Automatic relationship extraction from agricultural text for ontology construction  

作　　者：Neha Kaushik Niladri Chatterjee 

机构地区：[1]Indian Institute of Technology Delhi,Hauz Khas,New Delhi 110016,India

出　　处：《Information Processing in Agriculture》2018年第1期60-73,共14页农业信息处理（英文）

摘　　要：In the present era of Big Data the demand for developing efficient information processing techniques for different applications is expanding steadily.One such possible application is automatic creation of ontology.Such an ontology is often found to be helpful for answering queries for the underlying domain.The present work proposes a scheme for designing an ontology for agriculture domain.The proposed scheme works in two steps.In the first step it uses domain-dependent regular expressions and natural language processing techniques for automatic extraction of vocabulary pertaining to agriculture domain.In the second step semantic relationships between the extracted terms and phrases are identified.A rulebased reasoning algorithm RelExOnt has been proposed for the said task.Human evaluation of the term extraction output yields precision and recall of 75.7%and 60%,respectively.The relation extraction algorithm,RelExOnt performs well with an average precision of 86.89%.

关 键 词：Relation extraction Term EXtraction NLP ONTOLOGY Knowledge-based relation EXTRACTION Self-supervised relation extraction 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]