{"title":"Rule-Based Attractions Describe Paragraph Information Extraction","authors":"Xiaolan Feng, Xiaobing Zhao Zhao","doi":"10.1109/ICRIS.2018.00103","DOIUrl":null,"url":null,"abstract":"In this paper, a rule-based information extraction method of descriptive paragraphs of scenic spots is proposed. While paying attention to the location information of scenic spots, it extracts brief and general descriptive paragraphs of scenic spots which are taken as descriptive texts of scenic spots, which is of academic reference value for textual information extraction beyond the current entity triple. The experiments are conducted respectively from perspective of the location relation, the affiliation, and the relation of creation of time. When only considering the location relation and rules of the affiliation, the accuracy rate is 90.85%, the recall rate is 85.43%, and the F value is 88.06%. So the validity and applicability of this method are proved.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Robots & Intelligent System (ICRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRIS.2018.00103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a rule-based information extraction method of descriptive paragraphs of scenic spots is proposed. While paying attention to the location information of scenic spots, it extracts brief and general descriptive paragraphs of scenic spots which are taken as descriptive texts of scenic spots, which is of academic reference value for textual information extraction beyond the current entity triple. The experiments are conducted respectively from perspective of the location relation, the affiliation, and the relation of creation of time. When only considering the location relation and rules of the affiliation, the accuracy rate is 90.85%, the recall rate is 85.43%, and the F value is 88.06%. So the validity and applicability of this method are proved.