Title:
Improvised Retrieval
Using
Matching Score Technique
Abstract: Measuring effectiveness of
information
retrieval systems is essential for monitoring search quality in dynamic
environments.
In this merge, top-ranked documents in the merged result are employed
to
evaluate and rank the systems. As merging is a key component in a
meta-search
engine, the results from various search engines are collected and the
meta-search
system merges them into a single ranked list. We examine popular data
fusion
techniques designed to achieve improvements in effectiveness and
clarify
the conditions required for data fusion to show improvement. The
effectiveness
of a meta-search engine is closely related to the result merging
algorithm
it employs. In this paper, we propose merging algorithm, based on a
wide
range of available information about the retrieved results, from their
local
ranks, their titles and subtitles, to the full documents of these
results.
Our approach is effective and outperforms the retrieved results as
compared
to previously proposed ranking methods.
Authors: Mohd. Husain and Neetika Saxena