本文選題：科研創(chuàng)新網(wǎng)絡　切入點：知識增長　出處：《圖書情報工作》2017年11期 　論文類型：期刊論文

【摘要】：[目的/意義]從知識主體吸收知識的認知視角出發(fā),研究科研創(chuàng)新網(wǎng)絡中知識動態(tài)增長的演化規(guī)律以及影響機制,引入復雜網(wǎng)絡理論,構建基于科研創(chuàng)新網(wǎng)絡的知識增長過程模型。[方法/過程]考慮科研創(chuàng)新網(wǎng)絡中知識主體獲取知識的空間結構和認知特征,基于對數(shù)透視法則將網(wǎng)絡中實際的知識物理分布轉換為知識主體自身的認知空間;在分析知識吸收過程中相關影響因素的基礎上,深入理解知識動態(tài)增長的流動模式構建知識增長函數(shù),并從效率和公平相匹配角度界定知識增長的績效。[結果/結論]科研創(chuàng)新網(wǎng)絡中的知識增長績效受網(wǎng)絡結構隨機化程度的影響呈現(xiàn)先下降后上升的趨勢;知識主體具備適度的知識傳播能力和吸收能力才能實現(xiàn)網(wǎng)絡中最優(yōu)的知識累積效應;主體獲取知識的認知過程受對數(shù)法則的約束,且隨著其認知半徑的增大,網(wǎng)絡的知識增長績效越高。
[Abstract]:[objective / significance] from the cognitive perspective of knowledge absorption by knowledge subject, the evolution law and influence mechanism of knowledge dynamic growth in scientific research innovation network are studied, and the complex network theory is introduced. The model of knowledge growth process based on scientific research innovation network is constructed. [method / process] considering the spatial structure and cognitive characteristics of knowledge acquisition in scientific research innovation network, Based on the logarithmic perspective rule, the physical distribution of knowledge in the network is transformed into the cognitive space of the knowledge subject itself, and based on the analysis of the related factors in the process of knowledge absorption, Deeply understand the flow pattern of knowledge dynamic growth, construct knowledge growth function, The performance of knowledge growth is defined from the point of view of matching efficiency and fairness. [results / conclusion] the performance of knowledge growth in scientific research innovation network is affected by the degree of randomization of network structure. In order to realize the optimal knowledge accumulation effect in the network, the knowledge agent has the moderate ability of knowledge transmission and absorption, and the cognitive process of knowledge acquisition is restricted by the logarithmic law and increases with the increase of its cognitive radius. The higher the knowledge growth performance of the network.
【作者單位】： 武漢大學信息資源研究中心;
【基金】：國家自然科學基金項目“科研團隊動態(tài)演化規(guī)律研究”(項目編號:71273196) 山東省重點研發(fā)計劃項目“可定制大數(shù)據(jù)知識服務平臺關鍵技術研究及應用”(項目編號:2015GGX101037)研究成果之一
【分類號】：F272;F273.1

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