An Intelligent Bio-medical Document Retrieval Using Concept Map Identification

V. Shunmughavel, P. Jaganathan
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Abstract

The document retrieval is one of the fast growing and complex research area in the field of information retrieval. Concept-based information retrieval is more beneficial than keyword-based access. The most important advantage is the ability to make use of semantic relationships among concepts in finding relevant documents.  Removal of irrelevant documents by identifying conceptual mismatches is another benefit. The linguistic representation of concepts is words and phrases. These concepts are mental structures. The inherent conciseness of natural language can make words represent multiple concepts. Different words can represent the same or similar concepts. We present a novel method of concept mining methodology, which provides an efficient way of document retrieval. The performance of this proposed retrieval system was analyzed by the existing methods for different medical documents. The proposed retrieval system shows that the documents are retrieved effectively based on concepts and the system performs with higher accuracy value.
基于概念图识别的智能生物医学文献检索
文献检索是信息检索领域中一个发展迅速而又复杂的研究领域。基于概念的信息检索比基于关键字的信息检索更有利。最重要的优点是能够利用概念之间的语义关系来查找相关文档。通过识别概念不匹配来删除不相关的文档是另一个好处。概念的语言表征是词和短语。这些概念是心理结构。自然语言固有的简洁性可以使单词代表多个概念。不同的词可以表示相同或相似的概念。提出了一种新的概念挖掘方法,为文档检索提供了一种有效的方法。利用现有的检索方法对不同医学文献检索系统的性能进行了分析。结果表明,基于概念的文档检索系统能够有效地检索到文档,具有较高的检索精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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