Geodesic
Improving document ranking based on logs of search engine users
Numerical methods and programming, Tome 13 (2012) no. 4, pp. 559-571.

Voir la notice de l'article provenant de la source Math-Net.Ru

Search engine logs provide significant information about user preferences. We propose an algorithm that improves search engine ranking quality by using log mining and machine learning. The corresponding evaluation shows a significant improvement in the ranking quality on real-world large-scale datasets. The proposed algorithm allows parallel processing of large-scale data using the MapReduce framework. The developed approach is also applicable to a wide range of log mining tasks.
Keywords: search engines; machine learning; log mining. 
@article{VMP_2012_13_4_a8,
     author = {M. S. Ageev},
     title = {Improving document ranking based on logs of search engine users},
     journal = {Numerical methods and programming},
     pages = {559--571},
     publisher = {mathdoc},
     volume = {13},
     number = {4},
     year = {2012},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VMP_2012_13_4_a8/}
}
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M. S. Ageev. Improving document ranking based on logs of search engine users. Numerical methods and programming, Tome 13 (2012) no. 4, pp. 559-571. http://geodesic.mathdoc.fr/item/VMP_2012_13_4_a8/