Abstract
The rankings of an object based on different criteria pose the problem of choice to give a ranking to that object at a position nearest to all the rankings. Generating a ranking list of such objects previously ranked is called rank aggregation. The aggregated ranking is analyzed by computing Spearman Footrule distance. The ranking list chosen by minimizing Spearman Footrule distance is NP-Hard problem even if number of lists is greater than four for partial lists. In the context of web, rank aggregation has been applied in meta-searching. However, the usage of prevailing search engines and meta-search engines, even though some of them being designated as successful, reveal that none of them have been effective in production of reliable and quality results, the reason being many. In order to improve the rank aggregation, we proposed the enhancement in the existing Modified Shimura technique by the introduction of a new OWA operator. It not only achieved better performance but also outperformed other similar techniques.
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Ansari, M.Z., Sufyan Beg, M.M., Kumar, M. (2016). Enhancement of Fuzzy Rank Aggregation Technique. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 381. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2526-3_14
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DOI: https://doi.org/10.1007/978-81-322-2526-3_14
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