学术期刊更正文献的特征分析

【目的】学术期刊更正是学术界自我纠错的重要方式,其产生的更正文献包含大量的纠错信息,具有重要的研究价值。对更正文献的分布特点与规律予以分析和揭示,以期加强科研工作者对更正文献的了解和利用,完善学术期刊对论文更正的规范与管理,从而加强学术界与期刊界对更正行为本身以及更正文献的关注,并为后续的相关研究提供借鉴与参考。【方法】选取Web of Science核心合集数据库中近十年的更正文献记录,从年度分布、国家分布、学科分布、期刊分布四个角度对更正文献进行文献计量学分析。 【结果】分析发现,近十年来,更正文献的总量逐年攀升,进入高速增长阶段。在国家分布上,更正文献广泛分布在全球184个国家和地区,且高度集中在科研实力较为发达的国家;就其学科分布而言,更正文献具有显著的分散性特点,几乎涵盖了全部的学科;在期刊分布上,更正文献广泛分布在9000余种期刊,且集中分布于高质量优秀期刊。【结论】更正文献是科学研究中不容忽视的文献类型之一,学术期刊应从更正文献的发布、传播与引用三个角度予以规范;此外,各领域专家学者应积极参与,发挥其群体智慧;同时,应采用开放评审,提升论文质量,完善期刊建设,促进学术信息交流的健康有序发展。     

Regularizing query-based retrieval scores

We adapt the cluster hypothesis for score-based information retrieval by claiming that closely related documents should have similar scores. Given a retrieval from an arbitrary system, we describe an algorithm which directly optimizes this objective by adjusting retrieval scores so that topically related documents receive similar scores. We refer to this process as score regularization. Because score regularization operates on retrieval scores, regardless of their origin, we can apply the technique to arbitrary initial retrieval rankings. Document rankings derived from regularized scores, when compared to rankings derived from un-regularized scores, consistently and significantly result in improved performance given a variety of baseline retrieval algorithms. We also present several proofs demonstrating that regularization generalizes methods such as pseudo-relevance feedback, document expansion, and cluster-based retrieval. Because of these strong empirical and theoretical results, we argue for the adoption of score regularization as general design principle or post-processing step for information retrieval systems.

Exploiting structural information for semi-structured document categorization

This paper examines several different approaches to exploiting structural information in semi-structured document categorization. The methods under consideration are designed for categorization of documents consisting of a collection of fields, or arbitrary tree-structured documents that can be adequately modeled with such a flat structure. The approaches range from trivial modifications of text modeling to more elaborate schemes, specifically tailored to structured documents. We combine these methods with three different text classification algorithms and evaluate their performance on four standard datasets containing different types of semi-structured documents. The best results were obtained with stacking, an approach in which predictions based on different structural components are combined by a meta classifier. A further improvement of this method is achieved by including the flat text model in the final prediction.     

网上化学期刊文献的获取与利用策略

该文论述了网上化学期刊文献的获取方法，并探讨了如何更好地利用网上所获取的化学期刊文献。     

关于高等学校院系资料室文献资源建设的思考

图书资料工作是高校教学和科研工作的组成部分,是高等学校办学水平的重要标志。办好高等学校图书馆对于提高教育教学质量有着密切的关系,而高等学校院系资料室又是图书馆的重要组成部分,它对于提高教育教学质量有着更为直接的关系。但是资料室的建设和发展存在一定的问题和困难,影响了高等学校的教学科研工作,改革资料室的管理办法,加强工作人员的素质培养,提高资源利用率已是迫在眉睫。     

A scaleable document clustering approach for large document corpora

In this paper, the scalability and quality of the contextual document clustering (CDC) approach is demonstrated for large data-sets using the whole Reuters Corpus Volume 1 (RCV1) collection. CDC is a form of distributional clustering, which automatically discovers contexts of narrow scope within a document corpus. These contexts act as attractors for clustering documents that are semantically related to each other. Once clustered, the documents are organized into a minimum spanning tree so that the topical similarity of adjacent documents within this structure can be assessed. The pre-defined categories from three different document category sets are used to assess the quality of CDC in terms of its ability to group and structure semantically related documents given the contexts. Quality is evaluated based on two factors, the category overlap between adjacent documents within a cluster, and how well a representative document categorizes all the other documents within a cluster. As the RCV1 collection was collated in a time ordered fashion, it was possible to assess the stability of clusters formed from documents within one time interval when presented with new unseen documents at subsequent time intervals. We demonstrate that CDC is a powerful and scaleable technique with the ability to create stable clusters of high quality. Additionally, to our knowledge this is the first time that a collection as large as RCV1 has been analyzed in its entirety using a static clustering approach.     

建立国家文献信息保障体系的构想

论述建立国家文献信息保障体系的意义，分析了当前国内系统内和地区文献保障体系现状，提出了如何建立国家文献信息保障体系的构想和具体措施。     

基于自动摘要的网络情报收集系统研究

介绍一种网络情报收集系统的组成及体系结构，并结合这种体系结构分析系统实现过程中的关键技术及实现方法，提供生成自动摘要的流程．给出自动摘要生成过程中关键词及摘要句提取算法，分析摘要质量评价方法，提供了保障系统安全运行的措施，     

文本数字水印技术研究

随着计算机技术和网络技术的飞速发展,数字文本的传播、拷贝、分发更加容易,同时也面临着非法传播和随意篡改的问题。文本数字水印技术可以保护数字作品的版权,防止盗版和侵权行为。该文分析了基于格式文本的数字水印技术的算法和研究现状,并重点讨论了针对当今比较流行的PDF格式化文档的数字水印算法,最后探讨了今后研究的发展趋势。     

Web页面列表信息的自主抽取

本文研究了对于Web页面列表信息的抽取方法。通过对超文本文档特征的分析获取抽取知识,并通过自学习适应页面的变化,实现了对于列表信息的抽取。