, LI Qingqing, YANG Zhihao, WANG Lei, ZHANG Yin, LIN Hongfei, WANG Jian. A Question Answering System for Primary Liver Cancer Based on Knowledge Graph. , 2019, 33(6): 88-93.
A Question Answering System for Primary Liver Cancer Based on Knowledge Graph
CAO Mingyu1, LI Qingqing1, YANG Zhihao1, WANG Lei2, ZHANG Yin2, LIN Hongfei1, WANG Jian1
1.Dalian University of Technology, School of Computer Science and Technology, Dalian, Liaoning 116024, China; 2.Beijing Institute of Health Administration and Medical Information, Beijing 100850, China
Abstract：The question answering (QA) system based on medical KB has important research and application significance. Aimed at the primary liver cancer common in adults, this paper extracts related knowledge triples from the medical guides and SemMedDB to construct a KB of primary liver cancer. On this basis, a pipeline QA system is implemented. Firstly the system identifies the entity from the question. Then the sentence embedding is generated by combining TFIDF and the word embedding to select the most similar problem template. Finally the system retrieves the answer from the KB according to the semantics of the template and the entity in the question. The results show that, this system can effectively answer questions about drugs, diseases and symptoms related to primary liver cancer.
[1] AMIT S.Introducing the knowledge graph、Things,not strings.[EB/OL].(2012-12-4).http://googleblog.blogspot.be/2012/05/introducing-knowledeg-graph-things- not.html. [2] 漆桂林,高桓,吴天星.知识图谱研究进展[J].情报工程,2017,3(1):4-25. [3] Forner A,Llovet J M,Bruix J.Hepatocellular carcinoma[J].Lancet,2012,379(9822):1245-1255. [4] 杜泽宇,杨燕,贺樑,等.基于中文知识图谱的电商领域问答系统[J].计算机应用与软件,2017(5):153-159. [5] Rindflesch T C,Kilicoglu H,Fiszman M,et al.Semantic MEDLINE:An advanced information management application for biomedicine[J].Information Services & Use,2011,31(1-2):15-21. [6] 徐增林,盛泳潘,贺丽荣,等.知识图谱技术综述[J].电子科技大学学报,2016,45(4):589-606. [7] Huang Z,Xu W,Yu K.Bidirectional LSTM-CRF models for sequence tagging[J].arXiv Dreprine arXiv:1508.01991,2015. [8] Gers F A,Schmidhuber J,Cummins F.Learning to Forget:Continual Prediction with LSTM[J].Neural Computation,2000,12(10):2451-24671. [9] Unger C,Lehmann J,Ngomo A C N,et al.Template-based question answering over RDF data[C]//Proceedings of the 21st International Conference on World Wide Web,2012:639-648. [10] Lukovnikov D,Fischer A,Lehmann J.Neural network-based question answering over knowledge graphs on word and character level[C]//Proceedings of the 21st International Conference on World Wide Web.International World Wide Web Conferences Steering Committee,2017:1211-1220. [11] Joachims T.A Probabilistic analysis of the rocchio algorithm with TFIDF for text categorization[C]//Proceedings of the ktth International Conference on Machine Learning,1996:143-151. [12] Mikolov T,Sutskever I,Chen K,et al.Distributed representations of words and phrases and their compositionality[J].Advances in Neural Information Processing Systems,2013,26:3111-3119.
2019, Vol. 33 
