An information retrieval system (IRS) is used to retrieve documents based on an information need. The IRS makes relevance judgements by attempting to match a query to a document. As IRS capabilities are indexing design dependent, the hybrid indexing method (IRS-H) is introduced. The objectives of this article are to examine IRS-H (as an alternative indexing method that performs exact phrase matching) and IRS-I, regarding retrieval usefulness, identification of relevant documents, and the quality of rejecting irrelevant documents by conducting three experiments and by analysing the related data. Three experiments took place where a collection of 100 research documents and 75 queries were presented to: (1) five participants answering a questionnaire, (2) IRS-I to generate data and (3) IRS-H to generate data. The data generated during the experiments were statistically analysed using the performance measurements of Precision, Recall and Specificity, and one-tailed Student’s t-tests. The results reveal that IRS-H (1) increased the retrieval of relevant documents, (2) reduced incorrect identification of relevant documents and (3) increased the quality of rejecting irrelevant documents. The research found that the hybrid indexing method, using a small closed document collection of a hundred documents, produced the required outputs and that it may be used as an alternative IRS indexing method.

信息检索系统（IRS）用于根据信息需求检索文档。IRS通过尝试将查询与文档进行匹配来做出相关性判断。由于IRS功能取决于索引设计，因此引入了混合索引方法（IRS-H）。本文的目的是通过进行三个实验并通过以下三个方面来研究IRS-H（作为执行精确短语匹配的替代索引方法）和IRS-I的关系：检索的有用性，相关文档的标识以及拒绝无关文档的质量。分析相关数据。进行了三个实验，向他们提出了100份研究文档和75个查询的集合：（1）五名参与者回答了问卷，（2）IRS-I生成数据，（3）IRS-H生成数据。t检验。结果表明，IRS-H（1）增加了对相关文档的检索，（2）减少了对相关文档的不正确识别，（3）提高了拒绝无关文档的质量。研究发现，混合索引方法使用了一百个文档的小型封闭文档集合，产生了所需的输出，并且可以用作替代的IRS索引方法。