一种有效的历史移动对象轨迹的k最近邻居查询算法

近10多年来,研究者们已经在k最近邻居(kNN)查询方面做了很多工作,但是对于移动对象轨迹的kNN查询处理却研究得很少.鉴于此,研究了在存储有历史移动对象轨迹信息的TB树结构上的kNN查询问题,并且提出了一种有效的基于最佳优先搜索范例的kNN(k≥1)查询算法,称为BFPkNN.BFPkNN是一种I/O最佳的算法,即它仅仅访问有可能包含最终结果的结点.同时,为了减少存储空间和CPU代价,又提出了若干有效的剪枝策略.大量的实验证明BFPkNN在效率和可扩展性上均大大胜过其他同类算法.     

利用语料库技术的中文自动文摘系统

本文着重介绍利用“后邻字符树”的方法在领域语料库中生成字符树库,用于自动文摘候选句子选取时提高精度,介绍了后邻字符树的构造、后邻字符树库的生成及优化和句子权值计算方法。     

公文流转中复杂工作流程的通用设计

该文针对传统办公自动化系统中公文流转的固定流程和流转复杂性的矛盾,提出了以动态流程为基础的复杂工作流程的通用设计方法.同时结合开发实例加以剖析,并展望了今后的发展前景.     

Java和JavaScript在Lotus Domino/Notes5.0开发中的应用

主要论述Ｊａｖａ和ＪａｖａＳｃｒｉｐｔ在Ｌｏｔｕｓ Ｄｅｍｉｎｏ／Ｎｏｔｅｓ５．０开发Ｗｅｂ应用中的一些技巧;讨论了Ｊａｖａ在Ｌｏｔｕｓ Ｄｏｍｉｎｏ／Ｎｏｔｅｓ５．０中的应用,并提供了一个Ｊａｖａ和ＪａｖａＳｃｒｉｐｔｅ相结合的应用实例。     

Efficient k-Nearest-Neighbor Search Algorithms for Historical Moving Object Trajectories

k Nearest Neighbor (kNN) search is one of the most important operations in spatial and spatio-temporal databases. Although it has received considerable attention in the database literature, there is little prior work on kNN retrieval for moving object trajectories. Motivated by this observation, this paper studies the problem of efficiently processing kNN (k≥1) search on R-tree-like structures storing historical information about moving object trajectories. Two algorithms are developed based on best-first traversal paradigm, called BFPkNN and BFTkNN, which handle the kNN retrieval with respect to the static query point and the moving query trajectory, respectively. Both algorithms minimize the number of node access, that is, they perform a single access only to those qualifying nodes that may contain the final result. Aiming at saving main-memory consumption and reducing CPU cost further, several effective pruning heuristics are also presented. Extensive experiments with synthetic and real datasets confirm that the proposed algorithms in this paper outperform their competitors significantly in both efficiency and scalability.     

基于生理信号的观众情感状态识别模型

为研究电影情节与观众生理信号变化的关系,提出基于生理信号的观众情感状态识别模型,从观众生理信号中提取特征,采用顺序前进法（SFS）进行特征选择,并基于支持向量机（SVM）建立观众情感状态识别模型.实验选择了不同类型的3部影片,共11名人员参加,在电影播放时拍摄观众表情并记录其生理信号,基于表情人工标注其情感状态.实验结果表明：该模型对各情感状态的区分较理想,平均识别率在90%以上.