共查询到20条相似文献，搜索用时 296 毫秒
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林平 《大学图书情报学刊》2007,25(1):86-90
科学文献的相互引用关系是引文分析的主要依据.引文分析是以文献引用数据为基础,用以揭示其数量特征和规律的一种文献计量分析方法.作者对<大学图书情报学刊>1998年与2004年的引文数量进行了量化分析,指出了刊物在引文数量、引文文献类型、引文语种、引文主题、引文原始来源期刊的发展和变化情况,提出了值得重视的有关问题. 相似文献
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[目的/意义] 为了解我国标准文献的学术影响力, 以为标准文献的利用提供参考, 从标准文献的角度出发, 分析其被引证特征。[方法/过程] 选择中国引文数据库中1994-2013年标准类引文数据, 采用文献计量的方法, 从标准引文总量、篇均标准引文量等方面分析标准文献的总体被引用情况和学科分布情况。[结果/结论] 标准引文量和篇均标准引文量占引文总量比例很小;各学科标准引文量差异较大, 工科和医科对标准文献的引用较多;标准引文数量和被引频次较高的专题集中于自然科学;大部分社会学科标准引用量为零;标准引文的半衰期整体上较长, 老化速度较慢。 相似文献
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本文对2000年的8种语言学、文字学类期刊论文的引文进行统计。从引文的语种、引文的文献类型和引文的时间等几方面作了具体的分析研究，从中得出评议专业文献中心馆藏文献结构的最佳配置方案。 相似文献
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天津理工学院学报引文分析与评价 总被引：5，自引：0，他引：5
本文运用文献计量学方法 ,对《天津理工学院学报》1 988— 1 997年刊登论文的引文量、引文类型、引文语种、引文年代等方面进行了统计与分析 ,以期为本刊作者合理利用文献和高校图书馆做好文献资源建设与开发提供客观依据 相似文献
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英美学术文献的几种主要引文方式 总被引：2，自引：0，他引：2
一篇没有详尽规范引文的学术文献难以得到专家和同行的认可，对文献作者来说，明确地标明文献中的引文可以充实论据，提高文献本身的价值和可信度，彻底摆脱“剽窃”的嫌疑；而对于文献利用者来说，规范明确的引文给他们提供了方便可靠、进一步研究、考证和评价的途径。本文向大家介绍英国和美国英文文献的几种主要的引文方式和英美国家著录格式。 相似文献
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以引文上下文为研究对象,探讨来自于引文上下文、目标文献摘要以及目标文献自标医学主题词（下称主题词）三者间的符合程度,定量分析引文上下文在表征目标文献内容特征时的作用。以被Circulation杂志高频引证的5篇研究类论文作为目标文献,提取其施引文献的全部引文上下文,并对其进行分词及主题词匹配;将其结果与目标文献摘要提取的主题词以及文献自标的主题词进行两两比较。结果表明,引文上下文与目标文献摘要具有较高的符合度,而且在表征被引文献内容特征的效果上明显具有优势。 相似文献
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引文分析法是图书馆学、情报学的专门研究方法。利用文献计量学（Bibliometries）的引文分析法（citation analysis method）,对《津图学刊》1998－2001年所刊载论文的引文量、引文语种、引文类型、引文年代、引文期刊、引文著者等诸多方面进行了统计与分析,以期为本刊作者合理利用文献提供依据。 相似文献
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A test of the performance of an automatic indexing procedure based on the processing of the full text of medical journal articles shows results comparable to those achieved using Excerpta Medica and MEDLARS manual indexing. A file of nineteen documents was partitioned by sixteen questions, for each of which two search strategies in each indexing language were formulated. The results were compared to ideal answers chosen by a fourth-year medical student who read the entire file and posed the questions. 相似文献
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Jacques Savoy 《Information Retrieval》2007,10(6):509-529
This paper reports on the underlying IR problems encountered when indexing and searching with the Bulgarian language. For
this language we propose a general light stemmer and demonstrate that it can be quite effective, producing significantly better
MAP (around + 34%) than an approach not applying stemming. We implement the GL2 model derived from the Divergence from Randomness paradigm and find its retrieval effectiveness better than other probabilistic, vector-space and language models. The resulting
MAP is found to be about 50% better than the classical tf idf approach. Moreover, increasing the query size enhances the MAP by around 10% (from T to TD). In order to compare the retrieval
effectiveness of our suggested stopword list and the light stemmer developed for the Bulgarian language, we conduct a set
of experiments on another stopword list and also a more complex and aggressive stemmer. Results tend to indicate that there
is no statistically significant difference between these variants and our suggested approach. This paper evaluates other indexing
strategies such as 4-gram indexing and indexing based on the automatic decompounding of compound words. Finally, we analyze
certain queries to discover why we obtained poor results, when indexing Bulgarian documents using the suggested word-based
approach. 相似文献
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In this paper the problem of indexing heterogeneous structured documents and of retrieving semi-structured documents is considered. We propose a flexible paradigm for both indexing such documents and formulating user queries specifying soft constraints on both documents structure and content. At the indexing level we propose a model that achieves flexibility by constructing personalised document representations based on users views of the documents. This is obtained by allowing users to specify their preferences on the documents sections that they estimate to bear the most interesting information, as well as to linguistically quantify the number of sections which determine the global potential interest of the documents. At the query language level, a flexible query language for expressing soft selection conditions on both the documents structure and content is proposed. 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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邵品洪 《现代图书情报技术》1994,10(3):26-28
本文扼要地介绍了日本学者围绕提高情报检索系统的性能,开展自然语言信息处理研究的一些成果:包括以英语科技文摘为对象所进行的自动索引研究和动词的用法分析,以及从混合使用汉字和假名的日语文本中自动抽出日语名词的研究等。 相似文献
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标引的一致性是衡量主题标引质量的重要指标。综述了计算机类献主题标引不一致的四种表现，分析了引起标引不一致的原因，在此基础上探讨了计算机类献主题标引一致性的方法。 相似文献
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浅谈《工程索引》网络版的不足 总被引：1，自引：0，他引：1
《工程索引》(Ei)是工程领域权威的检索工具,但存在一些不足。笔者认为,其不足之处主要在于:收录论文较为滞后、收录文献语种分布不合理、中文信息标引不规范及输出功能有待增强等方面。 相似文献
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基于集成学习的自动标引方法研究 总被引：1，自引：0，他引：1
目前大多数自动标引方法不能有效利用文本中包含的多个特征.而支持向量机、条件随机场模型等统计机器学习模型能够有效利用文本包含的多种特征进行关键词提取.同时,由于各种自动标引模型性能各异,综合利用各种模型进行集成学习方式的自动标引,能够提高自动标引的质量.为了进一步提高自动标引的质量,本文试图整合统计机器学习模型与集成学习方法的优势,对文档进行基于多分类模型综合投票方式的自动标引.实验结果表明基于集成学习方法的自动标引能提高标引结果的查准率和召回率.另外,集成学习标引模型中,基分类器加权的标引结果,优于基分类器未加权的标引结果. 相似文献