Abstract
We propose to use MapReduce to quickly test new retrieval approaches on a cluster of machines by sequentially scanning all documents. We present a small case study in which we use a cluster of 15 low cost machines to search a web crawl of 0.5 billion pages showing that sequential scanning is a viable approach to running large-scale information retrieval experiments with little effort. The code is available to other researchers at: http://mirex.sourceforge.net
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Hiemstra, D., Hauff, C. (2010). MapReduce for Information Retrieval Evaluation: “Let’s Quickly Test This on 12 TB of Data”. In: Agosti, M., Ferro, N., Peters, C., de Rijke, M., Smeaton, A. (eds) Multilingual and Multimodal Information Access Evaluation. CLEF 2010. Lecture Notes in Computer Science, vol 6360. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15998-5_8
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DOI: https://doi.org/10.1007/978-3-642-15998-5_8
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