Abstract
Result merging is a key component in a metasearch engine. Once the results from various search engines are collected, the metasearch system merges them into a single ranked list. The effectiveness of a metasearch engine is closely related to the result merging algorithm it employs. In this paper, we investigate a variety of resulting merging algorithms based on a wide range of available information about the retrieved results, from their local ranks, their titles and snippets, to the full documents of these results. The effectiveness of these algorithms is then compared experimentally based on 50 queries from the TREC Web track and 10 most popular general-purpose search engines. Our experiments yield two important results. First, simple result merging strategies can outperform Google. Second, merging based on the titles and snippets of retrieved results can outperform that based on the full documents.
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Lu, Y., Meng, W., Shu, L., Yu, C., Liu, KL. (2005). Evaluation of Result Merging Strategies for Metasearch Engines. In: Ngu, A.H.H., Kitsuregawa, M., Neuhold, E.J., Chung, JY., Sheng, Q.Z. (eds) Web Information Systems Engineering – WISE 2005. WISE 2005. Lecture Notes in Computer Science, vol 3806. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11581062_5
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DOI: https://doi.org/10.1007/11581062_5
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