MLIR systems can facilitate the researchers and the end users to discover appropriate information in the preferred language. Due to the versatile applicability of MLIR systems, these systems require careful and thorough evaluations to demonstrate their desired performance. Therefore, the work reported in this book describes the greater efforts that are taken to develop a set of Metrics under Binary Retrieval and Ranked Relevance scheme for Evaluating the Performance of MLIR Systems. An Empirical and Statistical analysis is done to validate the proposed metrics under specified scheme of IR systems.

The aim of this book is to offer a set of application-independent fine grained quantification schemes, which will act as a generic model for evaluating the performance attributes of Multilingual Information Retrieval (MLIR) systems. This book describes the greater efforts that are taken to develop a set of Metrics under four different schemes for Evaluating the Performance of MLIR Systems. These proposed measurement schemes can play the decisive roles for developing qualitative designs to maintain the optimized performance in any MLIR system. The Experimental Results in this book are chosen such that, to assess the proposed metrics both empirically and statistically in order to validate their usefulness.