社会资本对知识共享意愿影响的实证研究

通过对126家企业IT员工的问卷调查,研究了自我效能、乐于助人、注重形象、互惠感等社会资本要素对员工知识共享意愿的影响.分析结果表明,乐于助人和互惠感对显性知识共享意愿和隐性知识共享意愿都产生了显著的正向影响,而自我效能对知识共享意愿的影响不显著,注重形象对显性知识共享意愿的影响是负面的,对隐性知识共享意愿则没有影响.研究结论对企业知识共享实践具有重要参考意义.     

基于多层次关联规则挖掘的反恐情报跨层特征关联分析

【目的/意义】为了发现更全面、更具有普适性的反恐情报信息,本文在单层次关联规则挖掘的基础上研究 反恐情报的多层次关联规则挖掘方法。【方法/过程】根据反恐情报的数据特征提出统一最小支持度和多单项最小 支持度参数并用的方式筛选多层次涉恐特征频繁项集,在情报分析过程中保存部分特殊的冗余频繁项集、冗余多 层次关联规则和无趣多层次关联规则。【结果/结论】本文的研究可以发现涉恐数据中不同概念分层的关联规律。 [创新/局限] 文中提出的关联分析方法能够弥补普通的单层次关联规则挖掘在分析包含多层属性的涉恐数据中存 在的不足,为反恐预警和反恐决策提供更丰富、更科学、覆盖范围更广的参考。     

Multi-person decision analysis in large scale systems—group decision making

This paper treats the problem of amalgamating the preference orderings of individuals into an overall preference ordering for the society comprised of those individuals. A mathematical rule for doing this is known as a “social welfare function”. The imposition of five seemingly desirable conditions on the social welfare function leads to Arrow's Impossibility Theorem, which states that there is no function which satisfies these five conditions. To circumvent this problem, several proposed restrictions on the social welfare function are discussed. The concept of decentralized group decision making, in which the members of the group are arranged in a hierarchical structure, is described. Here decision making takes place within subgroups and then the subgroups are treated as individuals in the decision making process for the group as a whole. Conditions under which decentralized decision making leads to the same results as centralized decision making are stated and proved.     

基于概念格的应急知识挖掘模型研究

本文提出一个面向增值的应急知识挖掘模型。以形式概念分析和概念格理论为基础,建立应急知识形式背景和应急知识概念格,通过格上作业,发现应急知识定域隐含的知识关系,达到应急知识增维的目的。实证结果表明,该模型具有良好的应急知识挖掘表现,所获得的高维应急知识能在一定程度上给下次同类型突发事件的应对提供启迪。     

A unified perspective on decision making and decision support systems

The lack of consensus on the meaning and role of decision support systems (DSSs), in the market and in academia, indicates that DSS as a field is not maturely defined and modeled. Moreover, an integrated view of the field is necessary to assess the role and value of DSS products and services. Such a view is also a prerequisite for understanding the issues of integration, as well as the potential contributions of artificial intelligence (AI) and expert systems (ES). This paper presents a unified and dynamic model showing the relationships of knowledge, information, decision, and action in the decision process. DSS modeling is viewed as a logical deduction of the utility (goal) structure. Using the framework of the model, the sequence and phases of decision making are revised. The concept of situation model is introduced. Four categories of information are addressed: instruction, historical, predicted value of alternatives, and patterns. The role of existing and potential support systems and their evolution toward utilization of ES and AI are discussed.     

基于决策列表的客户响应模型研究

决策列表是进行数据分析和数据挖掘的重要方法,一般用于形成公司决策和模型预测。文章介绍了决策列表、关联规则及其客户响应模型的构建,然后将决策列表算法应用于金融机构营销计划的实施中,通过对历史数据分析得到一些较为实用的预测性客户属性规则,提高销售效率。     

Optimal local sensor decision rule for target detection with channel fading statistics in multi-sensor networks

In this paper, we investigate the optimal local sensor decision rule based on non-ideal transmission channels between local sensors and the fusion center for distributed target detection system. The optimality of a likelihood-ratio test (LRT)-based local decision rule at local sensor, which requires only the knowledge of channel statistics instead of instantaneous channel state information (CSI), is established. The coupled local decision rule at each sensor is derived in a closed-form for coherent BPSK and OOK and non-coherent OOK. The iterative person-by-person optimization (PBPO) algorithm is employed to solve the coupled local thresholds. Simulation analysis reveals that the derived thresholds according to the local decision rule are consistent to the exhaustive searching. Furthermore, the detection performance of the system with the proposed optimal local decision rule for different reception modes and modulations is analyzed and compared.     

一种基于知识仓库的决策支持体系结构模型

网络计算环境下决策支持体系模式与机制是知识管理研究与应用领域的难点与热点问题之一,文章考察了决策过程的特征和知识转化的机制,在此基础上提出了一个基于知识仓库的层次化决策支持体系模型,讨论了知识仓库的概念、结构和组成等关键实现技术。     

关联规则在贫困学生信息库的应用

本文以高校学生信息数据为研究对象,主要以贫困学生信息数据为应用点,采用数据挖掘技术挖掘学生信息中的有用知识。本文围绕挖掘贫困学生信息这个主题,运用Apriori关联规则算法对得到的综合数据信息进行挖掘,并对Apriori算法的应用进行了改进,得出了有利于学生管理部门支持决策的知识。     

The international telecommunication regime in the information age

This paper examines recent changes in the international telecommunication regime. The concept of an international regime comes from the field of international relations. Although it is not universally accepted, one of the most widely supported definitions describes an international regime as, ‘implicit or explicit principles, norms, rules, and decision‐making procedures around which actors’ expectations converge in a given area of international relations'.¹ The ‘given area’ of concern here is telecommunication. Telecommunication and the principles, norms, rules and decision‐making procedures which are relevant to it at the international level—which have been studied extensively by communications and development economics scholars²—have only rarely been the focus of international relations scholars.³ The objective of this paper is to use tools from the study of international relations to explore subject matter that has more frequently been the focus of scholars in communications, development economics, and information economics.     

技术创新网络中的知识-信息-知识作用过程研究

 本篇论文首先推广了信息概念,在此基础上建立知识与知识时空的概念,将跨组织学习的动力问题理解为信息场上某一特定知识时空与信息的相互作用,利用能量的观点来研究技术创新网络跨组织学习的绩效,将其定义为知识时空能量的产生与转移,并分析了在此过程中模糊知识与明晰知识的转化过程;严格证明了对于给定知识来说,技术创新网络中两者之间的跨组织学习比通过第三者更为有效的结论。     

粒计算及其在数据挖掘中的应用

本文分绍了信息粒及粒计算的概念．建立了粒与二进制数的对应关系。定义了粒计算与二进制教计算的相似性和互换性．因此用粒计算方法作数据挖掘被转换为用二进制计算方法来约简数据和提取关联规则。这样为我们的决策提供了速度快、效率高的挖掘方法。     

基于数据仓库技术的图书馆业务数据可视化监控平台——以厦门图书馆为例

结合图书馆自动化系统,利用数据仓库技术建立图书馆服务可视化监控平台开展图书馆数据中隐性信息的深度挖掘与可视化分析工作,是提升图书馆业务能力和水平的重要途径。通过对图书馆业务数据多维度分析和多粒度设计,采集与挖掘,设计图书馆可视化分析平台,实证了该平台在厦门图书馆的实际应用效果。     

网络关系、信任与知识共享——基于江苏高科技企业问卷调查的分析

论文将网络关系区分为工具型与私密型,将人际信任区分为认知型与情感型,将知识共享区分为显性知识共享与隐性知识共享.基于179份来自江苏高科技企业管理人员的有效问卷,运用结构方程模型对网络关系、信任与知识共享的作用机理进行实证研究.结果表明:工具型关系与私密型关系均对信任具有显著的正向作用,工具型关系对认知型信任、私密型关系对情感型信任的影响程度更高;认知型信任对隐性知识共享具有显著的正向影响,对显性知识共享作用不明显,情感型信任对显性知识共享具有显著的正向影响,对隐性知识共享作用不明显;工具型关系与私密型关系均对知识共享具有显著的正向作用,私密型关系对两类知识共享的影响程度更高.     

一种基于句法规则的文本挖掘技术的设计

文本挖掘是数据挖掘技术的一个重要方面,本文根据句法规则的特征,利用文本挖掘技术,提出基于句法规则的文本知识挖掘设计模型,从数据准备、句法规则构造、文本预处理、文本知识挖掘、挖掘结果评价等方面对工作原理进行了分析,重点阐述了句法规则的构造过程,最后通过实验验证了该模型,该设计对实现文本知识的智能化挖掘具有一定的研究意义和应用价值。     

知识管理策略与知识创造

知识创造过程是揭示显性知识和隐性知识在个体或组织中相互转化和作用从而产生新的知识的重要模型和理论。本文在分析、归纳了知识创造过程与知识管理策略的相互关系的基础上,提出了对应于不同的知识创造过程所应采用的知识管理策略。     

基于对冲作用的社交网络中口碑传播模型及控制策略研究

[目的/意义]文章旨在探究社交网络中的口碑传播规律,为现代企业应对口碑传播提供决策参考,对完善网络传播理论具有重要意义。[方法/过程]本文在经典传播模型的基础上,考虑到口碑的时效性及正、负面口碑的对冲作用,构建一种社交网络口碑传播离散模型,分析口碑的传播规律;随后,通过仿真实验分别研究了网络拓扑结构、初始传播节点的度与比例对传播过程的影响;最后,在企业宣传成本的约束条件下,提出了社交网络中负面口碑传播的最优控制策略。[结果/结论]结果表明,在匀质网络中,企业应优先提高传播正面口碑的人群数量;而在异质网络中,选择具有强影响力的媒体或公众人物传播正面口碑是企业的最优选择。     

基于Rough Set的客户群共性特征知识挖掘

运用实例数据,对挖掘客户群共性特征知识的整个过程进行了模拟。首先对获取的原始数据进行预处理,构建客户行为特征知识决策表。对各个属性两两间进行Spearman相关性分析,将具有显著相关性的属性剔除掉,然后利用Rosetta软件提供的遗传算法工具对余下的属性进行约简,并生成关联规则。最后用Accuracy(可信度)和Support(支持度)两个指标对各项规则进行筛选,得到各个客户群的共性特征知识,并对最终得到的规则进行了分析。     

Irony detection via sentiment-based transfer learning

Irony as a literary technique is widely used in online texts such as Twitter posts. Accurate irony detection is crucial for tasks such as effective sentiment analysis. A text’s ironic intent is defined by its context incongruity. For example in the phrase “I love being ignored”, the irony is defined by the incongruity between the positive word “love” and the negative context of “being ignored”. Existing studies mostly formulate irony detection as a standard supervised learning text categorization task, relying on explicit expressions for detecting context incongruity. In this paper we formulate irony detection instead as a transfer learning task where supervised learning on irony labeled text is enriched with knowledge transferred from external sentiment analysis resources. Importantly, we focus on identifying the hidden, implicit incongruity without relying on explicit incongruity expressions, as in “I like to think of myself as a broken down Justin Bieber – my philosophy professor.” We propose three transfer learning-based approaches to using sentiment knowledge to improve the attention mechanism of recurrent neural models for capturing hidden patterns for incongruity. Our main findings are: (1) Using sentiment knowledge from external resources is a very effective approach to improving irony detection; (2) For detecting implicit incongruity, transferring deep sentiment features seems to be the most effective way. Experiments show that our proposed models outperform state-of-the-art neural models for irony detection.     

流程正式化一定妨碍创造力吗——知识治理与环境不确定性的作用

基于组织设计和知识治理理论,在动态不确定性环境下,企业流程正式化、知识治理机制与外部环境的有效交互对新产品创造力有积极的影响。在直接检验流程正式化与新产品创造力关系的基础上,深入分析并检验了两种不同类型知识治理与外部环境的相互作用对上述关系的调节作用。以206家中国企业为研究对象的实证结果发现：流程正式化正向促进新产品创造力;正式知识治理负向调节流程正式化与新产品创造力之间的关系,而非正式知识治理正向调节流程正式化与新产品创造力之间的关系;流程正式化、正式知识治理与环境不确定性的三项交互与新产品创造力正相关。研究结论不仅揭示了正式流程影响创造力的作用机理,并明确了这一影响过程的边界条件。