{"title":"使用基于黑板的推理代理进行预测分析","authors":"Jia Yue, A. Raja, W. Ribarsky","doi":"10.1109/WI-IAT.2010.155","DOIUrl":null,"url":null,"abstract":"Significant increase in collected data for investigative tasks and the increased complexity of the reasoning process itself have made investigative analytical tasks more challenging. These tasks are time critical and typically involve identifying and tracking multiple hypotheses; gathering evidence to validate the correct hypotheses and eliminating the incorrect ones. In this paper we specifically address predictive tasks that are concerned with predicting future trends. We describe RESIN, an AI blackboard-based agent that leverages interactive visualizations and mixed-initiative problem solving to enable analysts to explore and pre-process large amounts of data in order to perform predictive analytics. Our empirical evaluation discusses the advantages and challenges of predictive analytics in a complex domain like intelligence analysis.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Predictive Analytics Using a Blackboard-Based Reasoning Agent\",\"authors\":\"Jia Yue, A. Raja, W. Ribarsky\",\"doi\":\"10.1109/WI-IAT.2010.155\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Significant increase in collected data for investigative tasks and the increased complexity of the reasoning process itself have made investigative analytical tasks more challenging. These tasks are time critical and typically involve identifying and tracking multiple hypotheses; gathering evidence to validate the correct hypotheses and eliminating the incorrect ones. In this paper we specifically address predictive tasks that are concerned with predicting future trends. We describe RESIN, an AI blackboard-based agent that leverages interactive visualizations and mixed-initiative problem solving to enable analysts to explore and pre-process large amounts of data in order to perform predictive analytics. Our empirical evaluation discusses the advantages and challenges of predictive analytics in a complex domain like intelligence analysis.\",\"PeriodicalId\":340211,\"journal\":{\"name\":\"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WI-IAT.2010.155\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI-IAT.2010.155","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictive Analytics Using a Blackboard-Based Reasoning Agent
Significant increase in collected data for investigative tasks and the increased complexity of the reasoning process itself have made investigative analytical tasks more challenging. These tasks are time critical and typically involve identifying and tracking multiple hypotheses; gathering evidence to validate the correct hypotheses and eliminating the incorrect ones. In this paper we specifically address predictive tasks that are concerned with predicting future trends. We describe RESIN, an AI blackboard-based agent that leverages interactive visualizations and mixed-initiative problem solving to enable analysts to explore and pre-process large amounts of data in order to perform predictive analytics. Our empirical evaluation discusses the advantages and challenges of predictive analytics in a complex domain like intelligence analysis.