文本信息中的目标动向感知技术

Target Activity Awareness on Text Information

通过建立目标动向的本体模型以及采用基于规则的方式来对文本信息中的目标动向描述语句进行语义分析,完成目标动向的识别和关联语义信息抽取;在提取大量的文本信息中的目标动向信息上建立目标与时空的关联关系,有利于文字信息分析人员感知目标在时空范围内的态势。通过对目标的动向信息抽取和结构化的关联关系转化及分析,可以为情报分析人员提供锁定目标的态势数据,并通过目标动向情况预测锁定目标的活动趋势、预警分析等。

The dissertation mainly discusses semantic analysis of target activity description sentences in text information by establishing ontology model of target activity in accordance with rule-based technologies to realize recognition of target activity and relational semantic information extraction. On the basis of success-ful extraction of target activity information from a huge amount of data for establishing relations between tar-get and time-space, it is advantageous for text information analyzers to sense the situation of the target in the time-space domain. By extraction of target activity information, conversion and analysis of structural relationships, it is possible for intelligence analyzers to obtain situation data sufficient to lock down their target, and predict or early warn target activity trends by correspondent historical target activities.