面向網(wǎng)絡大數(shù)據(jù)的知識融合方法綜述
發(fā)布時間：2018-07-22 17:22
【摘要】：網(wǎng)絡大數(shù)據(jù)是指"人、機、物"三元世界在網(wǎng)絡空間中交互、融合所產(chǎn)生并在互聯(lián)網(wǎng)上可獲得的大數(shù)據(jù).網(wǎng)絡大數(shù)據(jù)中蘊含豐富的知識資源,包括描述特定事物的實體、刻畫實體邏輯聯(lián)系的關(guān)系、用于語義標注實體的分類等.知識自身呈現(xiàn)出異質(zhì)性、多元性和碎片化等特點.如何在網(wǎng)絡大數(shù)據(jù)環(huán)境下海量碎片化的數(shù)據(jù)中提取出能夠用于解決問題的知識,并對知識進行有效的融合計算,將從網(wǎng)絡大數(shù)據(jù)中獲得的知識有效組織起來是知識庫構(gòu)建亟待解決的技術(shù)難點和當前研究的熱點.該文從知識融合的定義出發(fā),介紹近年來的可用于知識融合的技術(shù)和算法的最新進展,通過分類和總結(jié)現(xiàn)有技術(shù),為進一步的研究工作提供可選方案.文中首先介紹了在知識融合中用于判斷知識真?zhèn)蔚闹R評估的若干研究和評估方法;然后基于知識評估的結(jié)果,從實體擴充、關(guān)系擴充和分類擴充3個方面詳細總結(jié)了知識融合中各種可用的知識擴充方法和研究進展;探討了應用于網(wǎng)絡大數(shù)據(jù)的知識融合的總體框架;基于這些討論,總結(jié)面向網(wǎng)絡大數(shù)據(jù)的知識融合面臨的主要挑戰(zhàn)和可能解決方案,并展望了該技術(shù)未來的發(fā)展方向與前景.
[Abstract]:Network big data refers to the big data generated by the interaction and fusion of "people, machines, and objects" in cyberspace and available on the Internet. The network big data contains abundant knowledge resources, including describing the entities of specific things, characterizing the relations of entity logical relations, and classifying entities for semantic annotation. Knowledge itself presents the characteristics of heterogeneity, pluralism and fragmentation. How to extract the knowledge which can be used to solve the problem from the massive fragmentation data in the network big data environment, and carry on the effective fusion computation to the knowledge, Effectively organizing the knowledge gained from the network big data is the technical difficulty and the hot spot of the current research to construct the knowledge base. Starting from the definition of knowledge fusion, this paper introduces the latest progress of the technologies and algorithms available for knowledge fusion in recent years. By classifying and summarizing the existing technologies, it provides an alternative scheme for further research work. This paper first introduces some research and evaluation methods of knowledge assessment used in knowledge fusion to judge knowledge authenticity, and then extends from entity based on the results of knowledge assessment. In this paper, three aspects of relationship expansion and classification expansion are summarized in detail, and the available methods and research progress of knowledge expansion in knowledge fusion are summarized in detail, the general framework of knowledge fusion applied to network big data is discussed, and based on these discussions, This paper summarizes the main challenges and possible solutions of knowledge fusion for network big data, and looks forward to the future development direction and prospect of the technology.
【作者單位】： 中國科學院信息工程研究所;中國科學院計算技術(shù)研究所;
【基金】：國家科技支撐計劃(2012BAH46B03) 核高基項目(2013ZX01039-002-001-001) 國家重點研發(fā)計劃(2016YFB1000902) 國家自然科學基金(61602467,61303056,61402442,61402464,61572469,61572473,61502478) 北京市自然科學基金項目(4154086)資助~~
【分類號】：TP311.13
，
本文編號：2138197
[Abstract]:Network big data refers to the big data generated by the interaction and fusion of "people, machines, and objects" in cyberspace and available on the Internet. The network big data contains abundant knowledge resources, including describing the entities of specific things, characterizing the relations of entity logical relations, and classifying entities for semantic annotation. Knowledge itself presents the characteristics of heterogeneity, pluralism and fragmentation. How to extract the knowledge which can be used to solve the problem from the massive fragmentation data in the network big data environment, and carry on the effective fusion computation to the knowledge, Effectively organizing the knowledge gained from the network big data is the technical difficulty and the hot spot of the current research to construct the knowledge base. Starting from the definition of knowledge fusion, this paper introduces the latest progress of the technologies and algorithms available for knowledge fusion in recent years. By classifying and summarizing the existing technologies, it provides an alternative scheme for further research work. This paper first introduces some research and evaluation methods of knowledge assessment used in knowledge fusion to judge knowledge authenticity, and then extends from entity based on the results of knowledge assessment. In this paper, three aspects of relationship expansion and classification expansion are summarized in detail, and the available methods and research progress of knowledge expansion in knowledge fusion are summarized in detail, the general framework of knowledge fusion applied to network big data is discussed, and based on these discussions, This paper summarizes the main challenges and possible solutions of knowledge fusion for network big data, and looks forward to the future development direction and prospect of the technology.
【作者單位】： 中國科學院信息工程研究所;中國科學院計算技術(shù)研究所;
【基金】：國家科技支撐計劃(2012BAH46B03) 核高基項目(2013ZX01039-002-001-001) 國家重點研發(fā)計劃(2016YFB1000902) 國家自然科學基金(61602467,61303056,61402442,61402464,61572469,61572473,61502478) 北京市自然科學基金項目(4154086)資助~~
【分類號】：TP311.13
，
本文編號：2138197
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