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Information Retrieval Based on Formal Concept Analysis

机译:基于正式概念分析的信息检索

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摘要

In information retrieval, in order to improve the recall and precision, similar concepts are often processed during the information retrieval. With this regard, the possibility of evaluating concept similarity is acquiring an increasing relevance, since it allows the identification of different concepts that are semantically close. For every concept consist of two parts which include objects and attributes, so the computing model also has two parts. First part deals with the objects similarity by using hierarchy structure of concept lattice. The second part deals with the attributes similarity by using the expert's knowledge. Beside this, the depth also has relevance with concepts similarity. So the result is altered with concepts' depth. Experiment shows using concept lattice could improve information retrieval's recall and precision.
机译:在信息检索中,为了改善召回和精度,在信息检索期间通常处理类似的概念。通过这方面,评估概念相似性的可能性是获取越来越多的相关性,因为它允许识别语义上关闭的不同概念。对于每个概念包括两个部分,包括对象和属性,因此计算模型也有两个部分。第一部分通过使用概念格的层次结构来处理物体相似度。第二部分通过使用专家的知识来处理属性相似性。除此之外,深度还具有与概念相似性的相关性。因此,结果被概念的深度改变了。使用概念格子的实验表明可以改善信息检索的召回和精确度。

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