计算机集成制造系统 ›› 2014, Vol. 20 ›› Issue (2): 250-.DOI: 10.13196/j.cims.2014.02.masonghua.0250.9.2014023

• 论文 • 上一篇    下一篇

领域本体组织的自助式零件库

马嵩华,田凌   

  1. 清华大学机械工程系
  • 出版日期:2014-03-28 发布日期:2014-03-28
  • 基金资助:
    国家自然科学基金资助项目(51175287)

Self-service parts library organized by domain ontology

  • Online:2014-03-28 Published:2014-03-28
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.51175287)

摘要: 针对目前已有基于Web的开放零件库在使用上自主性和自助性的不足,建立了一套领域本体组织的、基于HTML5技术的开放式零件库系统,该系统能够提供自助零件发布、零件语义信息检索、跨设备跨平台的零件数据浏览等功能。建立了领域本体,负责组织整个零件库资源,并使用推理机对该领域本体进行概念一致性检查;借助可扩展标记语言的转化,实现供应商的自助零件信息发布和本体属性及实例的维护;利用语义相似度算法扩展用户检索关键字,得到符合意图的零件检索结果。整个系统利用HTML5技术实现,支持在不同移动设备的不同操作系统中进行无插件的查看和操作,同时借助异步JavaScript与可扩展标记语言技术实现自助式零件上传和交互式零件选型。实现了领域本体组织下的跨平台零件库原型系统,有效提升了开放零件库使用的自助性和灵活性,对语义相似度算法的实验证明了领域本体定义的合理性,可以满足语义检索的扩展性要求。

关键词: 本体, 零件库, 语义检索, 跨平台, 大规模模定制

Abstract: Since the current web-based parts libraries lacked of autonomy and self-service,an open parts library system based on domain ontology organization and HTML5 technology implementation was built,which could provide data viewing functions such as self-service applications,semantic retrieval and parameter dynamic selection.The domain ontology was built to organize the resource data of parts library,and its completeness was checked by the inference engine.The data properties and individuals in the domain ontology were maintained based on self-service parts information published by suppliers.The semantic similarity algorithm was proposed to match the classes of domain ontology with the user's searching intent and further expand the outcomes of information retrieval.Based on the HTML5 technology,the system could be deployed on multi-operation system and mobile device without using plug-in.By using Asynchronous JavaScript and XML(AJAX)technology,the upload and interactive parts selection from a dynamic XML was realized.The prototype of the Web-based parts library was developed,and the algorithm of semantic similarity was evaluated which could satisfy the semantic retrieval demands.

Key words: ontology, parts library, semantic retrieval, multi-platform, mass customization

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