...视觉语言模型 图像语义 语义挖掘 性能优化 [gap=800]Key words】：visual language model; image semantic; semantic mining; performance optimal ...
基于18个网页-相关网页
semantic web mining 语义万维网信息挖掘 ; 语义web挖掘 ; 语义网络挖掘
semantic Web usage mining 语义网使用挖掘
Semantic Data Mining 语义数据挖掘
Semantic Content Mining 语义内容挖掘
multilayer semantic deep mining 多层语义深度挖掘
This dissertation tries to study the Semantic Gap problem in image. A framework of image semantic mining is developed, which includes the studies of image semantic hierarchy, image semantic object extraction, and semantic similarity measure.
本文针对图像的“语义鸿沟”问题,提出了图像语义挖掘框架,分别研究了图像语义层式统计模型、图像语义对象获取、图像语义相似测度等内容。
参考来源 - 基于统计学习的图像语义挖掘研究·2,447,543篇论文数据，部分数据来源于NoteExpress
For this purpose it uses text mining to analyze Web pages and identify their key semantic concepts.
从这个出发点来看，它使用的是文本挖掘，试图分析网页并鉴定他们关键的语义概念。
This architecture aligns with W3C web standards for the semantic web, and allows much more flexible searching and data mining than would be possible with a MARC record.
这个结构和W3C的语义网网络标准相吻合，而且相比MARC数据，它能够进行更加灵活的搜索和数据收割。
Linked data, semantic analysis, analytics and data mining all form a layer on top of the content-web that could serve as the foundation for the next series of applications and other added value.
关联数据、语义分析、分析数据挖掘，这些都可以作为下一代网络产品和其它附加值的基础。
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