作者：YUCONG DUAN, XIAOBING SUN, HAOYANG CHE, CHUNJIE CAO, ZHAO LI, XIAOXIAN YANG
摘要：目前,伴随着物联网设备的快速增长和边缘资源的涌现,安全保护的内容不仅作为一个柔性整体强化了物联网设备网络计算和存储能力的提升，而且在可移动混合设备网络边缘，实现了DIKW内容的存储、传输和处理。然而，从统一核心概念的语义作为出发点，如何理解各种DIKW内容或资源形成了一种概念性的挑战。通过构建DIKW框架的元模型，我们提出了在概念过程中对DIKW关键元素的语义进行认知形式化。形式化以对感知世界建模为中心，仅通过关系或语义作为构成元素的基本微粒。基于认知世界模型，在概念化过程中我们揭示了关系和实体的区别，并作为一种区分数据和信息的基础。然后，按照提出的DIKW的形式化，我们展示了使用这种形式化构建针对类型资源之间类型转换的边缘计算场景的安全保护方案的基本案例。
Abstract—Currently, with the growth of the Internet of Things devices and the emergence of massive edge resources, security protection content has not only empowered IoT devices with the accumulation of networked computing and storage as a flexible whole but also enabled storing, transferring and processing DIKW (data, information, knowledge, and wisdom) content at the edge of the network from multiple devices in a mobile manner. However, understanding various DIKW content or resources poses a conceptual challenge in unifying the semantics of the core concepts as a starting point. Through building metamodels of the DIKW framework, we propose to cognitively formalize the semantics of the key elements of the DIKW in a conceptual process. The formalization centers on modeling the perceived world only by relationships or semantics as the prime atomic comprising elements. Based on this cognitive world model, we reveal the difference between relationships and entities during the conceptualization process as a foundation for distinguishing data and information. Thereafter, we show the initial case for using this formalization to construct security protection solutions for edge computing scenarios centering on type conversions among typed resources formalized through our proposed formalization of the DIKW.
作者：Yucong Duan, Lixu Shao, Gongzhu Hu, Zhangbing Zhou, Quan Zou, Zhaoxin Lin
摘要：知识图谱已被广泛采用，在很大程度上是由于它们的无模式特性，这种特性使得知识图谱可以无缝扩展，并根据需要允许添加新的关系和实体，从而提高知识图谱的点密度和边密度。知识图谱已经成为用标记的有向图形式来表示知识的强大工具，并能表达文本信息的语义。知识图谱是通过将每个项目、实体和用户作为结点表示，通过边将彼此相互作用的结点链接构造的图形。知识图谱具有丰富的自然语义，可以包含和表达更完整的信息，其表达机制接近于自然语言。然而，对于知识图谱我们仍然缺乏统一的定义和标准的表达形式。本文建议澄清知识图表的整体表达，分别从数据、信息、知识和智慧层次阐明知识图谱的架构，以渐进的方式将知识图谱定义为四种基本形式，包括数据图谱、信息图谱、知识图谱和智慧图谱。
Abstract—Knowledge graphs have been widely adopted, in large part owing to their schema-less nature. It enables knowledge graphs to grow seamlessly and allows for new relationships and entities as needed. Knowledge graph has become a powerful tool to represent knowledge in the form of a labelled directed graph and to give semantics to textual information. A knowledge graph is a graph constructed by representing each item, entity and user as nodes, and linking those nodes that interact with each other via edges. Knowledge graph has abundant natural semantics and can contain various and more complete information. Its expression mechanism is close to natural language. However, we still lack a unified definition and standard expression form of knowledge graph. We propose to clarify the expression of knowledge graph as a whole. We clarify the architecture of knowledge graph from data, information, knowledge, and wisdom aspects respectively. We also propose to specify knowledge graph in a progressive manner as four basic forms including data graph, information graph, knowledge graph and wisdom graph.
作者：Lixu Shao, Yucong Duan, Xiaobing Sun, Quan Zou, Rongqi Jing, Jiami Lin
摘要：价值驱动设计通过在决策过程中运用经济学，在各级工程设计方面做出最佳的业务和技术解决方案的合理决策。为了最大化业务盈利能力，本文提出在数据图谱、信息图谱和知识图谱的基础上，将经济规划与技术实施之间的双向价值驱动设计结合起来，使用数据图谱、信息图谱和知识图谱来分析对软件开发活动产生负面影响的问题，包括需求分析、概要设计和详细设计。本文建议通过管理数据和信息重用、冗余和结构来提高系统的可靠性和鲁棒性。
Abstract—Value-Driven Design enables rational decisions to be made in terms of the optimum business and technical solution at every level of engineering design by employing economics in decision making. In order to maximize the business profitability, we propose to bridge bidirectional value driven design between economic planning and technology implementation on the basis of the data graph, information graph and knowledge graph. We use data graph, information graph and knowledge graph to analyze problems that have negative impact on activities of software development including requirement analysis, summary design and detail design. We propose to improve system reliability and robustness by managing data and information reuse, redundancy as well as structure.
作者：Lixu Shao, Yucong Duan, Xiaobing Sun, Honghao Gao, Donghai Zhu, Weikai Miao
摘要：知识图谱被广泛采用，在很大程度上是由于它们的无模式性质。以自然语言问题作为查询语言的方式提供了关键词查询和结构化查询之间的理想折衷，问题可用于表达关键词无法表达的复杂信息需求，并且不会在结构和语义上产生重大损失。自然语言问题是制定信息需求最直观的方式，用户可以通过提出自然语言问题来表达他们的信息需求。知识图谱具有丰富的自然语义，可以包含各种更完整的信息，其表达机制更接近于自然语言。本文建议澄清知识图表的整体表达，以渐进的方式将知识图谱定义为四种基本形式，包括数据图谱、信息图谱、知识图谱和智慧图谱。我们使用知识图谱来解决“5W”问题，这些问题分别是由“谁(Who)/何时(When)”，“什么(What)”，“如何(How)”以及“为什么(Why)”等疑问词引导的。
Abstract—Knowledge graphs have been widely adopted, in large part owing to their schema-less nature. It enables knowledge graphs to grow seamlessly and allows for new relationships and entities as needed. Natural language questions are the most intuitive way of formulating an information need. People can formulate questions to express their information needs. Natural language questions as a query language present an ideal compromise between keyword and structured querying. Questions can be used to express complex information needs that cannot be expressed as keywords without a significant loss in structure and semantics. Knowledge graph has abundant natural semantics and can contain various and more complete information. Its expression mechanism is closer to natural language. We propose to clarify the expression of knowledge graph as a whole.We use knowledge graph to solve the Five Ws problems respectively which are guided by interrogative words such as who/when, what, how and why. We also propose to specify knowledge graph in a progressive manner as four basic forms including data graph, information graph, knowledge graph and wisdom graph.
作者：Lixu Shao, Yucong Duan, Lizhen Cui, Quan Zou, Xiaobing Sun
摘要：随着数据挖掘技术的发展，私有资源保护的缺失已成为一个严峻的挑战。本文建议在在三个层面上明确知识图谱的表达，包括数据图谱、信息图谱和知识图谱，并分别说明数据图谱、信息图谱和知识图谱的表示。本文阐述了一种投入驱动的基于数据图谱、信息图谱和知识图谱的资源安全性保护方法，以确保资源在未经授权的情况下不会被使用、篡改、丢失和销毁
Abstract—With the development of data mining technology, lack of private resource protection has become a serious challenge. We propose to clarify the expression of Knowledge Graph in three layers including Data Graph, Information Graph and Knowledge Graph and illustrate the representation of Data Graph, Information Graph and Knowledge Graph respectively. We elaborate a pay as you use resource security provision approach based on Data Graph, Information Graph and Knowledge Graph in order to ensure that resources will not be used, tampered with, lost and destroyed in unauthorized situations.
作者：Yucong Duan，Lixu Shao，Xiaobing Sun，Donghai Zhu，Xiaoxian Yang，Abdelrahman Osman Elfaki
摘要：事务处理技术是报告信息一致性和可靠性的关键技术，决定了Web服务是否可以应用于电子商务。本文提出了一种投入驱动的事务处理方法，通过存储和计算协同调整方法实现时空优化，旨在根据用户投入满足不同用户的需求。本文研究资源建模、资源处理、处理优化和资源管理，提出了由数据图谱、信息图谱和知识图谱组成的三层架构。
Abstract—Transaction processing technology is the key technology of reporting information consistency and reliability, and determines whether web services can be applied to e-commerce. We propose an investment defined transaction processing approach towards temporal and spatial optimization with collaborative storage and computation adaptation approach aiming at satisfying requirements of different users according to their investment. We studies resource modelling, resource processing, processing optimization and resource management and puts forward a three-tier architecture consisting of Data Graph, Information Graph and Knowledge Graph.
作者：Lixu Shao, Yucong Duan, Donghai Zhu, Jingbing Li, Hui Zhou, Qi Qi
摘要：Web服务是在构建软件系统时集成组件的流行解决方案，允许系统与第三方用户之间进行通信，提供灵活和可重用的机制来访问其功能。医疗服务提供中普遍存在各种基于web服务的系统。本文基于数据图谱、信息图谱和知识图谱的层次结构提出了一个从数据、信息和知识的角度建立、检索和保护类型化健康资源的框架，并通过案例说明了框架的机制。
Abstract—Web service is a popular solution to integrate components when building a software system, or to allow communication between a system and third-party users, providing a flexible and reusable mechanism to access its functionalities. Various web service based systems are prevailing in health service provision. We propose a framework of construction, searching and protection of typed health resources in terms of data, information and knowledge through a hierarchy consisting of Data Graph, Information Graph and Knowledge Graph. We use cases to illustrate the mechanism of the framework.
作者：Zhengyang Song, Yucong Duan, Shixiang Wan, Xiaobing Sun, Quan Zou, Honghao Gao, Donghai Zhu
摘要：物联网（IoT）系统的广泛应用越来越多地要求更多的硬件设施来处理包括数据，信息和知识在内的各种资源。随着采集的资源数量的快速增长，使用传统的云计算模型很难适应这种情况。雾计算使存储和计算服务能够在网络边缘执行以扩展云计算。然而，雾计算应用依然存在一些问题，例如计算受限，存储有限以及昂贵的网络带宽，平衡网络资源的分配是一项挑战。我们提出了一种面向雾计算的存储和计算协同调整的类型资源处理优化机制。在此机制中，我们在基于无线网络的三层架构中处理类型化资源，该架构由数据图谱，信息图谱和知识图谱组成。所提出的机制旨在最小化网络，计算和存储的处理成本，同时以商业价值驱动的方式最大化处理的性能。仿真结果表明，所提出的方法提高了性能与用户投资的比率。同时，资源类型之间的转换为动态分配网络资源提供了支持。
Abstract—Wide application of the Internet of Things(IoT) system has been increasingly demanding more hardware facilities for processing various resources including data, information, and knowledge. With the rapid growth of generated resource quantity, it is difficult to adapt to this situation by using traditional cloud computing models. Fog computing enables storage and computing services to perform at the edge of the network to extend cloud computing. However, there are some problems such as restricted computation, limited storage, and expensive network bandwidth in Fog computing applications. It is a challenge to balance the distribution of network resources. We propose a processing optimization mechanism of typed resources with synchronized storage and computation adaptation in Fog computing. In this mechanism, we process typed resources in a wireless-network-based three tier architecture consisting of Data Graph, Information Graph, and Knowledge Graph. The proposed mechanism aims to minimize processing cost over network, computation, and storage while maximizing the performance of processing in a business value driven manner. Simulation results show that the proposed approach improves the ratio of performance over user investment. Meanwhile, conversions between resource types deliver support for dynamically allocating network resources.
作者：Yucong Duan, Lixu Shao, Buqing Cao, Xiaobing Sun, Lianyong Qi
摘要：事务处理技术是报告信息一致性和可靠性的关键技术，决定了Web服务是否可以应用于电子商务。类型化的数据、信息和知识等资源繁杂冗余，导致资源存储和处理效率低下，长事务的处理过程往往会持续较长时间，使得锁定资源的策略不能一直适用，为了协调事务型资源存储和计算代价，提出了一种投入驱动的事务处理方法。从资源建模、资源处理、处理优化和资源管理等角度进行研究，基于对现有知识图谱概念的拓展提出了一种三层可自动抽象调整的解决架构。这个架构包括：数据图谱、信息图谱和知识图谱等三个层面，关键在于对搜索目标资源对象类型转移代价和在资源存储空间上的存储代价的计算，并根据用户投入协同调整搜索目标资源对象的搜索机制和存储方案，从而降低资源搜索的时间复杂度和资源存储的空间复杂度，优化事务处理的时空效率。
Abstract—Transaction processing technology is a key technology for reporting information consistency and reliability, and determines whether Web services can be applied to ecommerce. Typed resources such as data, information and knowledge are complicated and redundant, resulting in low storage and processing efficiency of resources. Processing of long transactions often lasts for a long time so that the strategy of locking resources cannot always be applied. We propose an investment defined transaction processing approach towards temporal and spatial optimization with collaborative storage and computation adaptation. In terms of resource modeling, resource processing, processing optimization and resource management, we propose a threelayer solution architecture that can be automatically abstracted and adjusted based on expanding the existing concepts of knowledge graph. The architecture includes three layers that are data graph, information graph, and knowledge graph. The key lies in the calculation of type transferring cost and storage cost on the resource storage space of search target resource objects, and the adjustment of the search mechanism and storage scheme of search target resource objects according to users’ investment, thus reducing the temporal complexity of resource searching and spatial complexity of resource storage and optimizing the temporal and spatial efficiency.
作者：Yucong Duan，Jiaxuan Li，Qiang Duan，Lixin Luo，Liang Huang
摘要：经验规则是处理UML视图抽象最广泛使用的方法之一，它可以支持模型简化、一致性检查和复杂性降低。然而，经验规则面临着诸如完整性验证、规则之间的一致性以及组合优先级安排等挑战。在强调冗余信息/数据的基于Web服务的分布式模型驱动开发环境中，组合的挑战进一步扩大。相同的冗余信息可以表示为不同的形式，这些形式包括表示系统相同部分的不同拓扑结构。这种变化将导致选择以不同顺序执行的规则的不同组成，这将从某些规则的经验概率增加当前不确定性的严重性。通过设计实例模型，研究了冗余对规则应用的影响。我们构造有限状态自动机来统一经验规则，同时消除冗余造成的副作用。
Abstract—Empirical rules are among the most widely employed approaches for processing view abstraction for UML, which can support model simplification, consistency checking, and complexity reduction. However, empirical rules face challenges such as completeness validation, consistency among rules, and composition priority arrangement. The challenge of composition is enlarged in the environment of distributed model-driven development for web service-based systems, where redundant information/data is emphasised. The same redundant information can be expressed in different forms that comprise different topological structures representing the same part of the system. Such variation will result in choosing different compositions of rules executed in different orders, which will increase the severity of the current non-determinism from the empirical probability of some rules. We investigate the effect of redundancy on rule application through designing a simulated distributed storage for an example model. We construct finite-state automaton to unify empirical rules while relieving the side effects caused by redundancy.
作者：Lixu Shao，Yucong Duan，Zhangbing Zhou，Antonella Longo，Donghai Zhu，Honghao Gao
摘要：Web服务是一种流行的解决方案，用于在构建软件系统时集成组件，或者允许系统与第三方用户之间的通信，提供灵活且可重用的机制来访问其功能。由于医疗水平的差异和医疗资源分布的极度不均衡，医学信息技术缺乏统一的规划，得不到数字医疗系统的支持。因此，每个医疗机构不能共享患者的诊断资源。检查经常重复进行，不仅增加了住院和身体伤害的负担，而且导致医疗资源的浪费。本文提出了通过数据图谱、信息图谱和知识图谱的层次结构，在数据、信息和知识方面构造和搜索类型化卫生资源的框架，以提高资源访问和处理的性能。我们使用案例来说明框架的机制。
Abstract—Web service is a popular solution to integrate components when building a software system, or to allow communication between a system and third-party users, providing a flexible and reusable mechanism to access its functionalities. Due to differences in medical level and extremely uneven distribution of medical resources, medical information technology lacks unified planning and is not supported by digital health care system. Thus diagnosis resources of patients cannot be shared by each medical institution. Inspections usually repeat which not only increases the burden of hospitalizing and physical injuries, but also leads to the waste of medical resources. We propose a framework towards constructing and searching typed health resources in terms of data, information and knowledge through a hierarchy composing Data Graph, Information Graph and Knowledge Graph in order to improve performance in accessing and processing resources. We use cases to illustrate the mechanism of the framework.
作者：Yucong Duan，Lixu Shao，Xiaobing Sun，Lizhen Cui，Donghai Zhu，Zhengyang Song
摘要：互联网资源是非确定性的，不保真且极其复杂。我们针对正向和反向倾向的问题提供渐进式搜索方法，旨在通过多次渐进式搜索来提高资源的可信度。同时，我们引入知识图谱作为资源过程体系结构来组织网络资源，并分析搜索者通过语义分析检索信息的趋势。我们根据每次搜索的搜索次数和项目数量来计算资源的熵，以表示具有正面和负面趋势的资源的可靠性。在逐步搜索过程中将消除具有模糊趋势和错误信息的资源，并且将改进搜索结果的质量，同时避免搜索无限复杂问题的死循环。我们将搜索策略应用于医疗资源处理系统，为医务人员提供高精度的医疗资源检索服务，以验证我们的方法的可行性。
Abstract—Internet resources are non-deterministic, non-guaranteed and ultra-complex. We provide a progressive search approach towards problems with positive and negative tendencies aiming at improving the credibility of resources through multi times progressive searching. Meanwhile, we introduce Knowledge Graph as a resource process architecture to organize resources on the network and analyze the tendency of searchers for retrieving information by semantic analysis. We calculate entropy of resources according to searching times and amount of items of each search to represent the reliability of resources with positive and negative tendencies. Resources with ambiguous tendency and false information will be eliminated during the process of progressive search and quality of searching results will be improved while avoiding dead loop of searching towards infinite and complex problems. We apply the searching strategy to a medical resource processing system that provides high precision medical resource retrieval service for medical workers to verify the feasibility of our approach.
作者：Lixu Shao，Yucong Duan，Zhangbing Zhou，Quan Zou，Honghao Gao
摘要：互联网上海量的学习资源包含数据、信息和知识，用户在学习过程中容易迷失和混淆。自然语言的自动处理、自动合成、自动分析等资源的原始表示这些数据、信息和知识，已经成为一个巨大的挑战。提出了一种由数据图、信息图和知识图组成的三层结构，可以自动抽象和调整资源。该体系结构递归支持经验知识的集成和资源元素的高效自动语义分析，通过对数据图进行频率聚焦剖析，通过对信息图和知识图的抽象进行优化搜索。我们提出的体系结构由5W (Who/When/Where, What和How)提供支持，以满足用户的学习需求、学习过程和学习目标，为用户提供个性化的学习服务推荐。
Abstract—With massive learning resources that contain data, information and knowledge on Internet, users are easy to get lost and confused in processing of learning. Automatic processing, automatic synthesis, and automatic analysis of natural language, such as the original representation of the resources of these data, information and knowledge, have become a huge challenge. We propose a three-layer architecture composing Data Graph, Information Graph and Knowledge Graph which can automatically abstract and adjust resources. This architecture recursively supports integration of empirical knowledge and efficient automatic semantic analysis of resource elements through frequency focused profiling on Data Graph and optimal search through abstraction on Information Graph and Knowledge Graph. Our proposed architecture is supported by the 5W (Who/When/Where, What and How) to interface users’ learning needs, learning processes, and learning objectives which can provide users with personalized learning service recommendation.
作者：Lixu Shao，Yucong Duan，Zhangbing Zhou，Quan Zou，Honghao Gao
摘要：为信息技术方面的实现提供指导和直接集成，以实现连贯的数据、信息和知识协调以及鲁棒的面向价值的适应性，以实现业务利润率的最大化。我们建议利用服务经济学的思想，在应用程序接口经济中，实现无处不在的服务/XaaS的业务规划与技术实现之间的双向计算桥梁，以促进宏观服务市场的发展，特别是在全球价值链中。在价值驱动设计的启发下，我们提出了一种从价值计算到设计质量度量的系统形式化方法，通过基于无线传感器网络的服务系统创建过程中质量属性的管理框架，将设计构件的技术修改和变化与业务价值策略结合起来。在构建服务系统的过程中，我们使用数据、信息和知识流抽象各种数据、信息和知识操作与使用场景。我们建议通过管理数据和信息重用、冗余以及结构来提高系统的可靠性和鲁棒性。
Abstract—To provide guidance to and integrate directly with the information technology side implementation to achieve coherent data, information, and knowledge coordination and robust value-oriented adaptability for maximization of business profitability, we propose to leverage the ideology of service economics to achieve bidirectional computational bridging between business planning and technical implementation of ubiquitous services/XaaS in the application program interface economy for promoting the macro-service market, especially in global value chains. Enlightened by value-driven design, we propose a systemic formalization from value calculation to design quality measurement which binds the technical modification and variation on design artifacts with business value strategy through a framework of managed quality properties in a wireless sensor network–based service system creation process. In the process of building a service system, we use data, information, and knowledge flow to abstract various data, information, and knowledge manipulation and usage scenarios. We propose to improve system reliability and robustness by managing data and information reuse, redundancy as well as structure.
摘要：个性化推荐被广泛应用以加速云服务． 推荐系统旨在基于在线和离线的可用数据、信息和知识来估计给定领域的一组 对象的效用． 现有的推荐系统严重依赖基于内容的方法或协同过滤的方法来提出建议，但是它们都不能完全满足面向自然语言 语义的推荐效率和有效性． 知识图谱是一种用于直接存储容纳语义丰富的非结构化和结构化信息的知识库． 本文提出通过引入 知识图谱作为媒体层整合基于内容和协同过滤两种方法来提高推荐质量，并且通过在云环境中构建测试推荐系统展示了本文 提出方法的可行性。
Abstract—Personalized recommendation is widely deployed to accelerate the servilization in Cloud． A recommender system aims at estimating the utility of a set of objects belonging to a given domain based on available data，information and knowledge both online and offline． While existing recommender systems rely heavily on either a content-based approach or a collaborative approach to make recommendations，neither of them fully satisfy the natural language semantics oriented recommendation efficiency and effectiveness． Knowledge graph is a kind of knowledge base used to store unstructured and structured information which directly accommodate rich semantics． We propose to improve recommendation quality through the integration of both approaches by introducing knowledge graph as the media layer． We show the feasibility of our approach in construction of an examination recommender in Cloud environment．
摘要：在物联网、边缘计算和大数据智能处理高速发展的背景下,安全保护研究的内容已经从显式内容保护扩展到了对隐式内容的保护。多来源内容背景下的隐式内容的安全保护对内容的采集、识别、保护策略定制、保护方法的建模、实现都提出了新的挑战。而实际应用中对性价比的追求更加剧了解决方案的挑战性。受DIKW(Data, Information, Knowledge, Wisdom)方法启发提出将保护目标及背景内容分类为数据、信息和知识三种类型化资源。在DIKW上构建基于数据图谱(Data Graph),信息图谱(Information Graph)和知识图谱(Knowledge Graph)的类型化资源安全资源保护架构。将目标安全资源根据它们在搜索空间中的存在形式分为显式的和隐式的资源,依据不同类型资源表达所对应的表达类型转换及搜索代价差异构造了对应的安全防护方案。该方案支持在不同类型转换过程中的代价以及转换后的搜索代价的差异基础上设计并提供价值导向的安全服务。
Abstract— With the rapid development of Internet of Things, Edge Computing and intelligent Big Data processing, the content of security protection has been expanded from explicit content protection to implicit content protection. The security protection of implicit content in the context of multi-source content poses new challenges to the collection, identification, customization of protection strategies, modeling and implementation of protection methods. But in practice, the pursuit of performance/cost is adding more challenging to the solution. Inspired by the DIKW (Data, Information, Knowledge, Wisdom) method, this paper proposes to classify the target of protection content and background content into three types of resources: data, information and knowledge. A typed resource security protection architecture based on Data Graph, Information Graph and Knowledge Graph is constructed on DIKW. Target security resources are divided into explicit and implicit resources according to their existing forms in the search space, and corresponding security protection schemes are constructed according to the conversion and search cost differences corresponding to different types of resource expressions. The scheme supports the design and provision of Value Driven security solutions based on the differences of the conversion cost of different types of resources and the search cost after conversion.
摘要：海量的学习资源会引起用户在学习过程中产生认知过载和资源迷航,对数据、信息和知识等形态的资源的原始表述的自然语言的机器理解、自动处理、自动综合和自动分析等成为了巨大的挑战。从应对自动增量式结合经验知识和减少人工专家交互负担等两个方面考虑,本文从资源建模、资源处理、处理优化和资源管理等角度进行研究,基于对现有知识图谱(Knowledge Graph)概念的拓展提出了一种三层可自动抽象调整的解决架构。该架构借助从数据图谱上以实体综合频度计算为核心的分析到信息图谱和知识图谱上的自适应的自动抽象的资源优化过程支持经验知识引入和高效自动语义分析。该框架借助对应5W(谁(Who)/何时(When)/何地(Where)、什么(What)和如何(How))问题的分类接口衔接用户的学习需求等资源化描述,为用户提供个性化学习服务推荐。
Abstract— Faced with complex data, information and knowledge resources, users are easy to get lost and overloaded in the process of learning. Automated processing, automatic synthesis, and automatic analysis of natural language, such as the original representation of the resources of these data, information and knowledge, have become a huge challenge. This paper studies resource modeling, resource processing, processing optimization and resource management from the aspects of coping with automatic incremental knowledge and reducing the interaction burden of artificial experts and puts forward a three-tier solution architecture which can automatically abstract and adjust resources based on the concept extension of existing Knowledge Graph. This architecture recursively supports integration of empirical knowledge and efficient automatic semantic analysis of resource elements through frequency focused profiling on data graph and optimal search through abstraction on information graph and knowledge graph. Our proposed architecture is supported by the 5W (Who/When/Where, What and How) to interface users’ learning requirements which can provide users with personalized learning service recommendation.
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