基于网格的国外搜索引擎系统的比较研究*

在详细介绍国外基于网格的搜索引擎系统的研究内容和研究方法的基础上，对这些项目的研究内容和方法进行系统的比较研究，并借鉴国外基于网格的搜索引擎系统的研究成果，对我国今后的研究方向提出建议。     

专题型搜索引擎用户分析

通过对专题型搜索引擎的用户进行问卷调查,基于调查结果的统计与分析,从用户的视角来考察和评价当前专题引擎的发展现状,并以此为依据,对专题引擎的发展提出建议。     

基于模式识别理论的内燃机状态识别研究

用模式识别的理论和方法，对内燃机气门间隙的识别问题进行了探讨。在分析气门振动力学模型的基础上，通过测取振动信号获得故障特征信息，用模式识别的理论和方法，在建立状态特征模式空间的基础上实现对故障的分类识别。考虑到内燃机振动信号的复杂性，采用了外触发采样和有效截取的方法进行信号的数据采集和分析。     

图书出版的搜索引擎营销策略

本文从出版社如何开展网络营销入手,引出搜索引擎营销这一利器,通过翔实、具体的例子阐明了出版社应该如何实施搜索引擎营销策略,详细介绍了搜索引擎导向的广告投放策略、搜索引擎导向的网站优化策略、搜索引擎导向的网站推广策略、搜索引擎导向的信息收集策略.     

搜索引擎返回结果自动抽取

提出一种从搜索引擎返回结果页面上自动抽取结果记录及后续页面链接信息并生成Wrapper的方法:对于一个有效的结果页面，通过比较其HTML标签树上节点的相似度从而识别出潜在记录块，利用启发式规则从潜在记录块中将结果记录块和后续页面链接分别识别出来，然后利用其在标签树上的位置信息分别构造Wrapper。实验结论及与已有方法的比较表明，该方法简单可行且高效。     

浅析数字图书馆检索工具及其功能

在信息化时代,数字图书馆的建立已是大势所趋.面对浩繁的网络信息资源,传统的人工标引方法已不适用.为此,数字图书馆的建设必须采用新的检索工具,引进搜索引擎技术,采用现代的自动标引和传统的人工标引相结合的方式整合网络信息资源.     

WWW检索工具比较研究

近年来,随着ＷＷＷ技术的广泛应用,使得Ｉｎｔｅｒｎｅｔ迅速发展。作为Ｉｎｔｅｒｎｅｔ网上的信息查找途径,ＷＷＷ检索站点已成为Ｉｎｔｅｒｎｅｔ网上最繁忙的站点之一。本文选取了Ｙａｈｏｏ、ＡｌｔａＶｉｓｔａ、Ｅｘｃｉｔｅ、ＨｏｔＢｏｔ、Ｉｎｆｏｓｅｋ、Ｌｙｃｏｓ、ＯｐｅｎＴｅｘｔ、ＷｅｂＣｒａｗｌｅｒ及ＭｅｔａＣｒａｗｌｅｒ等九个著名的ＷＷＷ检索工具,通过上网实验,分析比较各工具检索引擎的特点,并从用户角度指出检索引擎现阶段存在的问题。最后对开发我国的ＷＷＷ检索工具提出了建议     

SAGA：一种新的船舶搁浅预警模型

随着船舶自动识别系统(Automatic Identification System,AIS)和电子海图信息与显示系统(Electronic Chart Displayand Information System,ECDIS)的出现及普及,使船舶交通管理系统(Ves-sel Traffic Service,VTS)对其辖区的航行船舶进行自动搁浅预警成为可能.针对预警自动化水平较低这一现状,提出搁浅预警(Search Area for Grounding A lert,SAGA)模型,通过判断船舶SAGA领域内最小水深是否满足安全要求来实现船舶搁浅预警.     

基于鱼群的PSO粒子滤波算法

粒子群优化(PSO)粒子滤波算法比较而言,容易陷入局部最优,因此算法的准确度就会降低。本文在解决该问题时引入了一种基于鱼群的PSO粒子滤波算法。此算法是通过鱼群优化在采样过程中找到全局最优的相对位置,使其能够向全局最优的位置逐渐接近,同时提高估计有效的粒子数目,从而能够更有效的减少粒子退化与枯竭问题。实验表明,此算法与PSO粒子滤波算法相比,在估计准确度方面有了较大的提升。     

Learning assessments in search-as-learning: A survey of prior work and opportunities for future research

People often search for information in order to learn something new. In recent years, the “search-as-learning” movement has argued that search systems should be better designed to support learning. Current search systems (especially Web search engines) are largely designed and optimized to fulfill simple look-up tasks (e.g., navigational or fact-finding search tasks). However, they provide less support for searchers working on complex tasks that involve learning. Search-as-learning studies have investigated a wide range of research questions. For example, studies have aimed to better understand how characteristics of the individual searcher, the type of search task, and interactive features provided by the system can influence learning outcomes. Learning assessment is a key component in search-as-learning studies. Assessment materials are used to both gauge prior knowledge and measure learning during or after one or more search sessions. In this paper, we provide a systematic review of different types of assessments used in search-as-learning studies to date. The paper makes the following three contributions. First, we review different types of assessments used and discuss their potential benefits and drawbacks. Second, we review assessments used outside of search-as-learning, which may provide insights and opportunities for future research. Third, we provide recommendations for future research. Importantly, we argue that future studies should clearly define learning objectives and develop assessment materials that reliably capture the intended type of learning. For example, assessment materials should test a participant’s ability to engage with specific cognitive processes, which may range from simple (e.g., memorization) to more complex (e.g., critical and creative thinking). Additionally, we argue that future studies should consider two dimensions that are understudied in search-as-learning: long-term retention (i.e., being able to use what was learned in the long term) and transfer of learning (i.e., being able to use what was learned in a novel context).