OpenKN: An open knowledge computational engine for network big data

Yantao Jia, Yuanzhuo Wang, Xueqi Cheng, Xiaolong Jin, J. Guo
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引用次数: 18

Abstract

With the coming of the era of big data, it is most urgent to establish the knowledge computational engine for the purpose of discovering implicit and valuable knowledge from the huge, rapidly dynamic, and complex network data. In this paper, we first survey the mainstream knowledge computational engines from four aspects and point out their deficiency. To cover these shortages, we propose the open knowledge network (OpenKN), which is a self-adaptive and evolutionable knowledge computational engine for network big data. To the best of our knowledge, this is the first work of designing the end-to-end and holistic knowledge processing pipeline in regard with the network big data. Moreover, to capture the evolutionable computing capability of OpenKN, we present the evolutionable knowledge network for knowledge representation. A case study demonstrates the effectiveness of the evolutionable computing of OpenKN.
OpenKN:面向网络大数据的开放式知识计算引擎
随着大数据时代的到来,迫切需要建立知识计算引擎,从海量、快速动态、复杂的网络数据中发现隐含的、有价值的知识。本文首先从四个方面对主流知识计算引擎进行了综述,并指出了它们的不足之处。为了弥补这些不足,我们提出了开放知识网络(OpenKN),它是一种自适应的、可进化的网络大数据知识计算引擎。据我们所知,这是第一个针对网络大数据设计端到端的整体知识处理管道的工作。此外,为了捕获OpenKN的可进化计算能力,我们提出了用于知识表示的可进化知识网络。通过实例分析,验证了OpenKN进化计算方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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