通过特定的改进，直方图也可应用到时空查询优化中。
Histogram can also be used in spatiotemporal query optimization after some improvements.
应用这个模型实现了对地名数据库的编辑更新及时空查询操作。
The application of the model can realize editing, updating and spatial-temporal querying of the place name database.
运动趋势的准确预测是实现移动对象数据库中各种预测性时空查询处理的基础。
Accurate predicting the movement trend is the fundamental issue for processing many kinds of predictive queries in moving objects database.
提出了基于属性簇的时空数据聚集查询算法。
In this paper, based-on attribute-cluster, a new spatiotemporal data aggregation query algorithm is proposed.
系统具备了对数据的浏览、查询、复制、输出以及增加、删减、修改、更新等功能，还能对数据进行时空分析。
It can realize not only the data manipulating functions such as browsing, query, copy, output, adding, deletion, modification and renewing, but also spatiotemporal analysis.
本文在基态修正模型的基础上，对时空数据更新和查询的方法进行探讨。
In this paper, the author studied the methods of spatiotemporal data updating and query on the basis of base state with amendments model.
连续近邻查询(CNN)是时空数据库中一种重要的查询类型。
Continuous nearest neighbors (CNN) inquiry is important in spatial-temporal database.
利用时空数据集的单点查询方法，组成了一种比较朴素的时空连接的算法。
The contributions of this paper are as the followings:(1) A simple spatial join algorithm is constructed by the single point query for spatiotemporal datasets.
但对于不同的时空数据模型，时空数据更新处理和查询的方法存在很大差异。
However, for different spatiotemporal data models, there is a big difference on spatiotemporal data updating and query approaches.
利用时空索引结构的特点，应用距离度量来减小平均磁盘访问量是查询处理常用的方法。
Making use of the structure of st indices, and applying distance metrics to decrease average disk access count is the most popular method in st query processing.
预测性连续时空区域查询在用户指定的时间范围期间持续地返回给定未来查询时间范围期间将出现在查询区域的移动对象。
In a user defined time interval, the predictive continuous range query continuously returns moving objects that will appear in a spatial query range during a future temporal query interval.
预测性连续时空区域查询在用户指定的时间范围期间持续地返回给定未来查询时间范围期间将出现在查询区域的移动对象。
In a user defined time interval, the predictive continuous range query continuously returns moving objects that will appear in a spatial query range during a future temporal query interval.
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