Generation of High-Quality Relevant Judgments through Document Similarity and Document Pooling for the Evaluation of Information Retrieval Systems

M. Joseph, Sri Devi Ravana
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Abstract

The Information Retrieval System Evaluation have carried out through Cranfield-paradigm in which the test collections provide the foundation of the evaluation process. The test collections consist of document corpus, topics, and a set of relevance judgements. The relevant judgements are the documents which retrieved from the test collections based on the topics. The precision of the evaluation process is based on the number of relevant documents in the relevant judgement list called qrels. This paper presents a study on how methodologies like pooling and document similarity helps to generate more relevant documents into the relevance judgments set in order to increase the accuracy of the evaluation process. The initial results have shown that combination of pooling with document similarity performs better compared to base clustering or classification.
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利用文献相似度和文献池生成高质量的相关判断,用于信息检索系统评价
信息检索系统的评价是通过克兰菲尔德范式进行的,其中测试集为评价过程提供了基础。测试集合由文档语料库、主题和一组相关判断组成。相关判断是基于主题从测试集合中检索的文档。评估过程的准确性基于相关判断表中相关文件的数量,称为qrels。本文研究了池化和文档相似度等方法如何帮助将更多相关文档生成相关判断集,以提高评估过程的准确性。初步结果表明,与基础聚类或分类相比,池化与文档相似度的组合性能更好。
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