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Ranking is a central task of many Information Retrieval (IR) problems, particularly challenging in the case of large-scale Web collections where it involves effectiveness requirements and efficiency constraints that are not common to other ranking-based applications. This paper describes QuickRank, a C++ suite of efficient and effective Learning to Rank… (More)
The aim of this study was to compare the effects of pirenzepine with those of atropine a non-selective antimuscarinic agent, on gastroduodenal motor patterns in duodenal ulcer patients. Twenty patients were allocated at random to 2 groups of 10 subjects each. The drugs were administered by bolus intravenous injection as equiactive antisecretory doses of 10… (More)
Learning-to-Rank models based on additive ensembles of regression trees have been proven to be very effective for scoring query results returned by large-scale Web search engines. Unfortunately, the computational cost of scoring thousands of candidate documents by traversing large ensembles of trees is high. Thus, several works have investigated solutions… (More)
Phishing is a serious threat to global security and economy. Previously we have developed a phishing filtering system based on automatic classification. We perform statistical filtering of emails, where a classifier is trained on characteristic features of existing emails and subsequently is able to identify new phishing emails with different contents. In… (More)
The Authors refer their experience using endoscopy, biopsy and 24 hours pHmetry associated in 62 patients with symptomatology of reflux. In 21 cases it was shown different grades of esophagitis, in 12 cases reflux potentially pathological. The Authors refer that this association in studying reflux is very comfortable for every Department.