Nadia Ghamrawi

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Common approaches to multi-label classification learn independent classifiers for each category, and employ ranking or thresholding schemes for classification. Because they do not exploit dependencies between labels, such techniques are only well-suited to problems in which categories are independent. However, in many domains labels are highly(More)
Eye tracking experiments have shown that titles of Web search results play a crucial role in guiding a user's search process. We present a machine-learned algorithm that trains a boosted tree to pick the most relevant title for a Web search result. We compare two modeling approaches: i) using absolute editorial judgments and ii) using pairwise preference(More)
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