信息化办公与女工网信息管理系统

信息化办公正在逐步取代过去老的办公模式。文章以信息化建设在中小企业科学管理中的重要性为起点,以制作架设女工网管理系统为背景,详细阐述了油田通信女工网办公管理系统的具体设计编写实现过程和系统高效安全运行机制的编写过程。     

Cognitive Support: Extending Human Knowledge and Processing Capacities

The idea of aiding as cognitive support is to offer the user the knowledge he or she is missing. Recently, we developed a design method for aiding that is based on explicit requirements of the human problem solver. This proved to be able to supplement a lack of human knowledge in a statistical analysis task. In this article we extend the aiding concept to time-pressured tasks and we investigate whether aiding can supplement lack of knowledge and capacity under tasks with high mental loading, such as dealing with irregularities in process control. We developed a simulator of the workplace of a railway traffic controller with an aiding function for dealing with irregularities (e.g., a switch getting out of order). Application of the design method proved to be possible for this task. We then conducted an experiment to study effects of the aiding on task performance, mental effort, and learning under low and high task load conditions. Users of the simulator dealt better and faster with irregularities when the computer provided aiding. The higher the task load was, the larger this beneficial effect was. For theory about human-computer interaction, this research points to possible positive effects of aiding on performance and learning as a consequence of reducing cognitive demands.     

In Search for the Perfect Pathway: Supporting Knowledge Work of Welfare Workers

This paper investigates the collaborative practices and computational artifacts that welfare workers use in a public welfare agency. Specifically, the paper focuses on caseworkers’ knowledge practices related to assessing unemployed citizens and identifying ‘perfect’ pathways. I draw upon an ongoing ethnographic study, carried out in one of the largest municipal jobcentres in Denmark. Findings from this research point out that existing computational artifacts support compliance with welfare policy, while limited support is provided to caseworkers in helping citizens obtain an employment. The contribution of the paper is three-folded: 1) identifying fundamental characteristics of the caseworkers’ knowledge work entailed in assessing unemployed citizens and identifying appropriate pathways, 2) examining the conditions surrounding these knowledge practices, and 3) discussing implications for the design of computational artifacts that better support local knowledge practices. While maintaining support to policy compliance, I argue that computational artifacts can also support ‘data-driven knowledge’, meaning the creation of knowledge that is based on data collected from the wide range of cases of unemployed.     

信息集成与知识集成

信息集成能够有效提高信息交流、处理和反馈的效率,增强系统之间通过协作解决复杂问题的能力。实现知识集成是信息系统集成的最终目标,因为系统之间交换的数据和信息都是知识的载体,因而知识集成也最具潜力和最难于实现。文章分析了信息系统集成中的知识集成问题、方法和使能技术,并通过一个资源管理模型来进行原理验证。     

知识管理与决策支持系统

知识管理是现代企业管理理论发展的新阶段,传统的信息管理手段面临严峻的考验,已无法满足知识管理的需求。本文分析了决策支持系统在知识管理中的地位和作用,提出了基于知识管理的决策支持系统模型,并且对实现这种系统的关键技术进行了分析和评价。     

Stardust: Accessible and Transparent GPU Support for Information Visualization Rendering

Web‐based visualization libraries are in wide use, but performance bottlenecks occur when rendering, and especially animating, a large number of graphical marks. While GPU‐based rendering can drastically improve performance, that paradigm has a steep learning curve, usually requiring expertise in the computer graphics pipeline and shader programming. In addition, the recent growth of virtual and augmented reality poses a challenge for supporting multiple display environments beyond regular canvases, such as a Head Mounted Display (HMD) and Cave Automatic Virtual Environment (CAVE). In this paper, we introduce a new web‐based visualization library called Stardust, which provides a familiar API while leveraging GPU's processing power. Stardust also enables developers to create both 2D and 3D visualizations for diverse display environments using a uniform API. To demonstrate Stardust's expressiveness and portability, we present five example visualizations and a coding playground for four display environments. We also evaluate its performance by comparing it against the standard HTML5 Canvas, D3, and Vega.     

一种面向非结构化信息的知识获取框架

在文本、图片、音频等非结构化信息中蕴含着大量的知识,如何从海量非结构化信息中,自动获取这些知识是一个亟待解决的问题。该文提出一种非结构化信息知识获取框架KAFUI,该框架以非结构化信息管理架构UIMA为基础,支持异构的非结构化信息资源的接入,可整合和复用多种分析引擎,分析结果中标注了非结构化信息中的实体及其关系,这些实体和关系,进一步转换为以OWL描述的知识,并可通过推理发现新的事实。该框架的原型已在实际场景中应用,其实验情况表明是可行而有效的。     

Knowledge Discovery in Texts for Constructing Decision Support Systems

This paper presents a Text Mining approach for discovering knowledge in texts to later construct decision support systems. Text mining can take advantage of knowledge stored in textual documents, reducing the effort for knowledge acquisition. The approach consists in performing a mining process on concepts present in texts instead of working with words. The assumption is that concepts represent real world events and characteristics better than words, allowing the understanding and the explanation of the reasoning used in decision processes. The proposed approach extracts concepts expressed in natural phrases, and then analyzes their distributions and associations. Concepts distributions and associations are used to characterize classes or situations. After the discovery process, the obtained knowledge can be embedded in automated systems to classify elements or to suggest actions or solutions to problems. In this paper, experiments using the approach in a psychiatric domain are discussed. Concepts extracted from textual medical records represent patients' symptoms, signals and social/behavior characteristics. An automatic system was constructed with the approach: a classifier whose goal is to help physicians in disease diagnoses. Results from this system show that the approach is feasible for constructing decision support systems with satisfactory performance.     

Integrating Process Support and Knowledge Management for Virtual Software Development Teams

In this paper we describe how knowledge management and software process support can be integrated to improve the efficiency of virtual software teams. The approach presented here integrates a process enactment environment with an on-demand knowledge delivery strategy that is based on parameterized information needs models. The parameters in the information needs models are bound at project execution time to values extracted from the process enactment engine. Thus, the approach supports virtual teams by establishing a platform for systematic and task-specific knowledge exchange. The proposed approach is prototypically implemented in the MILOS system, an open source project of the University of Calgary (Canada) and the University of Kaiserslautern (Germany).     

A Knowledge Discovery System with Support for Model Selection and Visualization

The process of knowledge discovery in databases consists of several steps that are iterative and interactive. In each application, to go through this process the user has to exploit different algorithms and their settings that usually yield multiple models. Model selection, that is, the selection of appropriate models or algorithms to achieve such models, requires meta-knowledge of algorithm/model and model performance metrics. Therefore, model selection is usually a difficult task for the user. We believe that simplifying the process of model selection for the user is crucial to the success of real-life knowledge discovery activities. As opposed to most related work that aims to automate model selection, in our view model selection is a semiautomatic process, requiring an effective collaboration between the user and the discovery system. For such a collaboration, our solution is to give the user the ability to try various alternatives and to compare competing models quantitatively by performance metrics, and qualitatively by effective visualization. This paper presents our research on model selection and visualization in the development of a knowledge discovery system called D2MS. The paper addresses the motivation of model selection in knowledge discovery and related work, gives an overview of D2MS, and describes its solution to model selection and visualization. It then presents the usefulness of D2MS model selection in two case studies of discovering medical knowledge in hospital data—on meningitis and stomach cancer—using three data mining methods of decision trees, conceptual clustering, and rule induction.     

不完备信息系统知识获取方法在桥梁养护决策中的应用

基于相容关系和区分矩阵的知识获取算法来分析信息不完备情况下的桥梁养护决策问题,根据对不完备决策表和完备决策表知识获取结果的对照分析来验证不完备信息系统中知识获取方法的有效性。结果表明,本文所采用的不完备信息系统知识获取方法能有效地消除信息不完备所带来的知识丢失和信息过度膨胀的情况。     

基于支撑向量机的自适应信息推荐算法

提出一种新的基于支撑向量机的自适应主动推荐算法，该算法将用户模型按照层次化方式组织成领域信息和原子需求信息，考虑多用户同类信息需求，采用支撑向量机对领域信息结点中的原子需求信息进行分类协同推荐。然后再针对每一领域信息节点中的原子信息需求进行基于内容的过滤，最后将所有领域信息需求获得的推荐集按照一定的重要度等级进行推荐．本文所提算法克服了采用单一方法的弊端而使得推荐质量得到了很大的改善，基于标准测试集的测试结果表明该算法在查全率和查准率方面表现出了优越的性能，尤其适合大规模用户的自适应主动信息推荐。     

Common Body of Knowledge for Information Security

Various academic, governmental, and industrial organizations to work to develop a common body of knowledge (CBK) for the security domain. Yet, such CBKs generally focus on specific information security subdomains and thus offer narrow perceptions of the overall domain. In contrast, the authors present a CBK that addresses information security's multidisciplinary nature by incorporating knowledge and experience from fields such as management, business administration, ethics, sociology, and political science.     

Decision Support for Location Problems in Town Planning

Urban development and town planning need an adequate decision-making process. European cities, in particular, are compact. Urban elements and functions are in a constant state of change. Moreover, the large number of historic buildings and areas means a sensitive and responsible approach must be taken. The aim of this paper is to consider special location problems in town planning. We formulate multi-criteria location problems, derive optimality conditions and present a geometric algorithm and an interactive procedure including a proximal point algorithm for solving multi-criteria location problems. In this paper, we use location theory as a possible method to help determine the location of a children's playground in a newly-built district of Halle, Germany.     

信息粒度与知识系统

知识工程已被广泛地应用到信息、控制、识别、决策、经济等各个方面,是目前国内外最活跃的研究与应用领域.但是无论在方法上或应用上知识工程都遇到了很大的困难,因此从数学的角度探索知识是什么已是知识工程的瓶颈问题.陆汝钤院士指出:"知识科学中最基本的问题是研究知识的数学本质"[1].Shannon于1984年通过信息量揭示了信息的数学本质,为信息的变换提供了理论基础.揭示知识的数学本质,探索知识形成、表示与变换的原理与方法,将进一步推动知识工程的发展.     

面向信息挖掘的XML知识表示方法研究

在研究了基于XML的知识发现过程的基础上,作者提出了XML的知识表示方法。论文重点探讨了在信息挖掘的过程中,使用XML实现的三个方面知识表示:数据预处理的知识表示;挖掘算法的知识表示;挖掘结果的知识表示。最后以聚类分析为例,给出了知识表示的应用并总结了XML知识表示方法的优点。     

一种面向装备保障的信息融合功能模型

综述了当前典型的三层、四层、五层信息融合模型,在分析装备保障信息融合特点的基础上,建立了装备保障信息融合功能模型.模型对装备保障信息融合整个过程给出了较为清晰的划分,提出了信息提取、预测评估、过程精炼和综合决策四级信息融合功能,突出了人的因素在装备保障信息融合中的作用,有助于信息融合技术在装备保障领域的应用.