随着对语言文字信息处理研究工作的不断加深,藏文信息处理技术也逐渐从字信息处理走向了语言信息处理。跟日语、汉语、韩语等语种的信息处理相同,藏文自动分词(Tibetan Automatic Word Segmentation)是藏文信息处理中的一项必不可少的基础性工作,在此基础上才能划分短语、抽取概念以及分析主题,以至自然语言理解,最终实现智能化。对于不同应用环境,藏文自动分词需要采用最合适的算法,本文通过对藏语语料的统计分析和藏语词的分布特点、语法功能的研究,提出了设计开发基于词典库的藏文自动分词系统,力求为藏文输入法研究、藏文电子词典建设、藏文字词频统计、搜索引擎的设计和实现、机器翻译系统的开发、网络信息安全、藏文语料库建设以及藏语语义分析研究奠定基础。
Emerging technologies of wireless and mobile communication enable people to accumulate a large volume of time-stamped locations,which appear in the form of a continuous moving object trajectory.How to accurately predict the uncertain mobility of objects becomes an important and challenging problem.Existing algorithms for trajectory prediction in moving objects databases mainly focus on identifying frequent trajectory patterns,and do not take account of the effect of essential dynamic environmental factors.In this study,a general schema for predicting uncertain trajectories of moving objects with dynamic environment awareness is presented,and the key techniques in trajectory prediction arc addressed in detail.In order to accurately predict the trajectories,a trajectory prediction algorithm based on continuous time Bayesian networks（CTBNs） is improved and applied,which takes dynamic environmental factors into full consideration.Experiments conducted on synthetic trajectory data verify the effectiveness of the improved algorithm,which also guarantees the time performance as well.
Shaojie QIAOXian WANGLu＇an TANGLiangxu LIUXun GONG
