搜索引擎的发展概况与趋势

搜索引擎是随着网上信息不断丰富应运而生的一种检索工具。1994年,Internet上诞生了第一个搜索引擎W ebCraw ler,通过对网页做索引来提供检索服务。2000年,Google的出现使搜索引擎市场发生了新的变化。近年来,中文搜索引擎的发展快,数量多。搜索引擎的发展有以下趋势:数据库小型化,专业化;强化全文检索功能;检索智能化、服务个性化;语种多样化;元搜索引擎的发展;搜索服务等。     

试论少数民族与贫困地区教师培训系统的建立——以海南师范大学“周末流动师资培训学院”为例

建立科学完备的少数民族与贫困地区教师培训系统是提高当地教师队伍素质,促进义务教育均衡发展的重要任务。本章从培训系统的角度,指出了目前少数民族与贫困地区教师培训系统中培训队伍、培训模式、培训制度和机制存在的问题,针对存在的问题,结合海南师范大学实施“周末流动师资培训学院”的实践,讨论了少数民族与贫困地区教师培训系统的重构和创新。     

基于Windows Phone平台的手机校园GIS系统设计方案

从探讨未来智慧校园移动端GIS产品的角度考量,利用云计算技术,以Microsoft Visual Studio 2010为开发平台,采用C#语言为开发语言,以ArcGIS Server 10为GIS服务端,设计开发了Windows Phone手机移动端的手机校园GIS系统。整个系统主要由校园新闻模块、课程安排模块、地图查询模块、我的日记模块、最近天气模块组成,能够起到使用手机小软件方便安排校园生活的目的,研发过程是对智能校园的一次很有意义的探索和尝试。     

在线语言学习的发展与前景

在线语言学习作为外语学习的一种趋势,扩大了学生对教师、对课程、对时空的选择范围,这种不同于传统授课模式的学习方式受到大家的广泛关注。对在线语言学习的发展进行了简要的介绍,并对时下流行的在线学习方式（包括在线语言学习教程、语言学习智能系统、语言学习游戏、移动语言学习和网络沟通五个方面）逐一进行了说明。     

基于星策略体系的移动教学平台设计

为了使云服务更好的运用于移动教学,提出星策略体系理论。星策略体系由星系设计、星系教学策略及教学活动设计三部分组成。由课堂教学与移动教学的关系及云服务的现状弓l出星策略体系理论,研究在教学中如何应用星策略及云服务,基于星策略体系理论的指导设计了移动教学平台,以期更好地为教学服务。     

智能搜索引擎与数字图书馆个性化服务

智能搜索引擎基于知识(概念)层面实行信息检索，以较强的自然语言理解和知识处理能力，表现出良好的个性化信息服务特色。因此，智能搜索引擎应用于数字图书馆个性化服务体系，不仅有效发挥前者数据挖掘、知识发现的功能，同时能较大地加深后者的主动性、智能性优势。     

A heuristic hierarchical scheme for academic search and retrieval

We present PubSearch, a hybrid heuristic scheme for re-ranking academic papers retrieved from standard digital libraries such as the ACM Portal. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. We designed and developed a meta-search engine that submits user queries to standard digital repositories of academic publications and re-ranks the repository results using the hierarchical heuristic scheme. We evaluate our proposed re-ranking scheme via user feedback against the results of ACM Portal on a total of 58 different user queries specified from 15 different users. The results show that our proposed scheme significantly outperforms ACM Portal in terms of retrieval precision as measured by most common metrics in Information Retrieval including Normalized Discounted Cumulative Gain (NDCG), Expected Reciprocal Rank (ERR) as well as a newly introduced lexicographic rule (LEX) of ranking search results. In particular, PubSearch outperforms ACM Portal by more than 77% in terms of ERR, by more than 11% in terms of NDCG, and by more than 907.5% in terms of LEX. We also re-rank the top-10 results of a subset of the original 58 user queries produced by Google Scholar, Microsoft Academic Search, and ArnetMiner; the results show that PubSearch compares very well against these search engines as well. The proposed scheme can be easily plugged in any existing search engine for retrieval of academic publications.     

基于云计算的高校与农村文献信息资源共享平台的设计与实现

针对农村文献信息资源个性化服务的需求,利用云计算的强大优势,以移动通讯网络为信号传输方式,以高校图书馆文献信息资源为基础,搭建了一种基于云计算的高校与农村文献信息资源共享平台。将面对终端用户的应用服务与文献信息资源的数据处理分开,搭建两台服务器：云计算中心和移动终端服务器,所有的计算都由这2台服务器来完成。在1个农村、1所高校、1间云计算机房组成的实验对象上对这种基于云计算的农村与高校文献信息资源共享模式进行了小范围的验证。     

A study of results overlap and uniqueness among major Web search engines

The performance and capabilities of Web search engines is an important and significant area of research. Millions of people world wide use Web search engines very day. This paper reports the results of a major study examining the overlap among results retrieved by multiple Web search engines for a large set of more than 10,000 queries. Previous smaller studies have discussed a lack of overlap in results returned by Web search engines for the same queries. The goal of the current study was to conduct a large-scale study to measure the overlap of search results on the first result page (both non-sponsored and sponsored) across the four most popular Web search engines, at specific points in time using a large number of queries. The Web search engines included in the study were MSN Search, Google, Yahoo! and Ask Jeeves. Our study then compares these results with the first page results retrieved for the same queries by the metasearch engine Dogpile.com. Two sets of randomly selected user-entered queries, one set was 10,316 queries and the other 12,570 queries, from Infospace’s Dogpile.com search engine (the first set was from Dogpile, the second was from across the Infospace Network of search properties were submitted to the four single Web search engines). Findings show that the percent of total results unique to only one of the four Web search engines was 84.9%, shared by two of the three Web search engines was 11.4%, shared by three of the Web search engines was 2.6%, and shared by all four Web search engines was 1.1%. This small degree of overlap shows the significant difference in the way major Web search engines retrieve and rank results in response to given queries. Results point to the value of metasearch engines in Web retrieval to overcome the biases of individual search engines.     

搜索力经济研究

目前,由搜索引擎所引领的另类网络虚拟经济形态一“搜索力经济”正在迅速崛起。作为互联网新经济的核心价值,搜索力正引领着互联网的现在和未来。本文将对这一“热点区域”对“搜索力经济”的概念、出现原因及引发的变革等相关问题进行分析,帮助读者对互联网的新领域有更深刻的了解。