Evaluating the effectiveness of information retrieval systems using effort-based relevance judgment. Issue 1 (11th October 2018)

• Record Type: Journal Article
• Authors: Rajagopal, Prabha; Ravana, Sri Devi; Koh, Yun Sing; Balakrishnan, Vimala
• Is Part Of: Aslib journal of information management. Volume 71:Issue 1(2019)
• Page Start: 2
• Page End: 17
• Publication Date: 2018-10-11
• Subjects: Information system -- Information retrieval -- TREC -- Large-scale experimentation -- Relevance judgments -- System-oriented evaluation; Information science -- Periodicals; Library science -- Periodicals; 020.5
• DOI: 10.1108/AJIM-04-2018-0086
• Languages: English
• ISSNs: 2050-3806

Abstract

Abstract : Purpose: The effort in addition to relevance is a major factor for satisfaction and utility of the document to the actual user. The purpose of this paper is to propose a method in generating relevance judgments that incorporate effort without human judges' involvement. Then the study determines the variation in system rankings due to low effort relevance judgment in evaluating retrieval systems at different depth of evaluation. Design/methodology/approach: Effort-based relevance judgments are generated using a proposed boxplot approach for simple document features, HTML features and readability features. The boxplot approach is a simple yet repeatable approach in classifying documents' effort while ensuring outlier scores do not skew the grading of the entire set of documents. Findings: The retrieval systems evaluation using low effort relevance judgments has a stronger influence on shallow depth of evaluation compared to deeper depth. It is proved that difference in the system rankings is due to low effort documents and not the number of relevant documents. Originality/value: Hence, it is crucial to evaluate retrieval systems at shallow depth using low effort relevance judgments.