Domain-Specific Event Graph Construction Methods：A Review
Wang Yi1,Shen Zhe1,Yao Yifan1,Cheng Ying1,2()
1School of Information Management, Nanjing University, Nanjing 210023, China 2School of Chinese Language and Literature, Shandong Normal University, Jinan 250014, China
[Objective] This paper reviews construction methods for domain-specific event graphs, aiming to facilitate future research.[Coverage] We searched “Event Graph”, “Event extraction” and “Event relation” with Web of Science and Google Scholar, then retrieved a total of 61 representative literature.[Methods] We summarized the definition, construction process and extraction methods with literature review. Then, we discussed the rule-based, feature learning based, and neural network-based extraction techniques. Finally, we analyzed their feature selection procedures, model architecture and experiment results.[Results] Refer to the general knowledge graph construction methods, we proposed a process model that include trigger argument and relation recognition. We briefly described on construction standard in structure, domain, event form, inference ability and temporal relations. In practice, we found that Ontology reuse is necessary, and neural network is the best choice.[Limitations] We did not use the same dataset to evaluate all methods.[Conclusions] We proposed knowledge-boosted methods, transfer learning and cognitive models for future studies.
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