预测分析系统:人工智能缉毒技术的案例研究

M. Abramson, S. Bennett, W. Brooks, E. Hofmann, P. Krause, A. Temin
{"title":"预测分析系统:人工智能缉毒技术的案例研究","authors":"M. Abramson, S. Bennett, W. Brooks, E. Hofmann, P. Krause, A. Temin","doi":"10.1109/CAIA.1994.323682","DOIUrl":null,"url":null,"abstract":"The Predictive Analysis System (PANS) uses knowledge of narco-trafficking behaviors to help analysts fuse all-source data into coherent pictures of activity from which predictions of future events can be made automatically. The system uses a form of model-based reasoning, plan recognition, to match reports of actual activities to expected activities. The model incorporates several sets of domain constraints and a constraint propagation algorithm is used to project known data points into the future (i.e., predict future events). The system can track many possibilities concurrently, and also allows analysts to hypothesize activity and observe the possible effect of the hypotheses on future activities. It makes use of recent results in knowledge representation, plan recognition, and machine learning to capture analysts' expertise without suffering from the brittleness of rule-based expert systems.<<ETX>>","PeriodicalId":297396,"journal":{"name":"Proceedings of the Tenth Conference on Artificial Intelligence for Applications","volume":"131 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Predictive Analysis System: a case study of AI techniques for counternarcotics\",\"authors\":\"M. Abramson, S. Bennett, W. Brooks, E. Hofmann, P. Krause, A. Temin\",\"doi\":\"10.1109/CAIA.1994.323682\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Predictive Analysis System (PANS) uses knowledge of narco-trafficking behaviors to help analysts fuse all-source data into coherent pictures of activity from which predictions of future events can be made automatically. The system uses a form of model-based reasoning, plan recognition, to match reports of actual activities to expected activities. The model incorporates several sets of domain constraints and a constraint propagation algorithm is used to project known data points into the future (i.e., predict future events). The system can track many possibilities concurrently, and also allows analysts to hypothesize activity and observe the possible effect of the hypotheses on future activities. It makes use of recent results in knowledge representation, plan recognition, and machine learning to capture analysts' expertise without suffering from the brittleness of rule-based expert systems.<<ETX>>\",\"PeriodicalId\":297396,\"journal\":{\"name\":\"Proceedings of the Tenth Conference on Artificial Intelligence for Applications\",\"volume\":\"131 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Tenth Conference on Artificial Intelligence for Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAIA.1994.323682\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Tenth Conference on Artificial Intelligence for Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAIA.1994.323682","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

预测分析系统(PANS)利用对毒品贩运行为的了解,帮助分析人员将所有来源的数据融合成连贯的活动图像,从而可以自动预测未来的事件。该系统使用一种基于模型的推理、计划识别的形式,将实际活动的报告与预期活动相匹配。该模型结合了几组领域约束,并使用约束传播算法将已知数据点投影到未来(即预测未来事件)。该系统可以同时跟踪许多可能性,还允许分析人员对活动进行假设,并观察假设对未来活动的可能影响。它利用知识表示、计划识别和机器学习方面的最新成果来获取分析师的专业知识,而不会受到基于规则的专家系统的脆弱性的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Predictive Analysis System: a case study of AI techniques for counternarcotics
The Predictive Analysis System (PANS) uses knowledge of narco-trafficking behaviors to help analysts fuse all-source data into coherent pictures of activity from which predictions of future events can be made automatically. The system uses a form of model-based reasoning, plan recognition, to match reports of actual activities to expected activities. The model incorporates several sets of domain constraints and a constraint propagation algorithm is used to project known data points into the future (i.e., predict future events). The system can track many possibilities concurrently, and also allows analysts to hypothesize activity and observe the possible effect of the hypotheses on future activities. It makes use of recent results in knowledge representation, plan recognition, and machine learning to capture analysts' expertise without suffering from the brittleness of rule-based expert systems.<>
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
OaSiS: integrating safety reasoning for decision support in oncology Memory-based parsing with parallel marker-passing A study of an expert system for interpreting human walking disorders Integrating case-based reasoning, knowledge-based approach and Dijkstra algorithm for route finding Learning control knowledge through cases in schedule optimization problems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1