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An Information Retrieval Model Based on Latent Semantic Indexing with Intelligent Preprocessing

机译:基于潜在语义索引和智能预处理的信息检索模型

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摘要

The primary goal of an information retrieval system is to retrieve all the documents that are relevant to the user query. Disparities between the vocabulary of the system's authors and that of their users pose difficulties when information is processed without human intervention. Preprocessing the documents and user queries using intelligence techniques to remove the ambiguities in representation and indexing is the current area of research. In this paper, we present a novel intelligent method that has been appended to existing stemming and stopword removal processes. We designed an information retrieval system based on the proposed method using latent semantic indexing. The experimental results of the system using the proposed method exhibits the superiority over other systems based on traditional preprocessing methods.
机译:信息检索系统的主要目标是检索与用户查询相关的所有文档。当在没有人工干预的情况下处理信息时,系统作者及其用户的词汇之间的差异会造成困难。使用智能技术预处理文档和用户查询以消除表示和索引中的歧义是当前研究的领域。在本文中,我们提出了一种新颖的智能方法,该方法已附加到现有的词干和停用词删除过程中。我们基于潜在语义索引设计了一种基于所提出方法的信息检索系统。使用所提出的方法的系统的实验结果显示出优于基于传统预处理方法的其他系统的优越性。

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