信息检索中的相关性

讨论了信息检索中的相关性概念,通过分析美国学者Mizzaro的相关性框架,展示了信息检索过程中所包含的各种相关性以及它们之间的相互关系,探讨了用户相关性判断的影响因素。     

引文评价中的引文方式与力度因素

本文从引文内容、引文方式、引文深度及引文力度的角度分析不同引文对文献的支持作用。     

基于泛用型中文域名与关键词的生物学信息超链接技术实现

检索过程中，关键词灵活、易用，检索效率低。通过中文域名与关键词相结合技术对Web上生物学资源检索途径进行研究，通过泛域名解析技术、重定向技术和添加算法，实现生物学的站点、专题与网页的搜索技术。     

基于关键词标注的教学论坛内容组织方法研究

随着网络交互平台在教学活动中的普及,论坛、Blog等成为教学活动中实现知识分享的重要手段。然而,论坛和Blog中帖子的无序性、同类帖子之间缺乏联系等问题日益凸显,成为知识进一步共享的桎梏。因此,以分词和文本聚类的相关理论为指导,研究论坛帖子内容的内在联系,探索在教学平台上对帖子进行分词并通过关键词实现标注,进而把论坛中的所有帖子归纳到知识体系中,对于提高教学平台的服务质量,实现大范围的知识分享和建构具有重要意义。     

Keyword length and matching options as indicators of search intent in sponsored search

Sponsored search is an online advertising channel that has gained momentum worldwide. The key challenge is deciding on the types of keywords to bid on and matching options to utilise for the keywords. In this paper, we address this problem by providing a broad analysis on how the various traffic search metrics (length, CTR, average cost per click (CPC), average position, and quality score) influence the bidding results as the keyword matching option becomes broader, that is, from exact, to phrase to broad. Drawing on the shopping goals theory, we also establish the profile of the metrics associated with a more focused search intent across the matching options. Using a random sample of keywords selected from 9 640 keywords that online advertisers have bid on, spanning a variety of markets, the results indicate that as the matching option becomes narrower, that is, from broad to exact, the keyword traffic metrics increase in general, except for cost, which does not differ significantly across the matching options. Longer keywords, which are typically associated with a more focussed search intent, generate more clicks and have a higher quality measure on average across all matching options. The longer keywords are cheaper for the exact match option, but more expensive for the other matching options. The results are inconclusive with regard to the position that longer keywords occupy on a results page across the matching options. Thus, the narrower matching options and longer keywords matching those that a customer would typically use to search for a company's goods and services need to be targeted to ensure higher visits to a company's website.     

论我国图书馆文献信息资源检索工具的现状及发展趋势

从国内图书馆检索工具的演变谈其发展历程 ,并从文献信息资源组织的角度 ,论述检索工具的现状和发展趋势 ,指出目前检索工具的功能落后于文献组织功能 ;分类语言、主题语言与自然语言一体化的检索体系 ,将成为我国图书馆文献信息资源检索工具的发展趋势所在。图 1。参考文献 4     

十八大报告外交部分的解析

在党的十八大上,胡锦涛以"继续促进人类和平与发展的崇高事业"为主题,对当前的国际形势和中国外交部分做了精辟有力的论述。十八大报告的外交部分准确分析中国所处的国际环境,确定中国的身份和责任,并在此基础上指明中国新时期的外交理念和外交策略,勾画出中国外交战略的新蓝图,为正在稳步发展的中国指明了前进的方向。报告中还包含诸多的亮点和新提法,值得人们关注和深思。     

"公众知识分子"与"三个意义世界"

所谓“公众知识分子”是对一种新理想群体的定义 ,它的提出和建构有着深刻的时代背景 ,这就是所谓“三个意义世界”之所指。当代海外的新儒学研究者之所以希望成为所谓“公众知识分子” ,有他们的初衷或目的。如何能够以及能否最终实现这样一种理想群体 ?所谓“公众知识分子”与所谓“三个意义世界”又是什么关系 ?对这些问题进行一定深度的探讨 ,最终将有利于理解所谓“文化中国”的基本建设构架及其现实意义。我们展开分析的理路是从“公众知识分子”到“三个意义世界” ,然后再落实到“文化中国” ,从中必然涉及对儒家自由主义的讨论     

“Malapropism溯源”质疑——与覃先美同志商榷

<正> 《怀化师专学报》哲学社会科学版一九八六年第一期发表了覃先美同志《Malapropism初探》一文。笔者认为,根据J.A.Cuddon对Malapropism的解释(全部原文大附后),覃文对"Ma-lapropism溯源”的考究是不确切的,对mal a propos的译文也是欠妥的。 一、覃文说:"Malapropism是1775年以后英国的‘特产’,它为Malaprop太太所创(着重号是笔者加的),而Malaprop太太则是十八世纪英国启蒙时期杰出的现实主义剧作家Richard Sheridan的喜剧'The Rivals'中的一个出色的人物”。这里的“特产”是不合乎J.A.Cuddon本意的。J.A.Cuddon的原文为:“Malaproprism: So called after Mrs Malaprop,     

Predicting scientific research trends based on link prediction in keyword networks

The rapid development of scientific fields in this modern era has raised the concern for prospective scholars to find a proper research field to conduct their future studies. Thus, having a vision of future could be helpful to pick the right path for doing research and ensuring that it is worth investing in. In this study, we use article keywords of computer science journals and conferences, assigned by INSPEC controlled indexing, to construct a temporal scientific knowledge network. By observing keyword networks snapshots over time, we can utilize the link prediction methods to foresee the future structures of these networks. We use two different approaches for this link prediction problem. First, we have utilized three topology-based link prediction algorithms, two of which are commonly used in literature. We have also proposed a third algorithm based on nodes (keywords) clustering coefficient, their centrality measures like eigenvector centrality, and nodes community information. Then, we used nodes topological features and the outputs of aforementioned topology-based link prediction algorithms as features to feed five machine learning link prediction algorithms (SVM, Random Forest Classifier, K-Nearest Neighbors, Gaussian Naïve Bayes, and Multinomial Naïve Bayes). All tested predictors have shown considerable performance and their results are discussed in this paper.