Normalized Distance Measure-A Measure for Evaluating MLIR Merging Mechanisms
The Multilingual Information Retrieval System (MLIR) retrieves relevant information from multiple languages in response to a user query in a single source language. Effectiveness of any information retrieval system and Multilingual Information Retrieval System is measured using traditional metrics like Mean Average Precision (MAP), Average Distance Measure (ADM). Distributed MLIR system requires merging mechanism to obtain result from different languages. The ADM metric cannot differentiation effectiveness of the merging mechanisms. In first phase we propose a new metric Normalized Distance Measure (NDM) for measuring the effectiveness of an MLIR system. We present the characteristic differences between NDM, ADM and NDPM metrics. In the second phase shows how effectiveness of merging techniques can be observed by using Normalized Distance Measure (NDM). In first phase of experiments we show that NDM metric gives credits to MLIR systems that retrieve highly relevant multilingual documents. In the second phase of the experiments it is proved that NDM metric can show the effectiveness of merging techniques that cannot be shown by ADM metric.
Keywords: Average Distance Measure (ADM), Normalized Distance Measure (NDPM), Merging mechanisms, Multilingual Information Retrieval (MLIR)
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