语义检索的关键技术就是语义扩展。
所以，语义检索受到越来越多的关注。
Therefore, the semantic retrieval is being more and more attention.
提出了一种简单快捷的语义检索框架。
Provided a simple yet rapid searching framework based semantic information.
检索实验结果表明，该方法具有较好的语义检索性能。
Experiment results on traffic images show good retrieval quality.
基于概念分布进行检索是实现图像语义检索的方法之一。
This paper proposes a method of image semantic annotation and retrieval based on concept distribution.
文章还介绍了成语的知识表达方法和自动的语义检索过程。
This paper also introduces the knowledge representation of Chinese idioms and the automatic process of semantic retrieval.
可视化检索技术是图形生成和语义检索相结合的一种新技术。
Visual retrieval is a new technology which integrates graphic generation with semantic retrieval.
通过对系统的检索功能进行测试，初步验证了语义检索的功能。
Through the function testing of the retrieval system, the semantic search functions are verified.
设计工作还包括整体系统框架的设计和高级语义检索模块的设计等。
Our work also includes the overall design of the system framework and the design of high-level semantic retrieval module.
本文主要探讨两种实现语义检索的索引：潜语义索引和其修正形式。
This paper discusses two semantic indexing methods:LSI and its revised format IRR.
然后通过构建的敦煌壁画领域本体实现基于本体的敦煌壁画的语义检索。
And complete the Dunhuang frescos retrieval based on the ontology that constructed before.
语义检索能克服传统的基于关键词匹配检索的缺点，是信息检索的发展趋势。
Semantic retrieval can be used to overcome the shortcomings of traditional retrieval techniques based on lexical matching, and is the trend of information retrieval.
本论文主要研究如何将本体技术应用到信息检索系统中，从而实现语义检索。
This paper mainly researches how to apply ontology to IR systems, to implement semantic retrieval.
论文结合该系统展示了语义检索的特性以及语义推理机制在语义检索中的作用。
Then the paper shows the feature of semantic information retrieval and the effect of semantic inference mechanism within semantic information retrieval.
实验结果表明：在概率潜在语义检索模型中，词的正确切分能提高检索的平均精度。
Experimental results indicate that accurate segmentation can improve the effectiveness of retrieval based on PLSA.
实验表明，本标注工具应用到图像语义检索系统中，大幅度的提高了语义检索的性能。
The experimental results show that the image annotation tool improves the performance of semantic retrieval substantially.
基于领域本体的语义检索被认为是解决目前信息检索领域中所面临的困难的途径之一。
A semantic retrieval method based on domain ontology is a useful way to resolve the problems in the information retrieval area.
利用共现分析构建概念空间，实现语义检索，是当前信息组织和检索领域研究热点之一。
Using co-word analysis to construct concept space and realize semantic retrieval is one of the research hotspots in information organization and retrieval fields at present.
如何在语义检索过程中更深层次地体现语义信息，以及完善检索算法是我们今后工作的目标。
How to more deeply achieve the semantic information in the process of semantic retrieval, and embody the retrieval algorithm more deeply, are our goals in the future.
论文首先从传统信息检索技术的现状入手，分析其主要问题，阐述语义检索如何解决这些问题。
The paper starts from the status quo of traditional IR technic, to analyse its main problems, then adequately expatiates how semantic information retrieval solves these problems.
本文在系统地研究语义检索和个性化学习的基础上，提出了一种基于本体的个性化学习资源语义检索模型。
In this paper, based on a systematic study of semantic retrieval and personalized learning, a personalized learning resource retrieval models based on semantic have been proposed.
传统CBIR技术试图通过分析图像视觉特征的相似性来检索图像，这不能满足普通人按语义检索图像的需求。
Traditional techniques of CBIR try to retrieve images through analyzing the similarity of image visual features, but CBIR cannot meet the requirements of semantic image retrieval.
如何使信息具有应用程序可以理解的语义，实现信息资源的语义检索，这些问题是信息检索领域所面临的挑战。
How to enable the information to have the application procedure understandable meaning and realize semantic retrieval, these questions are the challenges which the information retrieval domain faces.
对基于RDF的动态语义检索算法进行了探讨，在它的基础上提出了一种基于“簇”的RDF动态语义检索算法。
The RDF-based dynamic semantic search algorithm is discussed, and on the basis a cluster-based RDF dynamic semantic search algorithm is proposed.
系统在语义分析模块中利用语义推理进行检索词的规范和扩展，在语义检索模块通过语义推理挖掘关联隐含知识。
By using semantic inference this prototype system processes the specification and expansion of search keyword in the semantic analysis module and discovers the implicit knowledge.
许多面向应用的自然语言处理相关任务，如信息抽取、机器翻译和语义检索都对句法浅析浅析提出了迫切的需求。
Many applied tasks related to NLP, such as Information Extraction, Machine Translation and Information Retrieve, all have the urgent requirement of parsing.
本文从一种新的检索方式——语义检索的定义出发，讨论了对检索入口、信息组织和结果输出赋予语义的基本原理。
Proceeding from the definition of semantic search, this paper discusses the basic principles of how to endow information input, information organization and searching result with semantic meaning.
首先，它调用企业(核心)语义服务来检索企业级组织信息。
First, it invokes the enterprise (core) semantic service to retrieve the enterprise-level organization information.
前者有助于搜索、语义上下文和信息检索，而后者让用户能够在高级超文本环境中进行高效的编辑。
The former allows easy searches, semantic context and information retrieval, whereas the latter enables efficient editing in an advanced hypertext environment.
请注意，为了能够检索organization_finance实体，可以重用企业语义和数据服务，并且只需新引入财务服务。
Notice that in order to be able to retrieve an Organization_Finance entity, enterprise semantic and data services may be reused, and only finance services need to be introduced.
应用推荐