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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.
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