Two-stage statistical language models for text database selection

As the number and diversity of distributed Web databases on the Internet exponentially increase, it is difficult for user to know which databases are appropriate to search. Given database language models that describe the content of each database, database selection services can provide assistance in locating databases relevant to the information needs of users. In this paper, we propose a database selection approach based on statistical language modeling. The basic idea behind the approach is that, for databases that are categorized into a topic hierarchy, individual language models are estimated at different search stages, and then the databases are ranked by the similarity to the query according to the estimated language model. Two-stage smoothed language models are presented to circumvent inaccuracy due to word sparseness. Experimental results demonstrate that such a language modeling approach is competitive with current state-of-the-art database selection approaches.     

China's statistical system and resources

As the People's Republic of China plays an increasingly important role in international politics and trade, countries with economic interests there find they need to know more about this nation. Access to primary information sources, including official statistics from China, however, is very limited, as little exploration has been done into this closely controlled repository of information. This study explores major current statistical sources in China through examining (a) the statistical system in Chinese government, (b) the mechanism of statistical data collection, and (c) what statistical information is currently available in both print and electronic format and at what level. It shows that a wealth of statistical information does exist in China, it is systematically compiled, and it is available, although not conveniently, to the public through various channels. This study can serve the need for China's data from the academic and business communities, contribute to a better understanding of China's statistical system, and serve as a collection tool for academic, public, and corporation libraries as well.     

近年来国内竞争情报研究述评--基于中国期刊网1999～2004年竞争情报论文的统计分析

本文以中国期刊全文数据库（CNKI）收录的1999-2004年竞争情报相关论文为基础，通过大量数据统计分析，指出了我国竞争情报（CI：Competitive intelligence）研究的主要方向，并结合各方向的具体分析，指出了我国在竞争情报研究方面的不足，提出了相应的对策和我国竞争情报研究新的发展趋势。     

医学论文“统计学处理”常见问题分析及建议

【目的】 分析医学论文“统计学处理”中存在的问题,为提高医学期刊学术及编辑质量提供参考。 【方法】 审读已发表的医学论文,结合典型案例,对其中的“统计学处理”问题进行归纳总结。 【结果】 医学论文“统计学处理”部分主要存在下列问题：“统计学处理”内容不全,多组比较未交待两两比较的方法,统计软件与统计推断方法混淆,统计学基本概念模糊,统计描述与统计推断方法不一致,“统计学处理”与“结果”内容不一致,“统计学处理”中含有“结果”部分的内容。 【结论】 为了避免“统计学处理”中的错误,编辑应加强对统计学知识的学习,注意全文各部分统计学内容之间的联系;期刊应建立统一的编辑规范,严格按照正确的统计学方法修改论文;审稿中应充分发挥统计学专家的作用。     

对2006年世界杯足球赛决赛阶段运动员犯规情况的统计分析

采用文献资料法、录像观察法对2006年世界杯足球赛决赛阶段64场比赛场上队员犯规情况进行定性定量统计,利用EXCEL对数据进行统计分析。结果表明：1.全部比赛运动员共犯规2275次、越位379次、被判黄牌331张、红牌25张。2.运动员的犯规动作类型比例按顺序从过去的踢人、拉扯、冲撞、铲人、推人、绊摔变为铲人、推人、冲撞、绊摔、拉扯、踢人。     

浙江省青少年跆拳道比赛中腿法得分的统计与分析

文章采用现场统计法,对浙江省青少年跆拳赛技术运用情况进行了统计与分析,发现青少年男女运动员腿法运用情况基本相似,都是以横踢为主,只是男子在高难度动作上稍微突出一些;高水平的运动员各个技术动作的运用比较全面,而青少年技术使用比较单调。说明浙江省青少年运动员的技术水平和国家级有较大的差距,今后应重视青少年基本技术的全面训练,以提高整体水平为主。     

我国物联网产业统计指标体系基本框架研究

物联网产业的发展是继互联网后的又一次信息浪潮。物联网产业是我国新兴战略性产业之一,要对该产业进行统计并加以评价,需要建立统计指标体系。在前期研究的基础上,提出物联网产业统计指标体系设计原则和以增加值为核心指标的基本思路,构建我国物联网产业统计指标体系的基本框架,并对主要指标进行解释。     

从SCI论文统计分析看瓜尔豆研究进展

根据Web ofScience收录论文的统计数据,分析了国际瓜尔豆研究的进展和学科领域的研究情况,根据瓜尔豆的研究成果在SCI收录论文上所反映发生的差异和变化,并以此为依据,对瓜尔豆领域的研究、应用和发展提出了意见。     

自动化管理系统的统计功能与图书馆科学管理

本文以北邮电信的MELINETS系统为例，介绍了图书馆自动化系统的统计功能，分析了自动化系统的统计功能在图书馆科学管理工作中的作用，探讨了目前图书馆统计工作中存在的问题，并提出了改进措施。     

Automatic extraction of bilingual word pairs using inductive chain learning in various languages

In this paper, we propose a new learning method for extracting bilingual word pairs from parallel corpora in various languages. In cross-language information retrieval, the system must deal with various languages. Therefore, automatic extraction of bilingual word pairs from parallel corpora with various languages is important. However, previous works based on statistical methods are insufficient because of the sparse data problem. Our learning method automatically acquires rules, which are effective to solve the sparse data problem, only from parallel corpora without any prior preparation of a bilingual resource (e.g., a bilingual dictionary, a machine translation system). We call this learning method Inductive Chain Learning (ICL). Moreover, the system using ICL can extract bilingual word pairs even from bilingual sentence pairs for which the grammatical structures of the source language differ from the grammatical structures of the target language because the acquired rules have the information to cope with the different word orders of source language and target language in local parts of bilingual sentence pairs. Evaluation experiments demonstrated that the recalls of systems based on several statistical approaches were improved through the use of ICL.