概念层次

  • 网络concept hierarchy;conceptual level
概念层次概念层次
  1. 第四,提出了一个使用概括数据库(generalizeddatabases)和位置概念层次(concepthierarchies)的位置相关查询近似回答模型。

    Fourthly , it proposes an approximate answers model using generalized databases and the concept hierarchies based on location for mobile computing query processing .

  2. 基于不同概念层次知识发现的入侵检测系统

    IDSs Based on Variant KDD Concept Hierarchies

  3. 在概念层次上这没什么问题,但对于我们理解微软的C编译器实际是怎么做的来说没有任何帮助。

    While this is fine at a conceptual level , it makes it harder than necessary to what the Microsoft C # compiler actually does .

  4. 自动地、按需集成WebServices要求解决高层次目标规划问题和任务分解,要求集成是在概念层次上进行。

    To realize the automatic , on-demand integration of web services , it is necessary to resolve such issues as the high-level task decomposing and the goal planning at the concept level .

  5. 概念层次网络理论,简称HNC(TheoryofHierarchicalNetworkofConcepts)是黄曾阳创立的以语义研究为基础的自然语言理解系统理论。

    The Theory of Hierarchical Network of Concepts , HNC for short , is a series of theories for natural language processing on the basis of semantic study .

  6. 作为一种有效表现概念层次结构和语义的模型,Ontology被广泛运用到计算机科学的众多领域。

    As a fine model for presenting hierarchy and semantic meaning of concepts , Ontology can be used to eliminate semantic conflicts through schema mappings .

  7. 《概念层次网络理论》(HNC)述评

    Comments on Hierarchical Network of Concepts Theory On HNC and TG

  8. 而本体(Ontology)具有良好的概念层次结构和对逻辑推理的支持,具有通过概念之间的关系来表达语义的能力,能较好的为语义检索和概念检索提供知识基础。

    Ontology has a good concept structure and support for logical reasoning , owns the ability of expression semantics based on the relationship of concepts , and also can provide basic knowledges for semantic search and concept search .

  9. 文章提出了生成XML键的方法,该方法由关系数据库中的键、外键约束构造规范化关系模式的约束概念层次图,并保持语义映射为有效的、完全的XML键约束。

    This paper proposes a method of deriving keys for XML . This method constructs the constraint-concept hierarchical graph of normalized relational schema from RDB keys and foreign keys , from which the valid and complete XML keys are mapped preserving the original semantics .

  10. 该模型的实现运用了概念层次的思想方法,采用了不需要产生候选集的频繁集挖掘算法FPTree挖掘关联规则。

    The implementation of model makes use of concept level thought and applies algorithm FP_Tree , which is a frequent items set mining algorithm that don 't need to generate candidate items set , to mine association rules .

  11. 基于概念层次网络(HNC)理论,对多动词出现的一种情况&动词连见,进行了分类研究,给出了相应的处理规则。

    Based on HNC theory , this paper classified the consecutive verbs , a kind of multi-verb appearance , and proposed the relevant processing rules .

  12. 本文指明影响语音识别错误产生的主要因素,制定了基于概念层次网络(简称HNC)句类分析技术的纠错处理策略。

    HNC concept primitive are elements of HNC semantic network . , and the correcting tactics based on the Hierarchical Networks of Concepts ( HNC ) Analysis of Sentence Category ( SCA ) technology are described .

  13. 对概念层次树进行简介,分析量&质转化的定性映射(QualitativeMapping,QM)数学模型,通过对定性基准[αi,βi]的调整,实现概念提升,以构建概念层次树。

    The conception hierarchy tree is briefly introduced . The mathematical model of Qualitative Mapping ( QM ) based on mutual change of quality and quantity is analyzed . The conception is exalted to construct conception hierarchy tree by adjusting the qualitative criterion [ α I , β I ] .

  14. 重点介绍了面向整个自然语言理解处理的新理论&概念层次网络(HNC)理论的主要内容及其进展,试图在理论层面上给出HNC理论的基本概貌。

    Emphases is then laid to present the novel theory of HNC which is oriented to every phase of NLU , with regard to its main contents and progresses . A notional sketch of HNC is attempted .

  15. HNC(概念层次网络)理论的句类体系建立了句子的语义表述模式,本文从七个方面讨论了运用这一体系来开展句子语义研究的基本内容。

    The sentence category system of HNC ( Hierarchical Network of Concepts ) theory is a semantic model of sentence description . The main aspects of sentence meaning research based on this system are discussed briefly in this paper .

  16. 在知识发现的过程中建造与应用概念层次结构进行知识获取具有很多的优势,而概念格的Hasse图正好体现了一种概念层次结构,反映了概念之间的泛化和例化关系。

    There are many advantages to build and apply concept hierarchy in the knowledge acquisition , meanwhile , Hasse diagram of concept lattice embodies such concept hierarchy structure and reflects the generalization and specialization between the concepts .

  17. 概念层次在数据挖掘中有着重要的作用。

    Concept hierarchy plays a fundamentally important role in data mining .

  18. 概念层次网络中对偶性设计

    HNC ( Hierachical Networks of Concepts ) Middle-level Sign Antitheses Design

  19. 基于定性映射模型的概念层次树构建方法

    Method of conception hierarchy tree construction based on qualitative mapping

  20. 最后,模糊本体生成部分从概念层次生成模糊本体。

    And the last , Fuzzy ontology is generated from concept hierarchy .

  21. 一种新的面向属性归纳中概念层次技术研究

    New concept hierarchy optimization method in attribute - oriented induction

  22. 中文领域本体概念层次获取方法对比研究

    Contrast research of Chinese domain ontology concept hierarchy induction methods

  23. 基于概念层次网络的小学应用题句类分析和知识提取

    HNC-Based Approach of Sentence Category Analysis and Knowledge Extraction for the Primary Problem

  24. 基于抽样的概念层次数据挖掘算法

    An Algorithm for Concept Hierarchy Mining Based on Sampling

  25. 文本知识分析中的概念层次网络方法

    The Hierarchical Network of Concepts in Text Knowledge Analysis

  26. 一种基于取样的概念层次数据挖掘新算法

    A New Algorithm for the Data Mining of Concept Hierarchy Based on Sampling

  27. 基于模糊统计分析模型的概念层次分类研究

    Investigation of Concept Hierarchy Classification Based on the Model of Fuzzy Statistical Analysis

  28. 一种基于概念层次数据库挖掘一般化关联规则的算法研究

    Research on the Algorithm for Mining Generalized Association Rules Based on Taxonomic Quantitative Databases

  29. 自动标引中基于概念层次树的主题词轮排选择的算法实现

    Research on Choosing Subject Words in Automatic Indexing

  30. 基于云有序概念层次树的时间序列距离计算模型

    A new distance computing model based on cloud-sorted-concept-hierarchy-tree