Structures and dynamics of scientific knowledge networks:An empirical analysis based on a co-word network

Co-word networks are constructed with author-provided keywords in academic publications and their relations of co-occurrence.As special form of scientific knowledge networks,they represent the cognitive structure of scientific literature.This paper analyzes the complex structure of a co-word network based on 8,190 author-provided keywords extracted from 3,651 papers in five Chinese core journals in the field of management science.Small-world and scale-free phenomena are found in this network.A large-scale co-word network graph,which consists of one major giant component and many small isolated components,has been generated with the GUESS software.The dynamic growth of keywords and keyword co-occurrence relationships are described with four new informetrics measures.The results indicate that existing concepts always serve as the intellectual base of new ideas as represented by keywords.

Dynamic models of technology management capability development based on knowledge diffusion

Technology management is recognized as a key for organizations to achieve competitiveness. How to promote an organization’s technology management capability is of great significance in creating efficiencies and achieving a competitive edge. The knowledge essence of technology management capability is introduced and then the correlation between knowledge diffusion and the development of technology management capability is discussed. Further, the basic and extended dynamic models of the development of technology management capability are constructed, and is applied into an enterprise. The results show that the dynamic models can well explain how the knowledge improves the development of technology management capability, and they can be used as an useful tool by an enterprise to promote technology management capability. Finally, the managerial implications of the models are discussed.

A dynamic knowledge base based search engine

Search engines have greatly helped us to find thedesired information from the Intemet. Most search engines use keywords matching technique. This paper discusses a Dynamic Knowledge Base based Search Engine (DKBSE), which can expand the user's query using the keywords' concept or meaning. To do this, the DKBSE needs to construct and maintain the knowledge base dynamically via the system's searching results and the user's feedback information. The DKBSE expands the user's initial query using the knowledge base, and returns the searched information after the expanded query.

Knowledge representation and rule-based solution system for dynamic programming model

A knowledge representation has been proposed using the state space theory of Artificial Intelligence for Dynamic Programming Model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block modeling method uses the modules of a six tuple to form a rule based solution model. Moreover, a rule based system has been designed and set up to solve the Dynamic Programming Model. This knowledge based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynamic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Programming Model can also be conveniently realized in computer.

Decision Model of Knowledge Transfer in Big Data Environment

A decision model of knowledge transfer is presented on the basis of the characteristics of knowledge transfer in a big data environment.This model can determine the weight of knowledge transferred from another enterprise or from a big data provider.Numerous simulation experiments are implemented to test the efficiency of the optimization model.Simulation experiment results show that when increasing the weight of knowledge from big data knowledge provider,the total discount expectation of profits will increase,and the transfer cost will be reduced.The calculated results are in accordance with the actual economic situation.The optimization model can provide useful decision support for enterprises in a big data environment.

ESKD-A New Structure of Expert System Based on Knowledge Discovery

A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and knowledge base) cooperating mechanism. With all new features, ESKD may form a new research direction and provide a great probability for solving the wealth of knowledge in the knowledge base. The general structural frame of ESKD and some sub-systems among ESKD have been described, and the dynamic knowledge base based on double-base cooperating mechanism has been emphased on. According to the result of demonstrative experi- ment, the structure of ESKD is effective and feasible.

A Solution to Knowledge Management in Networked Collaborative Design

Concerning the demands in networked collaborative innovative design, a knowledge-based collaborative design model is introduced the model of knowledge integration along with its relevant supporting techniques are presented. After illustrating the general knowledge search paradigm, a kind of dynamic user model is proposed to improve knowledge search efficiency. At last a short introduction of the system’s implementation is described.

Research on Dynamic Mathematical Resource Screening Methods Based on Machine Learning

The current digital educational resources are of many kinds and large quantities, to solve the problems existing in the existing dynamic resource selection methods, a dynamic resource selection method based on machine learning is proposed. Firstly, according to the knowledge structure and concepts of mathematical resources, combined with the basic components of dynamic mathematical resources, the knowledge structure graph of mathematical resources is constructed;according to the characteristics of mathematical resources, the interaction between users and resources is simulated, and the graph of the main body of the resources is identified, and the candidate collection of mathematical knowledge is selected;finally, according to the degree of matching between mathematical literature and the candidate collection, machine learning is utilized, and the mathematical resources are screened.

知识获取视阈下创业学习对新创企业创新绩效的影响机制——环境动态性的调节作用

新创企业需要弥补“新生弱”缺陷,在动态环境下选择适当的创业学习模式、获取创业知识,促进企业持续创新和成长。基于创业学习理论,利用288份新创企业调研问卷,构建有调节的双中介理论模型,研究创业学习与新创企业创新绩效的因果关系,探究创业知识的中介作用,同时,引入环境动态性作为创业学习影响创业知识获取的边界条件。研究结果表明:①创业认知学习和实践学习对企业创新绩效具有促进作用,加入创业知识后,其在创业认知学习、创业实践学习与企业创新绩效间均具有完全中介作用;②创业认知学习与实践学习对创业显性知识、隐性知识均具有促进作用,而创业认知学习的正向影响更大;③环境动态性在创业认知学习与创业显性知识间具有负向调节效应,而在创业实践学习与创业显性知识间具有正向调节效应。结论启示,新创企业要善于结合外部环境并选择有效的创业学习方式,促进创业知识获取并进一步提升企业创新绩效。

动态环境中联盟稳定性如何影响探索性创新——基于动态关系观的过程机制研究

基于动态关系观揭示动态环境中联盟稳定性对探索性创新的影响机理。研究发现:(1)联盟稳定性可以促进探索性创新,伙伴知识分享在其中起中介作用;(2)关系治理正向调节联盟稳定性与伙伴知识分享关系,契约治理正向调节联盟稳定性与探索性创新关系;(3)环境动态性、治理机制与联盟稳定性三重交互对伙伴知识分享与探索性创新具有不同作用。当环境动态性程度高时,关系治理对联盟稳定性与伙伴知识分享的正向调节作用消失,而契约治理对联盟稳定性与伙伴知识分享的负向调节作用显现。与此同时,契约治理对联盟稳定性与探索性创新的正向调节作用消失,而关系治理对联盟稳定性与探索性创新的负向调节作用显现,不同治理机制有效性均会减弱。同样,伙伴知识分享的中介作用机制也会逐渐减弱。探讨联盟稳定性的价值情境,可为企业进行联盟构建与治理、促进探索性创新提供理论依据。

赋能政府数据开放知识创造——动态能力之探测—规则—反应

[目的/意义]研究动态能力如何赋能政府数据开放(Open Government Data, OGD)的知识创造,有助于深度理解其动态能力作用过程并持续推动OGD发展。[方法/过程]结合复杂适应系统(Complex Adaptive System, CAS)理论与知识创造的SECI模型,将OGD动态能力的作用过程分解为“探测—规则—反应”3个环节,构建基于CAS-SECI的OGD动态能力作用过程模型,通过焦点小组访谈法深入分析OGD动态能力作用的知识创造内核,并对OGD动态能力作用过程进行分解。[结果/结论]OGD变化感知能力、吸收转化能力、沟通交流能力及重构创新能力在“探测—规则—反应”过程中,通过知识社会化、外部化、组合化和内部化中的相关知识活动及流程,实现知识资本转化,系统反映了OGD动态能力作用的知识创造过程。着眼于对相关知识活动的实施和优化,提出强化探测、关注积累、加强交流、聚焦创新方面的对策建议。

知识引导的森林火灾逃生路网动态生成方法

规划合理的森林火灾逃生路网对应急逃生决策具有重要作用,但现有方法动态适应性弱,且未考虑山沟地带、狭窄山脊等影响人员逃生安全的关键空间信息,导致逃生路网规划准确性差。因此,本文引入智能化测绘技术方法,提出一种知识引导的森林火灾逃生路网动态生成方法,通过突破森林火灾逃生路网规划知识图谱构建、关键空间区域提取等关键技术,建立森林火灾逃生路网通行栅格网络模型,实现改进A*算法的逃生路网动态优化生成,研发原型系统并开展试验分析。结果表明,本文方法能够实现林火蔓延环境下逃生路网的动态生成,可为扑救人员提供有效的逃生决策信息;逃生规划准确率与已有静态森林火灾逃生路网规划方法的逃生规划准确率相比,高安全区重叠率提升了3.06%,逃生路网危险区重叠率降低了27.39%。

基于双粒度语义特征与异质性网络的知识共创价值识别

[研究目的]旨在优化虚拟社区中知识共创价值的识别方法,缓解因信息过载和关联复杂性等导致的高价值性知识资源识别效果不佳的问题。[研究方法]从知识共创的动态协同过程入手,构建集成双粒度语义与异质性网络的知识共创价值识别模型(DGSHAN)。首先利用BERT、Sentence-BERT并行获取词、句双粒度知识单元的语义信息,继而引入CNN、BiLSTM差异化提炼协同知识的局部内核特征与动态时序特征;同时采用HAN处理异质性关联网络,挖掘用户交互下多类型实体与拓扑结构中的关联规律,最后融合知识资源组合和用户行为互动双链路特征,实现知识共创价值的有效识别。[研究结论]经魅族社区Flyme数据验证,该模型的识别准确度、宏F1、加权F1分别为82.16%、73.56%、81.39%,相较于其他基线模型,各评估指标都有显著提高,可以有效提升知识共创价值的识别效果。

融合动态掩码注意力与多教师多特征知识蒸馏的文本分类

知识蒸馏技术可以将大规模模型中的知识压缩到轻量化的模型中,在文本分类任务中实现更高效的推断。现有的知识蒸馏方法较少同时考虑多种教师与多个特征层之间的信息融合。此外,蒸馏过程采用全局填充,未能动态关注数据中的有效信息。为此,该文提出一种融合动态掩码注意力机制与多教师多特征知识蒸馏的文本分类模型,不仅引入多种教师模型(RoBERTa、Electra)的知识源,还兼顾不同教师模型在多个特征层的语义信息,并通过设置动态掩码模型注意力机制使得蒸馏过程动态关注不等长数据,减少无用填充信息的干扰。在4种公开数据集上的实验结果表明,经过蒸馏后的学生模型(TinyBRET)在预测性能上均优于其他基准蒸馏策略,并在采用教师模型1/10的参数量、约1/2的平均运行时间的条件下,取得与两种教师模型相当的分类结果,平均准确率仅下降4.18%和3.33%,平均F 1值仅下降2.30%和2.38%。其注意力热度图也表明动态掩码注意力机制切实加强关注了数据尾部与上下文信息。

简短关联可编辑环签名及其区块链修正应用

关联可编辑环签名(LRRS)可提升区块链的匿名性,防止双花攻击,修正区块链数据,但其签名大小随环成员的增多而增大。针对该问题,结合已有LRRS和简短关联环签名方案,利用动态累加器对环成员的公钥进行累加计算,依据原知识证明签名(SPK)构造出新的SPK,提出简短LRRS(SLRRS)方案,基于该签名又提出新的区块链修正协议。在随机谕言机模型下,证明所提签名具有不可伪造性、匿名性、关联性。性能评估表明:随着环成员的增多,已有签名的大小在增大,而所提签名不变;同时此类签名所消耗的时间均在增多,而所提签名的时间增速较缓且最少。

基于层次结构图的多跳知识图谱问答模型

知识图谱问答(KBQA)旨在理解用户的自然语言问句,在结构化的知识图谱中通过检索、推理等手段来获取答案实体。近年来,多跳KBQA备受关注,然而,复杂问句中通常存在多个关系意图,已有KBQA方法大多忽视了推理关系链的关系顺序问题。为此,提出一种基于层次结构图的多跳知识图谱问答模型(HSG-KBQA),建模自然语言问句的关系层次顺序,指导模型在每个推理步选择合理的关系意图。设计一种层次结构图,显式地体现问句中关系的层次距离,利用LSTM-BiGCN编码层将词语间的依存信息编码到问句中;提出虚拟节点的概念,利用图池化技术过滤不重要的节点,学习推理过程中知识图谱的状态;设计基于注意力机制和层次权重的解码器来优化指令生成,使推理指令更匹配问句中的关系链顺序。实验结果表明,HSG-KBQA在WebQuestionsSP数据集上取得了71.3%的Hits@1分数,在PathQuestions数据集上取得了97.3%(PQ-2H)和89.7%(PQ-3H)的Hits@1分数,均优于对照基准模型,表明HSG-KBQA模型在KBQA任务中具有更好的性能。

智库知识服务发展机制的系统动力学仿真分析——以中国科协为例

文章基于系统动力学的智库知识服务发展机制理论模型,以中国科学技术协会为例,借助VensimPLE软件识别模型中的关键要素及相互关系,建立适用于中国特色新型智库知识服务发展机制的仿真模型,这对验证模型的可行性和有效性具有重要的理论与实践意义。仿真分析结果显示:该修正模型是由客户知识服务需求、智库知识服务能力、智库知识服务创新思想和智库知识服务生态系统等四个关键要素组成。其中,客户知识服务需求是智库知识服务发展的驱动力,推动智库知识服务创新思想的产生和知识服务能力的提升;智库知识服务能力是满足客户知识服务需求和产生智库知识服务创新思想的保障条件,是通过应用各种知识服务模式培育的;智库知识服务生态系统是推动智库知识服务可持续发展的统一整体,且通过智库知识服务创新思想不断向客户提供专业化、全球化和品牌化的知识服务,促进客户不断产生新的知识服务需求。

政府资助与企业研发投入:影响机制和效应分析

本文通过将政府资助政策纳入企业研发决策过程,拓展了传统的R&D投资模型,利用中国创新企业调查数据,基于多时点DID方法,分析了政府资助影响企业研发投入的作用机制和效应。研究结果显示,政府资助能够激励企业增加研发部门的投资比例,对企业研发投入存在“激励效应”,在非高新技术行业的影响效应更为明显;政府资助提升企业研发投入的作用机制在于通过引导企业开展创新活动,企业研发过程存在“干中学”效应,企业的知识存量水平增加,从而对企业研发投入产生动态影响。本文研究为更好发挥政府资助政策对企业创新的激励作用,以及设计有针对性的创新扶持政策,提供了一定借鉴和启示。