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With the ever-increasing scale of the Web, machine learning technologies have become important tools to improve search relevance ranking. RankBoost is a promising algorithm in this area, but it is not widely used due to its long training time. To reduce the computation time for RankBoost, we designed a FPGA-based accelerator system and its upgraded version. The accelerator, plugged into a commodity PC, increased the training speed on MSN search engine data up to 1800x compared to the original software implementation on a server. The proposed accelerator has been successfully used by researchers in the search relevance ranking.<\/jats:p>","DOI":"10.1145\/1462586.1462588","type":"journal-article","created":{"date-parts":[[2009,1,29]],"date-time":"2009-01-29T13:48:36Z","timestamp":1233236916000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["FPGA Acceleration of RankBoost in Web Search Engines"],"prefix":"10.1145","volume":"1","author":[{"given":"Ning-Yi","family":"Xu","sequence":"first","affiliation":[{"name":"Microsoft Research Asia"}]},{"given":"Xiong-Fei","family":"Cai","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia"}]},{"given":"Rui","family":"Gao","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia"}]},{"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia"}]},{"given":"Feng-Hsiung","family":"Hsu","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia"}]}],"member":"320","published-online":{"date-parts":[[2009,1]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Baeza-Yates R. and Ribeiro-Neto B. 1999. 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