From tabular data to knowledge graphs: A survey of semantic table interpretation tasks and methods

Tabular data often refers to data that is organized in a table with rows and columns. We observe that this data format is widely used on the Web and within enterprise data repositories. Tables potentially contain rich semantic information that still needs to be interpreted. The process of extracting meaningful information out of tabular data with respect to a semantic artefact, such as an ontology or a knowledge graph, is often referred to as Semantic Table Interpretation (STI) or Semantic Table Annotation. In this survey paper, we aim to provide a comprehensive and up-to-date state-of-the-art review of the different tasks and methods that have been proposed so far to perform STI. First, we propose a new categorization that reflects the heterogeneity of table types that one can encounter, revealing different challenges that need to be addressed. Next, we define five major sub-tasks that STI deals with even if the literature has mostly focused on three sub-tasks so far. We review and group the many approaches that have been proposed into three macro families and we discuss their performance and limitations with respect to the various datasets and benchmarks proposed by the community. Finally, we detail what are the remaining scientific barriers to be able to truly automatically interpret any type of tables that can be found in the wild Web.     

基于四元数胶囊网络的知识图谱补全模型

知识图谱采用RDF三元组的形式描述现实世界中的关系和头、尾实体,即（头实体,关系,尾实体）或（主语,谓语,宾语）。为补全知识图谱中缺失的事实三元组,将四元数融入胶囊神经网络模型预测缺失的知识,并构建一种新的知识图谱补全模型。采用超复数嵌入取代传统的实值嵌入来编码三元组结构信息,以尽可能全面捕获三元组全局特性,将实体、关系的四元数嵌入作为胶囊网络的输入,四元数结合优化的胶囊网络模型可以有效补全知识图谱中丢失的三元组,提高预测精度。链接预测实验结果表明,与CapsE模型相比,在数据集WN18RR中,该知识图谱补全模型的Hit@10与正确实体的倒数平均排名分别提高3.2个百分点和5.5%,在数据集FB15K-237中,Hit@10与正确实体的倒数平均排名分别提高2.5个百分点和4.4%,能够有效预测知识图谱中缺失的事实三元组。     

Knowledge context,learning and innovation: an integrating framework

Abstract

In this conceptual paper, we develop a framework which identifies those elements of firms’ knowledge context which are important for innovation, and the mechanisms through which that knowledge impacts on firms’ innovation performance. We make four main contributions to the existing literature. First, our characterisation of knowledge context provides the basis for a more specific identification of which elements of firms’ knowledge environment are important for innovation, discriminating between spatial, sectoral and network influences. Second, we reflect the role of innovation ambition in shaping firms’ knowledge search strategies. Third, we differentiate between firms’ interactive and non-interactive knowledge search activities and recognise that these may be complemented by unanticipated and serendipitous knowledge spillovers. Finally, we employ the notion of encoding capacity to reflect firms’ internal ability to assimilate and apply external knowledge, and clarify its distinctiveness from the more general concept of absorptive capacity. Our framework provides an integrating mechanism for existing empirical studies, and suggests a number of new research directions related to the determinants of innovation performance and the heterogeneity of innovation outcomes.     

Modal Pure Type Systems

We present a framework for intensional reasoning in typed -calculus. In this family of calculi, called Modal Pure Type Systems (MPTSs), a propositions-as-types-interpretation can be given for normal modal logics. MPTSs are an extension of the Pure Type Systems (PTSs) of Barendregt (1992). We show that they retain the desirable meta-theoretical properties of PTSs, and briefly discuss applications in the area of knowledge representation.     

IPv6中的邻居发现协议——NDP功能浅析

介绍了IPv6中的邻居发观协议的功能,并且详细阐述了知何利用ICMPv6中的信息控制报文来实现这些功能.     

分布式结构在IP网络管理中的应用

计算机网络被日益广泛地应用,越来越深入地影响着人类的生活。随着网络规模的不断扩大,管理维护网络的任务变得越来越困难。传统的网络管理系统采用集中式结构,已经不能适应现在普遍存在的大型网络的管理需要。当前存在三种典型网络管理体系结构:集中式、分布式、分层式,通过分析比较三种结构的优缺点,可以看出分布式结构拥有最多的忧点,非常适应当前大型网络管理的需要。本文介绍了一种分布式结构的实现方式。通过选举机制,通过拓扑发现节点之间维持一种动态的主从关系,并且系统对自身节点的故障有检测手段和一定的处理措施,从而大大增强了系统的健壮性。     

IPv4&IPv6共存网络隧道发现方法研究

本文对当前IPv4&IPv6共存网络中的隧道技术进行分析,提出一套改进型的基于源路由单点探测的骨干网隧道发现方法。该方法根据路径中双栈节点间的跳数变化和PMTU变化情况发现隧道,可以发现骨干网络交叉链路中的多级隧道。这对进一步研究过渡时期的网络拓扑发现技术具有一定的参考价值。