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一自1926年洛特卡在《科技生产率的频率分布》一文中用定律的形式描述著作者与论著的数量关系至今,文献计量研究已有五十多年历史。继洛特卡以后,齐夫、布拉德福特等人的工作也是奠基性的。文献计量学的先驱者们敏锐地抓住了文献活动的一堆紊乱的数据中隐藏着的某种规律性,并以定律的形式精确表述。以这一系列定律为主干,形成了今天的文献计量。文献计量学初创后,人们沿着三个方向扩大着这个领域:(1)利用文献计量学成果为图 相似文献
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以网络计量学领域的网站链接数为基础,研究网址入链分布规律。首先,通过研究中网站之间的链接关系,选定入链数作为研究对象,并获取原始数据;接着,利用最小二乘法、K-S检验算法以及M.L. Pao教授提出的指数不为2时的逼近c值的估计公式对数据进行洛特卡定律拟合,发现网络计量学领域的网址入链分布并不服从洛特卡定律。最后,讨论造成不服从洛特卡定律的原因。 相似文献
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对嘉兴府志所载明清文献著者的洛特卡分布分析 总被引：2，自引：0，他引：2
洛特卡定律反映了科研论文数量与作者数量之间的统计规律,本文通过对清道光二十（1840）年刻本《嘉兴府志》所载的文献著者分布进行统计分析,引入洛特卡定律计算参数,并最终通过了k-s检验。因此可以尝试将洛特卡定律引入古典目录学研究领域,指导现实工作。 相似文献
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20/80律与布-齐-洛三个定律之间的关系 总被引：9，自引：0，他引：9
20/80律是管理学界熟知的一个重要原理,是具有普遍意义的社会规律。作者通过证明在某些约束条件下,布拉德福、齐普夫、洛特卡3个定律均符合20/80分布律,提出20/80律也是文献计量学的一个基本定律,同时应将布-齐-洛3个定律的应用扩展到文献工作以外的广大的社会领域中去。 相似文献
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Egghe公式的推广:基于广义洛特卡定律的θ与β关系 总被引：5，自引：0，他引：5
Egghe公式是基于狭义洛特卡定律而推导出来的科学成果在科学工作者中的集中程度的定量描述的公式。由于狭义洛特卡定律不具有普遍性 ,因此Egghe公式的适用范围极其有限。本文从广义洛特卡定律出发 ,推导出θ与 β的关系 ,经经验数据的验证 ,精度较高 ,具有很强的适用性 相似文献
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����������ѧ�����������о� 总被引：6，自引：0，他引：6
本文以1988～1996年出版的21种图书馆学情报学刊物(英语)为文献来源,共收集了1075篇文献计量来源文献,13265篇参考文献,记录了22项计量元素。在此基础上,从来源文献产出分析与引文分析两个方面探讨国外文献计量学近10年来所呈现出的发展态势,获得了多项文献计量学的有关数据,并得到多项结论。 在对作者产生率的研究中,统计结果表明,发表1篇论文的作者在全部作者中占83.89%,发表5篇论文以上的作者占1.3%。这些活跃作者共发表论文229篇,占全部来源文献的21.3%。这一方面说明洛特卡定律的不尽合理之处,另一方面也表明文献计量学具有不同于其… 相似文献
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文献计量学经典定律的相互关系 总被引：2，自引：0，他引：2
文献计量学经典定律分为两组：第一组为布拉德福（文字表述）定律、莱姆库勒定律、芒代尔布罗定律和洛特卡定律；第二组为布拉德福（图象描述）定律、布鲁克斯定律和齐夫定律。经数学推导，论证了布鲁克斯定律与齐夫定律不存在等效关系；布拉德福（图象描述）定律与齐夫定律等效，而与布鲁克斯定律不等效；布拉德福（文字表述）定律与布拉德福（图象描述）定律亦不存在渐近关系。从而确认了文献计量学７种经典定律之间的相互关系为：第一组定律间等效，第二组定律间渐近，第一、第二两组定律之间既不渐近，更不等效。本文另与Ｅｇｇｈｅ与龚义台两位的有关研究作了比较，并对两者结论中的不足和错误之处进行了讨论 相似文献
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按照文献计量学有关方法,对2000年以来《编辑学报》的学术影响力进行分析,并采取秩和检验、Spearman(或Kendall)和K-S等方法(检验水准α=0.05)对该刊论文第一作者与论文数量之间的关系进行洛特卡定律的适应性检验。结果:第一作者人数与理论作者人数无差异(Z=1.107,P=0.172),存在相关性(rs=0.914,P0.001(或rK=0.843,P0.001))和一致性(Z=1.171,P=0.129)。说明该刊论文第一作者与论文数量之间的关系与洛特卡定律基本符合。 相似文献
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??The Lotka's law and the Price law reveal some internal relatians between the scientists and their works.A starletcs is made on the papers written by the Chinese mathematics workers and published on 75 kinds of journals in the past ten years.Qn this hasis,Lotka' s expression ff??yx??=0.6472·(1/X2.12)of the Chinese mathematics workers is pbtained.The authors find that the distribution of the Chinese mathematicx workers accards with some canclusians of the expression and Price Law,but not with Lotka's Law. 相似文献
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Alexander Serenko Raymond A.K. Cox Nick Bontis Lorne D. Booker 《Journal of Informetrics》2011,5(3):333-345
This paper reports on the first documented attempt to investigate the presence of the superstar (or Matthew) effect in the knowledge management and intellectual capital (KM/IC) scholarly discipline. The Yule–Simon model and Lotka's square law were applied to the publication data obtained from 2175 articles from 11 KM/IC journals. Based on the findings, it was concluded that the KM/IC discipline represents a very young, attractive academic field that welcomes contributions from a variety of academics and practitioners. In their paper acceptance decisions, KM/IC journal editors are not biased towards a small group of highly productive researchers, which is a positive sign that the field has been progressing in the right direction. The discipline is driven more by academics than by practitioners, and the distribution of articles is more concentrated among a few academic but not practitioner institutions. It was also observed that the Yule–Simon model and Lotka's square law may produce different distributions with respect to institutions. 相似文献
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Patent prior art search is a type of search in the patent domain where documents are searched for that describe the work previously carried out related to a patent application. The goal of this search is to check whether the idea in the patent application is novel. Vocabulary mismatch is one of the main problems of patent retrieval which results in low retrievability of similar documents for a given patent application. In this paper we show how the term distribution of the cited documents in an initially retrieved ranked list can be used to address the vocabulary mismatch. We propose a method for query modeling estimation which utilizes the citation links in a pseudo relevance feedback set. We first build a topic dependent citation graph, starting from the initially retrieved set of feedback documents and utilizing citation links of feedback documents to expand the set. We identify the important documents in the topic dependent citation graph using a citation analysis measure. We then use the term distribution of the documents in the citation graph to estimate a query model by identifying the distinguishing terms and their respective weights. We then use these terms to expand our original query. We use CLEF-IP 2011 collection to evaluate the effectiveness of our query modeling approach for prior art search. We also study the influence of different parameters on the performance of the proposed method. The experimental results demonstrate that the proposed approach significantly improves the recall over a state-of-the-art baseline which uses the link-based structure of the citation graph but not the term distribution of the cited documents. 相似文献
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[目的/意义] 构建技术转移特征指标体系,提前识别具有应用潜力的专利,为专利技术转移提供信息支撑,促进技术成果转移转化。[方法/过程] 基于专利转让行为的客观事实信息,界定转让和未转让数据集,分析比对两者特征差异,构建技术、法律、市场、主体4个维度的基于专利文献自身的技术转移特征指标体系,并进行指标统计学检验以及实证模型检验。[结果/结论] 基于专利文献自身的基础特征指标能够预判技术转移,各指标影响程度相对均衡且不存在主导性指标。实证SVM模型检验该指标体系的预测效度,初步实现能够应用于国家/地区层面、机构层面、专利个体层面的技术转移特征指标体系的构建与检验,该方法具有实用性。 相似文献
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L. A. Denisova V. M. Efremenkova G. A. Kusch T. P. Ponomarenko 《Scientific and Technical Information Processing》2011,38(2):123-131
We trace the reflection of patent information in the database/abstract service of the All-Russia Institute of Scientific and
Technical Information of the RAS from the date of their origin. We present the technology for forming the input flow of patent
documents. We describe the retrofunds of patent documents reflected in the four blocks of the database of the All-Russia Institute
of Scientific and Technical Information on natural science, technical sciences, life sciences and earth sciences in the period
from 1981 to 2009. We analyze the distribution dynamics of arrays of patents in the polythematic database and in every block
of the database of the All-Russia Institute of Scientific and Technical Information. 相似文献