徽州文书分类整理要点和疑难解析

徽州文书分类整理是一项学术性很强的科研工作,需要一整套科学规范的分类著录体系和正确合理的工作方法,要求整理人员掌握丰富的历史知识和多种专门业务知识。在分类整理中最常遇见的疑难问题是土地文书中名实不符、内容不清、地点不明和复合契四种,必须准确地解析文书所涉及的各种关系,根据文书真实内容确定类目。     

“阿尔茨海默病”在《中图法》中的类目设置探讨

近年来,有关阿尔茨海默病的文献大量涌现,但《中图法》第4版中并无相关类目。通过对《中图法》R749．16老年及早老性精神障碍和中国精神疾病分类的分析,参照国际疾病分类（ICD-10）和《美国精神疾病诊断与统计手册》第4版修订本（DSM-IV-R）和《中国精神障碍分类与诊断标准》第3版（CCMD-3）相关类目的现行标准和原则,提出3种分类方案。     

网络舆情场中信息受众观点测度的机理及路径分析

[目的/意义]整合定性与定量的舆情研究视角,统一多模态研究对象,实现网络舆情信息受众的观点测度,可修复网络舆情分析与治理的理论与实践裂痕。[方法/过程]通过引入网络舆情场的概念,对网络舆情信息受众、受众观点测度的内涵进行诠释,就网络舆情场与信息受众观点测度的逻辑关系加以辩证讨论。[结果/结论]提出网络舆情场内舆情受众观点测度机理和具体测度路径,为后续网络舆情场中的网络舆情信息分析、多维度信息受众观点测度,受众认知规律发现,网络舆情监督和管控限制等层面的研究做相应铺垫。     

Four pitfalls in normalizing citation indicators: An investigation of ESI’s selection of highly cited papers

InCites Essential Science Indicators is becoming increasingly used to identify top-performing research and evaluate the impact of institutes. Unfortunately, our study shows that ESI indicators, as well as other normalized citation indicators, have the following flaws. First, the publication month and the online-to-print delay affect a paper’s probability of becoming a Highly Cited Paper (HCP). Papers published in the earlier months of the year are more likely to accumulate enough citation counts to rank at the top 1% compared with those published in later months of the year. Papers with longer online-to-print delays have an apparent advantage for being selected as HCPs. Research field normalizations lead to the third pitfall. Different research fields have different citation thresholds for HCPs, making research field classification important for a journal. In addition, the uniform thresholds for both articles and reviews in ESI affect the reliability of HCP selection because, on average, reviews tend to have higher citation rates than articles. ESI’s selection of HCPs provides an intuitive feel for the problems of normalized citation impact indicators, such as those provided in InCites and SciVal.     

Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics

The purpose of this study is to find a theoretically grounded, practically applicable and useful granularity level of an algorithmically constructed publication-level classification of research publications (ACPLC). The level addressed is the level of research topics. The methodology we propose uses synthesis papers and their reference articles to construct a baseline classification. A dataset of about 31 million publications, and their mutual citations relations, is used to obtain several ACPLCs of different granularity. Each ACPLC is compared to the baseline classification and the best performing ACPLC is identified. The results of two case studies show that the topics of the cases are closely associated with different classes of the identified ACPLC, and that these classes tend to treat only one topic. Further, the class size variation is moderate, and only a small proportion of the publications belong to very small classes. For these reasons, we conclude that the proposed methodology is suitable to determine the topic granularity level of an ACPLC and that the ACPLC identified by this methodology is useful for bibliometric analyses.     

Seeking Nettle Textiles – Utilizing a Combination of Microscopic Methods for Fibre Identification

Bast fibres have been commonly used as a textile material in Northern Europe since Neolithic times. However, the process of identifying the different species has been problematic, and many important questions related to their cultural history are still unanswered. For example, a modified Herzog test and the presence of calcium oxalate crystals have both been used in identification. In order to generate more reliable results, further research and advancement in multi-methodological methods is required. This paper introduces a combination of methods which can be used to identify and distinguish flax (Linum usitatissimum), hemp (Cannabis sativa), and stinging nettle (Urtica dioica). The research material consisted of reference fibres and 25 fibre samples obtained from 12 textiles assumed to be made of nettle. The textiles were from the Finno-Ugric and Historical Collections of The National Museum of Finland. The fibre samples were studied by observing the surface characteristics and cross sections with transmitted light microscopy, and by using a modified Herzog test with polarized light, in order to identify the distinguishable features in their morphological structures. The study showed that five out of 25 samples were cotton, 16 nettle, one flax, and one hemp. Findings from two samples were inconsistent. The results show that it is possible to distinguish common north European bast fibres from each other by using a combination of microscopic methods. Furthermore, by utilizing these combined methods, new and more reliable information could be obtained from historical ethnographic textiles, which creates new vistas for the interpretation of their cultural history.     

Knowledge Classification on Ethnic Groups in Thailand

This research aimed to analyze and develop a scope of knowledge and structure with respect to ethnic groups in Thailand. The research was conducted on the basis of the knowledge organization concept and principles of classification. This was a quality research that used content analysis method. It consisted of three processes: (1) identification of the scope of knowledge; (2) the development of knowledge classification and structure; and (3) evaluation and confirmation of the knowledge structure by experts. The research results provided the knowledge scope and structure of the ethnic groups in Thailand which comprises of 12 classes, 51 sub-classes, and 65 divisions. This knowledge structure can be used for ontology development or used as guidelines for subject headings and search terms in the information system.     

UMLS语义网络在社会化标注系统中的应用研究

[目的/意义] 研究统一医学语言系统中语义网络与社会化标注系统结合的深层次应用。[方法/过程] 总结UMLS语义网络的现有应用,分析UMLS语义类型与FrameNet语义类型的特征,构建适合本研究的语义类型,并通过实例梳理社会化标注系统与本体映射的思路。[结果/结论] 提出将所构建的语义类型作为标签归类的分类器以及作为分众分类系统与框架网络本体映射的桥梁。突破传统的基于统计的标签归类方法可为本体与分众分类系统的映射提供新的视角。     

融入情感差异和用户兴趣的微博转发预测

[目的/意义] 微博转发是实现微博信息传播的重要方式,对用户转发行为进行研究可以更好地理解微博信息传播机制,对热点话题检测、舆情监控、微博营销等具有重要意义。针对以往研究中用户兴趣表示不够全面准确以及未考虑情感差异对用户转发行为的影响,提出一个融入情感差异和用户兴趣的微博转发预测模型。[方法/过程] 该模型首先从维基百科中提取概念语义关系构建维基知识库,将其作为语义知识源对微博文本进行语义扩展,解决语义稀疏问题;对语义扩展后的用户历史微博进行聚类,提取用户兴趣主题和主题对用户的影响力;然后计算微博中各类情感的情感强度,提取情感差异特征;最后结合用户行为特征、用户交互特征、微博特征、用户兴趣特征和情感差异特征,运用SVM实现微博转发预测。[结果/结论] 在新浪微博真实数据集上进行实验,验证了所提模型的有效性。     

知识域可视化中的共被引与耦合研究综述

[目的/意义] 知识域可视化是信息可视化衍生出的一个重要分支。基于图书情报学、科学学的研究方法,对知识域可视化研究成果中的共被引与耦合进行全面梳理,分析共被引与耦合在知识域可视化方法中的具体应用,总结知识域可视化的共被引与耦合新发展,引导和推动知识域可视化研究的深入开展。[方法/过程] 在界定知识域、知识域可视化和构建知识域可视化研究框架的基础上,对知识域可视化方法的共被引与耦合进行了归纳和总结,分析了文献共被引方法、作者共被引、期刊共被引、文献耦合方法、作者耦合方法这5种主要的共被引与耦合方法。[结果/结论] 认为以上5种方法是知识域可视化研究的主要方法,而多元引用方法、融合替代计量学的共被引与耦合代表了知识域可视化的新发展。