Appraisal of MLIR systems using Weight Based Precision Metrics - Sujatha, Pothula; Prasad Koti, T; Dhavachelvan, P (International Journal of Computer Sciences and Engineering, 2025)
Multilingual Information Retrieval System (MLIR) allows users to provide queries in one language and extract the relevant content in multiple languages. Appraising the quality of these systems is a promising task. A wide variety of metrics are available for estimating the performance of IR systems, Precision and Recall are considered as the basic measures among them. However, less number of metrics is available in the literature to analyze the performance of MLIR Systems. This paper demonstrates the significance of MLIR systems when the retrieved documents are in various languages and the weights assigned by the user based on his preference languages. This is achieved by comparing the performances of IR and MLIR using the proposed weight based Precision oriented metrics. In addition, four essential parameters of the retrieval systems are considered to compare the significance of the proposed metrics with traditional metrics. The analyses of these metrics demonstrate positive and promising results. Statistical Analyses are also performed to show the importance of the proposed metrics. Thus we can conclude that weight based precision oriented metrics plays a vital role in MLIR domain area.