Impacts of geographical knowledge, spatial ability and environmental cognition on image searches supported by GIS software

Google Earth search function was used to study the impacts of small-scale spatial ability, large-scale environmental cognition, and geographical knowledge on new technology usage. The participants were 153 junior high students from central Taiwan. Geography grades served as indicators of prior knowledge, mental rotation and abstract reasoning skills as indicators of spatial ability, and sketch maps of school neighborhoods as indicators of environmental cognition (including landmark representation, intersection representation, and frame of reference). Lastly, the authors announced the landmarks searching worksheet and asked the participants to accomplish 16 familiar and unfamiliar landmark searching tasks using Google Earth with keyword search function disabled. The result showed the strongest predictor of landmark searching performance is ‘frame of reference’ in environmental cognition, followed by ‘mental rotation’ of spatial ability, ‘landmark representation’ of environmental cognition, and geographical knowledge. Google Earth landmark searches require complex cognitive processing; therefore, our conclusion is that GIS-supported image search activities give students good practice of active knowledge construction.     

快速动态优先搜索树的实现及其应用

对形如（x1：x2,[-∞：y]）的二维查询问题,提出一种快速的、易于实现的动态优先搜索树数据结构及其相关算法,采用只在叶节点存储数据的结构,以及在常数时间内实现旋转操作的算法。设n为数据点的个数,k为满足搜索条件的解的个数,则该动态搜索树空间复杂度为O（n）,插入、删除操作的时间复杂度为O（10gn）,搜索复杂度为O（logn＋k）。     

消费者在线评论有用性影响因素模型研究

消费者在线评论的价值已经得到消费者和在线零售商的公认,对评论有用性的研究已经成为新的研究热点。从减少消费者决策风险出发,在感知诊断性概念基础上定义了评论有用性概念,构建了一个评论有用性影响因素模型。从传播说服理论的维度考察,评论等级、评论长度、好评率和使用互联网经验是影响评论有用性的重要因素。商品类型对评论有用性具有调节作用。     

主题搜索引擎中网络蜘蛛搜索策略的研究

主题网络蜘蛛的搜索策略是主题搜索引擎的核心部分,是近年来主题搜索引擎研究中的热点问题之一。深入研究了主题网络蜘蛛的关键技术,阐述了多线程网络蜘蛛的实现过程,并对传统的VSM算法和PageRank算法进行了改进,提高了主题网络蜘蛛采集信息的有效性和准确性。     

Computer chess move-ordering schemes using move influence

The chessmaps heuristic is a pattern-oriented approach to ordering moves for the game of chess. It uses a neural network to learn a relation between the control of the squares and the influence of a move. Depending on what squares a player controls, the chessmaps heuristic tries to determine where the important areas of the chessboard are. Moves that influence these important areas are then ordered first. The heuristic has been incorporated into a move-ordering algorithm that also takes account of immediate tactical threats. Human players also rely strongly on patterns when selecting moves, but would also consider immediate tactical threats, so this move-ordering algorithm is an attempt to mimic something of the human thought process when selecting a move. This paper presents a new definition for the influence of a move, which improves the performance of the heuristic. It also presents a new experience-based approach to determining what areas of the chessboard are important, which may actually be preferred to the chessmaps heuristic. The results from game-tree searches suggest that the move-ordering algorithm could compete with the current best alternative of using the history heuristic with capture moves in a brute-force search.     

浅析基于Lucene框架的网络论坛信息分析与实现

在当今互联网的各大论坛,帖吧,个人空间,BLOG中存在着非常多的网友发布的薪水,职业,等方面的信息。如在各大高校的BBS中,每年到应届生加入求职大军时,相当一部分学生会就各公司的薪水状况,福利待遇进行询问以及讨论,而一部分得到公司职位的学生亦会在一定程度上公布公司的薪水待遇状况。这一类各公司的薪水信息,对于以后学生的求职,职业人士跳槽,具有相当的参考价值。同样,在各大论坛,互动社区中,都会有相当大的薪水信息帖。很不幸的是,这些薪水讨论帖子淹没在浩淼的互联网中,并且通过互联网在大陆近十年来发展积淀,此类信息已经达到了海量。利用成熟的Lucene框架,文本检索理论(Information Retrieve),以及相关的分词,归类,索引技术,将这些信息,按照网友提交的关键字进行抽取与分析。按网友需要搜索出具备参考价值的职业信息。为网友的求职,跳槽,提供决策支持。     

Web2.0环境下的网络信息检索研究

Web2.0网站在现有网站中的比例越来越高,其具有的互动性、提倡个人体验等特点给信息搜索带来了新的挑战。该文分析了Web2.0的特点,指出Web2.0的某些特点会导致很多信息隐蔽化,并从隐蔽信息检索的角度尝试性地提出了解决办法。     

非结构化对等网络资源定位机制研究

非结构化对等网络是当今P2P的主流,资源搜索定位机制是其核心问题,Gnutella为代表的非结构化对等网络采用基于BFS和DFS的定位机制。在分析非结构化对等网络特征的基础上,提出了改进搜索定位机制的思路和方法。     

整合开源工具的小型搜索引擎构建

在介绍了搜索引擎基本原理和构架的基础上,提出了一种整合Larbin、Lucene、ICATLAS等多种开源工具快速构建小型搜索引擎的实验方案。实验表明,该引擎能有效完成网页的采集、处理、索引和检索等工作。