异质工程文档语义检索的若干问题研究
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摘要
知识经济的兴起推动了制造业的信息化和知识化,知识密集型产业得到进一步发展。知识密集型的产品设计、分析、生产等过程使用并产生了大量的数据、信息、知识,例如在处理过程应用了不同的计算机系统对产品分析处理,作用于不同的工程阶段,这些数据、信息、知识存储在多源异质工程文档中,并且导致文档的数量增长迅速。此外,产品设计、分析、生产过程的工程环境本身在知识密集型产业中也更加复杂,它涉及多个并行或串线的流程阶段,需要多个学科知识的支持和不同工程人员、功能团队的参与共同完成。这对知识密集型产业中的知识管理和共享重用提出了挑战,而复杂环境下异质工程文档的内容理解与语义检索是其中的关键,这对产品创新、产品质量保证、企业的信息化发展具有非常重要的应用价值。
论文在国家863计划项目“面向块状经济区域集群式供应链的服务支持技术及其平台研发与应用”中面向集群式供应链的知识服务平台的研究,浙江省自然科学基金重点项目“多源异质工程文档的内容理解与语义检索”等相关研究课题支持下,围绕着异质工程文档语义检索中语义表达、语义推理的若干问题展开研究,主要工作包括：
1)提出一种基于多维关联的异质工程文档语义检索方法。
对于产品设计、分析、生产过程中存在的大量工程文档,已有检索方法没有考虑工程文档的多源异质的特性,缺少对文档内容的语义处理。本文提出一种基于多维关联的异质工程文档语义检索方法,包括异质工程文档内容的多策略获取、语义标注、多维关联构建和表达、查询分析和结构化、语境构建和推理、查询求精、语义检索、结果排序、反馈等。方法能够对多源异质工程文档的内容统一理解,消除文档异质性,利用多维关联机制实现工程文档多方向多层次的关联,通过基于语境模型的语义推理计算用户的查询意图,提高查询和检索的准确性,实现跨文档的智能检索。
2)提出一种基于本体和主题地图融合的多维关联表达方法。
针对工程环境下文档资源中知识关联特点的分析,提出包含基于文档内容的内在关联、基于流程、演进的外在关联的多维关联机制。在研究本体、主题地图等关联方法基础上,提出一种基于本体和主题地图融合的多维关联表达方法,以本体为基础,构建工程语义模型表达通用的工程知识,利用主题地图对工程中特殊知识进行关联,实现工程文档的多维关联。提出的多维关联表达方法,针对工程多维关联的需求弥补了现有关联表达的不足,能够同时关注通用知识和文档中的具体内容,混合关联文档的内在外在联系,在多个语义层次上对多源异质工程文档的内容进行组织和理解。方法具有良好的适应能力和扩展性,能够为知识管理、检索、语义推理和导航等操作应用提供支持。
3)提出一种基于多维关联的局部语境模型和语境操作方法。
语境模型是对语义理解和工程知识应用的相关知识支持。针对工程环境语境建模的需求,提出了一种基于多维关联的局部语境模型,对模型形式化定义并介绍相应的操作。在多维关联的基础上语境模型形式化定义为包括核心实体集合、语境关联集合、规则集合、尺寸的四元组。在此基础上,根据知识管理中语境应用的特点,将语境操作分为语境增强操作和语境迁移操,语境增强操作包括语境补充、语境扩展和语境收缩,语境迁移操作包括语境提升和下降、语境平移、语境融合。与已有研究相比,我们提出的语境模型和操作考虑语境的动态性,在语义上对抽象与具体的上下文知识进行多层次的描述,满足工程环境下知识管理和应用任务中语境内容多样性的需求,能够进行复杂的语境操作,为多种应用场景F的任务提供准确的上下文知识和语义推理支持。
4)提出一种基于语境的查询处理和检索方法。
语境模型对用户查询意图的理解和检索提供支持,但是当前基于语境的研究存在模型静态化或模糊的问题,查询处理和检索中的语义理解和推理的灵活性和明确性受到限制,不易基于语境进行扩展。针对以上问题,提出一个新的基于语境的工程文档查询处理和检索方法,使用基于多维关联的局部语境模型对查询和检索进行处理,包括查询分析、查询结构化、语境构建和推理、查询求精以及检索等阶段。提出的方法利用语义推理算法动态生成面向具体查询任务的语境模型,为查询和检索提供基于语义理解的上下文环境,满足查询处理的灵活性和明确性的需求,在查询求精和检索中,利用基于语境的推理计算明确查询的语义和检索约束条件,获取准确的查询意图,降低检索处理的复杂度并提高检索质量。
Knowledge-based economy promotes manufacturing informatization and intellectualization, and knowledge-intensive industry is further developed. Knowledge-intensive product design, analysis, and manufacturing use and generate a large amount of data, information, knowledge, for example, processes employ different computer systems for analysis and processing. As a result, the number of engineering documents is increasing rapidly. Besides, engineering environment is complicated, because manufacturing involves many parallel or serial processes, which need the support of multiple disciplines knowledge and collaboration between different engineers and teams. This is a challenge for knowledge management, sharing and reusing in knowledge-intensive industry. And the key is to understand the content of heterogeneous documents and retrieve them semantically in complicated engineering environment, which has great value for product innovation, product quality assurance, and enterprise informatization.
This work is supported in part by a grant from the National High Technology Research and Development Program of China (No.2009AA04Z151) and the Zhejiang Natural Science Foundation of China (No.Z1090461), aiming at some problems in semantic retrieval for engineering documents, such as semantic representation and semantic inference. The main works are listed as follows:
1) A heterogeneous engineering document semantic retrieval approach based on multi-dimensional association is proposed.
For the heterogeneous engineering documents in product design, analysis, and manufacturing, current retrieval methods don't consider the multiple resources and heterogeneous characteristics of engineering documents, and can't analyze context semantically. The proposed framework for heterogeneous engineering document semantic retrieval based on multi-dimensional association includes multi-strategy content capture, semantic annotation, multi-dimensional association construction and representation, query analysis and structuring, context construction and inference, query refinement, semantic retrieval, result ranking, and feedback. The proposed approach can overcome document heterogeneity to understand document content semantically, associate documents at different facets and levels, infer query intents based on context semantically, improve query processing and retrieval precision, and realize intelligent retrieval across heterogeneous engineering documents.
2) A multi-dimensional association representation method based on ontology and Topic Maps is proposed.
Considering characteristics about engineering document association, we propose multi-dimensional association method for knowledge organization, which contains content-based internal association and processing and evolution-based external association. After analyzing the characteristics of ontology and Topic Maps, a multi-dimensional association representation method based on ontology and Topic Maps is proposed, which constructs semantic model based on ontologies, and expand association scope by Topic maps, which is used to associated special knowledge. The multi-dimensional association representation considers both general and special knowledge in documents, combines internal and external associations, analyzes and organizes heterogeneous engineering documents at semantic level, which supports knowledge management, retrieval, semantic inference and navigations.
3) A local context model based on multi-dimensional association and some context operations are proposed.
Context model is a knowledge support for semantic understanding and engineering knowledge applications. Considering the requirements of engineering context modeling, we propose context model based on multi-dimensional association, which is formally defined as a quad, and further introduce corresponding operations. The context model consists of core entity set, contextual association set, rule set and size space. According to the application scenarios, we propose two types of context operations, which are context enrichment and context shifting. Context enrichment contains context supplement, expansion, and contraction. Context shifting contains context lifting and lowering, core entity based change, and context merging. Compared with current researches, our method considers the dynamics of context, describes context knowledge at sematic level, meets the requirements for content diversity, and supports for semantic inference in various application scenarios.
4) A context-based query processing and retrieval approach is proposed.
Context can be used in query intents understanding and retrieval, but context models in current researches are static or ambiguous, which limit the flexibility and explicitness in semantic understanding and inference. To solve the problems above, we propose a context-based query processing and retrieval approach, including processes of query analysis, query structuring, context construction and inference, context-based query refinement and retrieval. The proposed approach utilizes semantic inference algorithm to construct context model for specific query task. The context provides semantic understanding of background knowledge for query and retrieval, which can guarantee the flexibility and explicitness of query processing. The proposed context-based query refinement and retrieval algorithm calculates confidences of query objects and conditions to identify the semantics in query and retrieval constrains and captures query intents, which can reduce complexity of retrieval and improve retrieval precision.
论文在国家863计划项目“面向块状经济区域集群式供应链的服务支持技术及其平台研发与应用”中面向集群式供应链的知识服务平台的研究,浙江省自然科学基金重点项目“多源异质工程文档的内容理解与语义检索”等相关研究课题支持下,围绕着异质工程文档语义检索中语义表达、语义推理的若干问题展开研究,主要工作包括：
1)提出一种基于多维关联的异质工程文档语义检索方法。
对于产品设计、分析、生产过程中存在的大量工程文档,已有检索方法没有考虑工程文档的多源异质的特性,缺少对文档内容的语义处理。本文提出一种基于多维关联的异质工程文档语义检索方法,包括异质工程文档内容的多策略获取、语义标注、多维关联构建和表达、查询分析和结构化、语境构建和推理、查询求精、语义检索、结果排序、反馈等。方法能够对多源异质工程文档的内容统一理解,消除文档异质性,利用多维关联机制实现工程文档多方向多层次的关联,通过基于语境模型的语义推理计算用户的查询意图,提高查询和检索的准确性,实现跨文档的智能检索。
2)提出一种基于本体和主题地图融合的多维关联表达方法。
针对工程环境下文档资源中知识关联特点的分析,提出包含基于文档内容的内在关联、基于流程、演进的外在关联的多维关联机制。在研究本体、主题地图等关联方法基础上,提出一种基于本体和主题地图融合的多维关联表达方法,以本体为基础,构建工程语义模型表达通用的工程知识,利用主题地图对工程中特殊知识进行关联,实现工程文档的多维关联。提出的多维关联表达方法,针对工程多维关联的需求弥补了现有关联表达的不足,能够同时关注通用知识和文档中的具体内容,混合关联文档的内在外在联系,在多个语义层次上对多源异质工程文档的内容进行组织和理解。方法具有良好的适应能力和扩展性,能够为知识管理、检索、语义推理和导航等操作应用提供支持。
3)提出一种基于多维关联的局部语境模型和语境操作方法。
语境模型是对语义理解和工程知识应用的相关知识支持。针对工程环境语境建模的需求,提出了一种基于多维关联的局部语境模型,对模型形式化定义并介绍相应的操作。在多维关联的基础上语境模型形式化定义为包括核心实体集合、语境关联集合、规则集合、尺寸的四元组。在此基础上,根据知识管理中语境应用的特点,将语境操作分为语境增强操作和语境迁移操,语境增强操作包括语境补充、语境扩展和语境收缩,语境迁移操作包括语境提升和下降、语境平移、语境融合。与已有研究相比,我们提出的语境模型和操作考虑语境的动态性,在语义上对抽象与具体的上下文知识进行多层次的描述,满足工程环境下知识管理和应用任务中语境内容多样性的需求,能够进行复杂的语境操作,为多种应用场景F的任务提供准确的上下文知识和语义推理支持。
4)提出一种基于语境的查询处理和检索方法。
语境模型对用户查询意图的理解和检索提供支持,但是当前基于语境的研究存在模型静态化或模糊的问题,查询处理和检索中的语义理解和推理的灵活性和明确性受到限制,不易基于语境进行扩展。针对以上问题,提出一个新的基于语境的工程文档查询处理和检索方法,使用基于多维关联的局部语境模型对查询和检索进行处理,包括查询分析、查询结构化、语境构建和推理、查询求精以及检索等阶段。提出的方法利用语义推理算法动态生成面向具体查询任务的语境模型,为查询和检索提供基于语义理解的上下文环境,满足查询处理的灵活性和明确性的需求,在查询求精和检索中,利用基于语境的推理计算明确查询的语义和检索约束条件,获取准确的查询意图,降低检索处理的复杂度并提高检索质量。
Knowledge-based economy promotes manufacturing informatization and intellectualization, and knowledge-intensive industry is further developed. Knowledge-intensive product design, analysis, and manufacturing use and generate a large amount of data, information, knowledge, for example, processes employ different computer systems for analysis and processing. As a result, the number of engineering documents is increasing rapidly. Besides, engineering environment is complicated, because manufacturing involves many parallel or serial processes, which need the support of multiple disciplines knowledge and collaboration between different engineers and teams. This is a challenge for knowledge management, sharing and reusing in knowledge-intensive industry. And the key is to understand the content of heterogeneous documents and retrieve them semantically in complicated engineering environment, which has great value for product innovation, product quality assurance, and enterprise informatization.
This work is supported in part by a grant from the National High Technology Research and Development Program of China (No.2009AA04Z151) and the Zhejiang Natural Science Foundation of China (No.Z1090461), aiming at some problems in semantic retrieval for engineering documents, such as semantic representation and semantic inference. The main works are listed as follows:
1) A heterogeneous engineering document semantic retrieval approach based on multi-dimensional association is proposed.
For the heterogeneous engineering documents in product design, analysis, and manufacturing, current retrieval methods don't consider the multiple resources and heterogeneous characteristics of engineering documents, and can't analyze context semantically. The proposed framework for heterogeneous engineering document semantic retrieval based on multi-dimensional association includes multi-strategy content capture, semantic annotation, multi-dimensional association construction and representation, query analysis and structuring, context construction and inference, query refinement, semantic retrieval, result ranking, and feedback. The proposed approach can overcome document heterogeneity to understand document content semantically, associate documents at different facets and levels, infer query intents based on context semantically, improve query processing and retrieval precision, and realize intelligent retrieval across heterogeneous engineering documents.
2) A multi-dimensional association representation method based on ontology and Topic Maps is proposed.
Considering characteristics about engineering document association, we propose multi-dimensional association method for knowledge organization, which contains content-based internal association and processing and evolution-based external association. After analyzing the characteristics of ontology and Topic Maps, a multi-dimensional association representation method based on ontology and Topic Maps is proposed, which constructs semantic model based on ontologies, and expand association scope by Topic maps, which is used to associated special knowledge. The multi-dimensional association representation considers both general and special knowledge in documents, combines internal and external associations, analyzes and organizes heterogeneous engineering documents at semantic level, which supports knowledge management, retrieval, semantic inference and navigations.
3) A local context model based on multi-dimensional association and some context operations are proposed.
Context model is a knowledge support for semantic understanding and engineering knowledge applications. Considering the requirements of engineering context modeling, we propose context model based on multi-dimensional association, which is formally defined as a quad, and further introduce corresponding operations. The context model consists of core entity set, contextual association set, rule set and size space. According to the application scenarios, we propose two types of context operations, which are context enrichment and context shifting. Context enrichment contains context supplement, expansion, and contraction. Context shifting contains context lifting and lowering, core entity based change, and context merging. Compared with current researches, our method considers the dynamics of context, describes context knowledge at sematic level, meets the requirements for content diversity, and supports for semantic inference in various application scenarios.
4) A context-based query processing and retrieval approach is proposed.
Context can be used in query intents understanding and retrieval, but context models in current researches are static or ambiguous, which limit the flexibility and explicitness in semantic understanding and inference. To solve the problems above, we propose a context-based query processing and retrieval approach, including processes of query analysis, query structuring, context construction and inference, context-based query refinement and retrieval. The proposed approach utilizes semantic inference algorithm to construct context model for specific query task. The context provides semantic understanding of background knowledge for query and retrieval, which can guarantee the flexibility and explicitness of query processing. The proposed context-based query refinement and retrieval algorithm calculates confidences of query objects and conditions to identify the semantics in query and retrieval constrains and captures query intents, which can reduce complexity of retrieval and improve retrieval precision.
引文
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