Learning Animal Concepts with Semantic Hierarchy-Based Location-Aware Image Browsing and Ecology Task Generator

机译：使用基于语义层次的位置感知图像浏览和生态任务生成器学习动物概念

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This study firstly notices that lack of overall ecologic knowledge structure is one critical reason for learnersȁ9; failure of keyword search. Therefore in order to identify their current interesting sight, the dynamic location-aware and semantic hierarchy (DLASH) is presented for learners to browse images. This hierarchy mainly considers that plant and animal species are discontinuously distributed around the planet, hence this hierarchy combines location information for constructing the semantic hierarchy through WordNet. After learners confirmed their intent information needs, this study also provides learners three kinds of image-based learning tasks to learn: similar-images comparison, concept map fill-out and placement map fill-out. These tasks are designed based on Ausubelȁ9;s advance organizers and improved it by integrating three new properties: Displaying the nodes of the concepts by authentic images, automatically generating the knowledge structure by computer and interactively integrating new and old knowledge.

机译：本研究首先注意到，缺乏整体的生态知识结构是学习者ȁ9的关键原因之一；关键字搜索失败。因此，为了识别他们当前感兴趣的场景，提出了动态的位置感知和语义层次结构（DLASH），供学习者浏览图像。该层次结构主要考虑到动植物物种在地球上不连续分布，因此该层次结构结合了位置信息，可通过WordNet构造语义层次结构。在学习者确认其意图信息需求之后，本研究还为学习者提供了三种基于图像的学习任务：相似图像比较，概念图填充和位置图填充。这些任务是基于Ausubel 9的高级组织者设计的，并通过集成三个新属性对其进行了改进：通过真实的图像显示概念的节点，通过计算机自动生成知识结构，以及交互式地集成新旧知识。

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《The 6th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education (WMUTE 2010)》|2010年|P.42-49|共8页
会议地点 Kaohsiung(CT);Kaohsiung(CT)
作者
Liu Ming-Chi; Wen Dunwei; Kinshuk; Huang Yueh-Min;
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原文格式 PDF
正文语种 eng
中图分类教育;
关键词
Wikipedia; WordNet; ecological learning; image browsing; learning task; location-aware; semantic analysis;

机译：维基百科； WordNet；生态学习；图像浏览；学习任务；位置感知；语义分析;

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机译：深度多任务学习，用于航空图像的地理规则语义分割
2. Image and Sentence Matching via Semantic Concepts and Order Learning [J] . IEEE Transactions on Pattern Analysis and Machine Intelligence . 2020,第3期

机译：通过语义概念和顺序学习进行图像和句子匹配
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机译：从嘈杂的媒体库中学习语义概念以进行自动图像注释
4. Learning Animal Concepts with Semantic Hierarchy-Based Location-Aware Image Browsing and Ecology Task Generator [C] . Liu Ming-Chi, Wen Dunwei, Kinshuk, IEEE International Conference on Wireless, Mobile and Ubiquitous Technologies in Education . 2010

机译：使用基于语义层次的位置感知图像浏览和生态任务发生器学习动物概念
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机译：VastMM-Tag：用于电子学习的视频的语义索引和浏览。
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机译：特殊学习障碍大学生词汇语义知识的弱点：来自语义流利性任务的证据
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机译：图像浏览与语义Web注释的自然语言释义。

Learning Animal Concepts with Semantic Hierarchy-Based Location-Aware Image Browsing and Ecology Task Generator

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