Maksat Kalimoldayev, Atabay A. A. Ziyaden, Amir Yelenova, G. Mutanov, Zhanar Omirbekova, Gizat Abdykerova
{"title":"MAPPING THE SKIES: ANALYZING AEROSPACE INDUSTRY TRENDS USING EVENT MAPS","authors":"Maksat Kalimoldayev, Atabay A. A. Ziyaden, Amir Yelenova, G. Mutanov, Zhanar Omirbekova, Gizat Abdykerova","doi":"10.32523/2306-6172-2023-11-4-53-68","DOIUrl":null,"url":null,"abstract":"Accurate event extraction and analysis are vital for understanding trends and making informed decisions in various domains. This paper presents a concise rule-based approach for event extraction in the aerospace domain, aiming to enhance decision-making processes. The proposed methodology utilizes rule-based pattern-matching techniques to identify and extract events from textual data, such as news articles and research papers. By leveraging linguistic features and syntactic structures, the approach effectively captures event-related information. Additionally, an event map visualization technique is introduced to provide a comprehensive overview of the extracted events and their relationships. The proposed approach, integrated into the Aerospace Expert System (AES), offers a powerful tool for tracking and analyzing events in the aerospace industry. Evaluation results demonstrate the high precision and recall of the rule-based approach, enabling stakeholders to gain valuable insights and make informed decisions in the aerospace domain.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32523/2306-6172-2023-11-4-53-68","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
Accurate event extraction and analysis are vital for understanding trends and making informed decisions in various domains. This paper presents a concise rule-based approach for event extraction in the aerospace domain, aiming to enhance decision-making processes. The proposed methodology utilizes rule-based pattern-matching techniques to identify and extract events from textual data, such as news articles and research papers. By leveraging linguistic features and syntactic structures, the approach effectively captures event-related information. Additionally, an event map visualization technique is introduced to provide a comprehensive overview of the extracted events and their relationships. The proposed approach, integrated into the Aerospace Expert System (AES), offers a powerful tool for tracking and analyzing events in the aerospace industry. Evaluation results demonstrate the high precision and recall of the rule-based approach, enabling stakeholders to gain valuable insights and make informed decisions in the aerospace domain.