灰色预测法在情报研究中的应用研究综述

[目的/意义] 灰色预测法可有效处理情报研究中广泛存在的小样本数据，通过对灰色预测法在情报研究中的应用情况进行梳理，总结其在应用过程中存在的不足，为灰色预测法在情报研究中的进一步应用提供参考。[方法/过程] 通过综述情报研究中涉及灰色预测法的相关文献，从数据选取、模型构建和解决的问题等方面对情报研究中灰色预测法的应用进行概述，总结当前情报研究中灰色预测法的应用所存在的问题，并提出改进建议。[结果/结论] 在方法应用上，已有研究主要采用数列灰预测，且模型集中在单变量灰色预测模型，根据预测对象不同，灰色预测法已经在包括期刊分析、图书馆运行管理、热点主题分析及科研机构评价方面得到了很好的应用，未来可根据预测对象特点及研究目标尝试不同的灰色预测方法，扩宽灰色预测法在其他方面的情报研究问题中的应用。     

国际科研众筹项目的特征描述、主题分析及属性对比:基于Experiment平台的发现

[目的/意义]为了深入了解科研众筹平台中的项目情况,本文对科研众筹项目的基本特征、研究主题和不同类型科研众筹项目的属性对比进行研究。[研究设计/方法]首先对科研众筹的起源、价值和运作模式进行了梳理;随后爬取了科研众筹平台Experiment的项目信息,并对该平台中科研项目的发起者、背书者、项目记录、所属学科、资助情况等进行特征描述;基于LDA模型对科研众筹项目主题进一步细化,并对不同资金筹集和不同主题分类情况下的科研众筹项目的属性差异进行比较分析。[结论/发现]科研众筹主题主要集中在生物学和生态学两个领域,不同资金筹集达成情况的科研众筹项目在项目背书者数量、信息记录次数和讨论次数上具有显著差异;不同主题的科研众筹项目在其讨论次数上具有显著差异。同时,是否提供视频和是否参与资助挑战在不同资金筹集达成情况和不同主题的科研众筹项目上均具有显著差异。[创新/价值]深入分析了科研众筹平台中项目主题及属性对比情况,对科研众筹平台优化信息审核机制、社交机制和信息展示机制具有一定的参考价值。     

The Program for Cooperative Cataloging’s Transformative Role as a Leader of Change

Abstract

The transformation of library metadata encoded in MARC to linked data will enable libraries to participate in the Semantic Web. This transformation, however, will be an iterative development dependent upon community-based decisions. The PCC, as a community-based organization, is ideally positioned to lead this transformation. As PCC guides this transition, three broad areas must be resolved: the conversion of legacy data to linked data, the use of identifiers to support controlled headings, and the transformation of current workflows to linked-data counterparts. By embracing the Web as a community, PCC can confirm its relevance in a complex web of global data.     

一种基于图卷积自编码模型的多维度学科知识网络融合方法

[目的/意义] 针对包含单一类型知识单元的知识网络难以全面反映学科知识结构的问题，提出一种从多维度进行知识网络结构融合的方法，为学科领域知识结构挖掘提供借鉴。[方法/过程] 利用LDA及TF-IDF方法抽取学科知识单元，然后运用语义相似度和关键词共现分析方法构建3个学科知识子网络：主题网络、关键词网络和实体网络，并采用空间节点传递对齐方法对齐子网络节点，接着设计基于图卷积操作的自编码模型对知识节点进行表示，最后通过计算余弦相似度重构学科知识网络。[结果/结论] 实验部分以人工智能领域为例，构建融合主题、关键词和实体的学科知识网络并展开分析，实验结果表明，本文所提方法能有效地揭示学科领域研究内容和知识结构，为学科知识发现与组织研究提供有益参考。     

《左传》的文本之争与文本流变

《左传》是我国首部以编年为次序、以鲁国十二公为传主,系统记述春秋战国时期历史,对中国文化产生了巨大影响的文史作品。文章在概述《左传》文化价值的基础上,梳理了两千多年来关于《左传》文本与作者的主要学术争论,甄别《左传》流变过程中的22个关键文本。     

欧洲九国共产党情报局机关刊物《争取持久和平,争取人民民主!》与中国关系考述(1949-1956)

《争取持久和平,争取人民民主!》是20世纪40年代中后期,欧洲九个社会主义国家的共产党和工人党为了一致行动而建立的情报局机关刊物。该刊物对新中国初期我国经济社会建设及成就进行了大量宣传与报道,对加强我国与世界其他爱好和平、渴求民主的各国人民加强互信、长存友谊贡献很大,也对当前学者研究新中国初期我国经济社会发展的过程、成就和经验等提供了原始史料,学术研究意义也很重大。但是,目前对这份刊物及其发挥过的重大作用了解的人少之又少,时值中国共产党成立100周年之际,对其创刊与发行的历史过程进行回顾、宣传中国社会经济发展的全貌进行展示、推动世界社会主义运动的作用进行肯定,意义都很重大。     

Ancient Mural Classification Method Based on Improved AlexNet Network

ABSTRACT

As an important part of art and culture, ancient murals depict a variety of different artistic images, and these individual images have important research value. For research purposes, it is often important to first determine the type of objects represented in a painting. However, the mural painting environment makes datasets difficult to collect, and long-term exposure leads to underlying features that are not distinct, which makes this task challenging. This study proposes a convolutional neural network model based on the classic AlexNet network model and combines it with feature fusion to automatically classify ancient mural images. Due to the lack of large-scale mural datasets, the model first expands the dataset by applying image enhancement algorithms such as scaling, brightness conversion, noise addition, and flipping; then, it extracts the underlying features (such as fresco edges) shared by the first stage of a dual channel structure. Subsequently, a second-stage deep abstraction is conducted on the features extracted by the first stage using a two-channel network, each of which has a different structure. The obtained characteristics from both channels are merged, and a loss function is constructed to obtain the classification result. This approach improves the model's robustness and feature expression ability. The model achieves an accuracy of 84.24%, a recall rate of 84.15%, and an F1-measure of 84.13% when applied to a constructed mural image dataset. Compared with the AlexNet model and other improved convolutional neural network models, the proposed model improves each evaluation index by approximately 5%, verifying the rationality and effectiveness of the model for automatic mural image classification. The mural classification model proposed in this paper comprehensively considers the influences of network width and depth and can extract rich details from mural images from multiple local channels. An effective classification method could help researchers manage and protect mural images in an orderly fashion and quickly and effectively search for target images in a digital mural library based on a specified image category, aiding mural condition monitoring and restoration efforts as well as archaeological and art historical research.     

Influence of Process Parameters on Chlorinated Biocide Decontamination by li-CO2 on Artificially Contaminated Model Materials

ABSTRACT

Previously, heavy use of biocides for the treatment of objects made of organic materials in museum collections (e.g. ethnographic, historical collections) was very common. Now suitable decontamination methods/technologies are being sought. A decontamination treatment by li-CO₂ was optimized that considered the specific requirements of museum objects. The treatment was tested on model materials artificially contaminated with biocide solutions containing dichlorodiphenyltrichloroethane (DDT), pentachlorophenol (PCP), lindane, and permethrin or cypermethrin. High decontamination was achieved for DDT, lindane, PCP, and permethrin on artificially biocide loaded wool and wood model materials. Optimal process parameter settings for li-CO₂ decontamination include a single 30?min cycle for woolen materials and three sequential 30?min cycles each for wood. These methods allow a reduction of at least 90% of all biocides for wool and between 70% and 85% for wood. Decontamination of the latter was more effective for less polar biocides as DDT and permethrin. Despite a significant improvement in decontamination for wood using co-solvents such as acetone, ethanol, and methyl tertiary-butyl ether (MTBE), their use is not recommended due to the increased risk of damage to the objects, in particular if a surface coating is present.     

美国民俗生活中心口述文献的采集与利用

[目的/意义]推动我国图书馆的口述文献采集工作，提升我国图书馆口述文献利用服务水平。[方法/过程]通过网络、文献、邮件等方式，对美国国会图书馆下属的美国民俗生活中心进行全面调研，对其开展的退伍军人历史、职业民俗、民权口述历史调查和洛马克斯家族等典型项目进行介绍总结，在此基础上分析该中心开展口述文献采集与利用的经验。[结果/结论]分析结果认为，该中心积极利用数字技术与平台、探索多元化采集模式、加强与社会组织合作、设立各种基金与倡导捐款、尊重参与者合法权益等做法和经验，对我国图书馆界具有一定的借鉴意义。     

中外情报学论文创新性特征研究

[目的/意义] 综合运用定性与定量相结合的方法对近年中外情报学论文的创新性进行分析和对比，揭示情报学领域研究的创新性特征，发现领域学术论文中创新句内部的知识关系，进行更细粒度的论文创新性分析，为研究领域创新点深层次利用提供条件，同时丰富科技论文创新性监测的途径，促进科学研究创新。[方法/过程] 从句子级创新性识别出发，选取中英文各两种情报学期刊作为样本，采用信息抽取和机器学习的方法，将创新句的抽取从现有的摘要扩展到全文，充分利用句子结构和句法特征识别领域创新内容，探讨近年中外情报学论文在创新对象、主题、类别等方面的特征，并做对比分析，最后通过对自动分类的论文集合进行定性的内容分析，总结归纳出中外情报学论文创新的表达范式。[结果/结论] 从创新的表达来看，中外情报学论文创新句的分布情况基本一致，英文期刊论文创新的表达更丰富。从创新性特征来看，英文情报学期刊论文创新主题较集中，而中文主题多样和分散；具体方法的创新是近年情报学领域的创新热点，而在研究方法上创新不足；中英文情报学期刊论文的创新性特点都反映了应用研究、实证研究的成果较多，而理论创新推动缓慢的趋势。