改进的关联规则在文献个性化检索中的应用研究

针对当前高校图书馆文献检索系统不能面向不同读者提供个性化检索服务的弱点,进行文献个性化检索的研究,提出将关联规则运用于对原始检索结果集按照读者层次进行个性化排序的设想,并以某高校图书馆的数据为例,详细描述利用改进的关联规则算法挖掘历史借阅数据,然后利用挖掘结果进行排序的过程,理论和实验验证将关联规则应用在文献个性化检索中的可行性。     

人工智能机器人技术在图书馆的应用

文章利用自然语言处理和机器学习技术,理解图书馆用户的检索意图并提供准确的文献检索结果,分析用户的查询语句和历史检索记录,学习和识别用户的偏好,从而提供个性化的检索服务。实验结果表明,文章应用人工智能机器人技术构建的文献自动检索系统具有较高的准确性和可靠性,能够有效提高图书馆文献检索的效率和质量。     

基于Spark内存算法的图书馆大数据文献服务方案研究

互联网时代背景下,如何提供高效并精确的文献检索服务是目前图书馆文献检索领域的难题.针对这一问题,首先分析了现阶段图书馆信息检索领域的研究方向和应用需求,然后提出基于Spark内存计算框架的文献检索服务方案,通过添加惩罚系数对Spark推荐算法进行了优化,最后以某高校图书馆近5年的检索数据进行反演.研究发现:首先,基于S...     

基于卷积神经网络的图书馆文献自动检索机器人研究

图书馆文献规模的不断扩大,为用户找寻需求文献带来了极大难度,为提高对于文献信息的处理效率和检索精度,基于卷积神经网络研究图书馆文献自动检索机器人。设计包括RFID硬件单元、卷积神经网络硬件加速器单元与文献信息存储器单元的硬件部分。设计包括文献信息自动分类模块、文献检索应用服务定义与协议描述模块与文献自动检索模块的软件部分。实验数据显示：设计机器人文献自动分类迭代次数与文献自动检索时延均低于最高限值,文献自动检索精度范围为74.07%～88.89%,说明文献信息的处理效率、机器人的应用效率及检索精度均较高,能满足读者的文献检索需求。     

一种改进的参考文献搜索模型及相关性技术研究

基于Web的参考文献检索越来越受到欢迎，但是现有的参考文献相关性计算方法不能准确地给出参考文献的相关性，从而影响了用户文献检索的质量。首先给出了一个参考文献结构模型，在该模型中提出了虚节点的概念，从而大大拓展了文献检索的范围；其次在参考文献结构模型的基础上，通过充分挖掘参考文献之间的引用关系来计算参考文献在参考文献信息库中的重要性。通用组合位置／频率法与参考文献引用相关性技术的结合应用大大提高了文献检索的精度和质量。     

中文信息的全文检索技术

前言信息时代产生了大量的信息，迫切需要一个高效的信息整理工具，以便快速得到自己的所需要的文章。全文检索以其易用和实用件、成为包括中义在内的信息领域的基本技术。1、全文检索技术的基本概念全文检索的基本工作方式是能够将所有包含检索词的文献检索出来，不管这个词出现在文献的什么位置；或者说文献中的任意一个词都可以作为检索到该文献的条件。全文检索是信息检索的一个分支。70、80年代得到迅速的发展，90年代以来得到广泛的应用。信息检索的核心在于在文献信息中抽取出能够表现文献的特征值，对特征值建立索引，以便于检索时…     

基于深度学习的图书馆文献自动检索机器人研究

针对当前检索机器人存在的检索速度慢、检索质量差的问题,利用深度学习算法从机械结构和检索功能两个方面,实现图书馆文献自动检索机器人的优化设计。改装机器人通信与交互模块、运动器件和视觉扫描器件,结合其工作方式,连接组成元件,完成机械结构的设计。在机器人设备的运行驱动下,完成图书馆文献资源的收集与处理任务。利用深度学习算法,提取图书馆文献特征并将其分类存储。根据输入的检索关键词,建立文献自动检索索引,通过计算关键词与文献特征之间的相似度,得出图书馆文献的自动检索结果。通过性能测试实验得出结论：设计机器人的检索召回率与准确率均高于95%,且检索时延低于80 ms,即设计机器人的检索质量与速度均满足应用要求。     

基于Spark框架的图书馆文献信息检索方法

由于传统信息检索方法检索时间长，检索误差率高，研究基于Spark框架的图书馆文献信息检索方法。首先，预处理文献信息数据，结合信息相似度，提取特征数据集合中的敏感数据获得属性特征。其次，基于Spark框架批处理数据，训练待测样本进行目标跟踪，寻找最优解集。对信息的特征进行查询，提取其中的关键词并在已建立的文本索引结构上进行检索和融合，运用K-Means聚类方法对融合结果进行重新排序。采用布尔查询机制构造文献检索模型，将不同信息数据多重倒排文献进行索引从而完成信息检索。实验结果表明，运用该方法检索时间最短，误差率最低，完成图书馆文献信息检索方法的优化。     

高校虚拟图书馆多媒体课件的设计与应用——以云南大学为例

以云南大学为例,介绍高校虚拟图书馆多媒体辅助教学软件的设计思想、开发过程以及在建构主义学习理论和认知负荷理论指导下的关键技术问题解决方法的思考和建议。内容涉及实物图书馆虚拟现实场景实现、图书文献检索和电子资源运用三个部分,以配合高校文献检索课教学,帮助学习者深入了解高校图书馆功能,掌握图书文献信息检索知识,合理使用各种电子资源库,最终达到塑造学习者信息素养的目的。     

Wiki技术在数字图书馆文献检索中的应用

针对传统数字图书馆中文献检索质量不高的问题,提出了一种基于Wiki技术的文献检索模型。该检索模型是在传统文献检索系统的基础上集成了Wiki平台及技术,采用数据挖掘算法提取文献的检索参数和用户检索兴趣特征来提高文献检索的质量。实验证明,基于Wiki的文献检索系统其回调率和查准率在总体上都比传统的有了较大的改善和提高。     

原创优先的搜索引擎排序算法

现有的搜索引擎排序算法大多根据网页之间的链接关系进行排序,没有考虑原创和转载文章之间的优先次序。该文提出一种适用于专业搜索引擎的新型排序算法,在排序时优先考虑原创文章,使原创文章的搜索排名得以提高,有助于新兴原创技术网站的发展,提高网络竞争的公平性。     

Finding story chains in newswire articles using random walks

Massive amounts of information about news events are published on the Internet every day in online newspapers, blogs, and social network messages. While search engines like Google help retrieve information using keywords, the large volumes of unstructured search results returned by search engines make it hard to track the evolution of an event. A story chain is composed of a set of news articles that reveal hidden relationships among different events. Traditional keyword-based search engines provide limited support for finding story chains. In this paper, we propose a random walk based algorithm to find story chains. When breaking news happens, many media outlets report the same event. We have two pruning mechanisms in the algorithm to automatically exclude redundant articles from the story chain and to ensure efficiency of the algorithm. We further explore how named entities and word relevance can help find relevant news articles and improve algorithm efficiency by creating a co-clustering based correlation graph. Experimental results show that our proposed algorithm can generate coherent story chains without redundancy. The efficiency of the algorithm is significantly improved on the correlation graph.     

Small treatise about e-manipulation for honest people

Information warfare is nowadays a well-known concept. However, articles are mainly split into two categories. The first one deals with how information must be managed in a system (e.g. a company or a state), in order to achieve information dominance, that is providing more and better information than the others so that they have to follow what is produced. The second one is more on how information can be used as a weapon. Dominance is one goal, but not the only one: deception, intoxication or misinformation are others. In this article, we chose the second approach. The goal when using information as a weapon is to influence a target so that it does what the attacker wants, or to cause effects. We chose also to focus on a specific battlefield: Internet. One particularly important aspect of the Internet is that it is both a container and contents. For instance, web sites are providing articles, but they are also some servers, referenced by search engines. As such, we combined this duality to increase the effects of the operations given as example. We illustrate the operation through examples, where both information is created, but also its container is improved. We show how Search Engine Optimization can be used for information warfare. Combining oriented action techniques and information based techniques make each of them much more efficient. This article shows how information warfare can be conducted on Internet. The goal is to illustrate how very few people can organize an information based attack, targeting either a company or a state for instance.     

多媒体互联网信息搜索技术探析

近几十年来,互联网技术的飞速发展加快了信息流通的速度,现代社会已经进入到信息时代。能够利用互联网技术进行信息搜索,已经成为现代人必备的基本素质和能力。手机、平板电脑、互动电视等多媒体技术的发展,使得多媒体互联网搜索技术在社会各行各业中广泛应用,极大地改变了社会的信息流通状况。目前人们越来越多地利用互联网信息资源来满足自身信息的需求,因此,互联网信息检索日益发展成为社会的主流。主要介绍互联网信息搜索引擎的共组原理以及多媒体互联网的信息搜索技术,为相关研究人员提供参考。     

面向信息检索的藏文文本索引策略研究

互联网文本数量持续爆炸式增长,用户通过互联网查找信息变得更加困难,响应时间得不到满足。针对藏文本身的语言学特点,探讨一种面向信息搜索的藏文文本索引建立策略,建立一种高效的藏文文本索引,以提高藏文信息检索速度。     

The Internet and Tobacco Cessation: The Roles of Internet Self-Efficacy and Search Task on the Information-Seeking Process

This study explores the effects of Internet self-efficacy and search task specificity on the self-efficacy outcome and task perseverance of finding online health-related sites that contain attributes of website accountability, as established by the American Medical Association (AMA). In a mixed 2 (self-efficacy) x 2 (search task specificity) repeated-measures experimental design, participants conducted two search tasks (general and specific) that varied in the amount of task difficulty. When search task specificity was taken into account, there was an Internet self-efficacy and task specificity interaction according to which high Internet self-efficacy participants locate sites higher in website accountability in the general search task (the more difficult search task) than their low self-efficacy counterparts. There was no significant difference in website accountability for the specific search task (the less difficult task). High Internet self-efficacy participants also demonstrated more task perseverance than their low Internet self-efficacy counterparts.     

Federating diverse collections of scientific literature

The Digital Library Initiative (DLI) project at the University of Illinois at Urbana-Champaign is developing the information infrastructure to effectively search technical documents on the Internet. The authors are constructing a large testbed of scientific literature, evaluating its effectiveness under significant use, and researching enhanced search technology. They are building repositories (organized collections) of indexed multiple-source collections and federating (merging and mapping) them by searching the material via multiple views of a single virtual collection. Developing widely usable Web technology is also a key goal. Improving Web search beyond full-text retrieval will require using document structure in the short term and document semantics in the long term. Their testbed efforts concentrate on journal articles from the scientific literature, with structure specified by the Standard Generalized Markup Language (SGML). Research efforts extract semantics from documents using the scalable technology of concept spaces based on context frequency. They then merge these efforts with traditional library indexing to provide a single Internet interface to indexes of multiple repositories     

基于Scrapy的房屋租赁信息搜索系统设计与实现

在如今互联网技术蓬勃房展及高房价的背景下，越来越多的人通过互联网寻找合适的租赁房源。目前互联网上房屋租赁网站众多，租房者在每家网站上均需要单独注册登录，且查询搜索过程繁琐，用户体验不佳。该文基于scrapy开源爬虫框架设计并实现了一个房屋租赁信息搜索系统，该系统从多个房屋租赁网站采集房源信息，进行数据格式转换后，向用户提供统一且多样化的房源搜索及展示功能。     

A statistical method for estimating the usefulness of text databases

Searching desired data on the Internet is one of the most common ways the Internet is used. No single search engine is capable of searching all data on the Internet. The approach that provides an interface for invoking multiple search engines for each user query has the potential to satisfy more users. When the number of search engines under the interface is large, invoking all search engines for each query is often not cost effective because it creates unnecessary network traffic by sending the query to a large number of useless search engines and searching these useless search engines wastes local resources. The problem can be overcome if the usefulness of every search engine with respect to each query can be predicted. We present a statistical method to estimate the usefulness of a search engine for any given query. For a given query, the usefulness of a search engine in this paper is defined to be a combination of the number of documents in the search engine that are sufficiently similar to the query and the average similarity of these documents. Experimental results indicate that our estimation method is much more accurate than existing methods.     

一个基于MAS的搜索引擎模型

在巨大的Internet/Web信息中很难积极地搜索到准确的信息,搜索引擎技术解决了用户检索Web信息困难的问题,而现有的搜索引擎返回的信息却并不总令用户满意。文中在对MAS理论调研的基础上,提出一个基于MAS的搜索引擎的模型,并将其与著名的Google搜索引擎作比较和分析。