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Intelligent Information Retrieval within Digital Library using Domain Ontology

机译:使用领域本体的数字图书馆内智能信息检索

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摘要

A digital library is a type of information retrieval system. The existing information retrieval methodologies generally have problems on keyword-search problem. We proposed a model to solve the problem by using concept-based approach (ontology) and metadata case base. This model consists of identifying domain concepts in user's query and applying expansion to them. The system aims at contributing to an improved relevance of results retrieved from digital libraries by proposing a conceptual framework for semantic retrieval. We need to import the concept of ontology, making use of its advantage of abundant semantics and standard concept. Domain specific ontology can be used to improve information retrieval from traditional level based on keyword to the lay based on knowledge (or concept) and change the process of retrieval from traditional keyword matching to semantics matching. One approach in this approach is using query expansion techniques and the other would be introducing a case based similarity measure for metadata information retrieval using CBR approach. Results show improvements over classic method, query expansion using general purpose ontology and a number of other approaches.
机译:数字图书馆是一种信息检索系统。现有的信息检索方法通常在关键词搜索问题上存在问题。我们提出了一种使用基于概念的方法(本体论)和元数据案例库来解决该问题的模型。该模型包括识别用户查询中的领域概念并将其扩展。该系统旨在通过提出语义检索的概念框架,以提高与数字图书馆检索结果的相关性。我们需要利用本体的丰富语义和标准概念的优势来导入本体的概念。领域特定的本体可以用来将信息检索从传统的基于关键字的层次改进为基于知识(或概念)的知识,并将检索过程从传统的关键词匹配变为语义匹配。该方法中的一种方法是使用查询扩展技术,另一种方法是引入基于案例的相似性度量,以使用CBR方法检索元数据信息。结果表明,与传统方法相比有了改进,使用通用本体和许多其他方法扩展了查询。

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