# Optimizing search engines using clickthrough data

##### Citations

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2,515 citations

### Cites background or methods from "Optimizing search engines using cli..."

...2 Note that there are some algorithms, such as [68], which were also referred to as ordinal regression based algorithms in the literature....

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...Ranking SVM [63, 68] uses SVM for the task of pairwise classification....

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...• Ground truth mining [3, 68, 105], which targets automatically mining ground truth labels for learning to rank, mainly from click-through logs of search engines....

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...Some work has been done along this direction [3, 68, 105], however, they also have certain limitations....

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...6 This kind of judgment can also be mined from click-through logs of search engines [68, 69, 105]....

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2,511 citations

### Cites methods from "Optimizing search engines using cli..."

...MN is due to Taskar, Guestrin, and Koller [2003] and StructSVM was presented by Tsochantaridis, Joachims, Hofmann, and Altun [2005]. An alternative technique for tackling structured prediction as a regression problem was presented and analyzed by Cortes, Mohri, and Weston [2007c]....

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2,460 citations

### Cites background from "Optimizing search engines using cli..."

...1, if θ is w0 xi, if θ is wi xi ∑n j=1 vj,fxj − vi,fx2i , if θ is vi,f (4) The sum ∑n j=1 vj,fxj is independent of i and thus can be precomputed (e.g. when computing ŷ(x))....

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...Scoring functions can be learned with pairwise training data [5], where a feature tuple (x(A),x(B)) ∈ D means that x(A) should be ranked higher than x(B)....

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2,292 citations

### Cites background or methods from "Optimizing search engines using cli..."

...In contrast, we have proposed an efficient algorithm (Hofmann et al., 2002; Altun et al., 2003; Joachims, 2003) even in the case of very large output spaces, that takes advantage of the sparseness of the maximummargin solution....

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...The same is true also for other ranking algorithms (Cohen et al., 1999; Herbrich et al., 2000; Schapire and Singer, 2000; Crammer and Singer, 2002; Joachims, 2002)....

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2,173 citations

##### References

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40,147 citations

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37,861 citations

### "Optimizing search engines using cli..." refers background in this paper

...However, just like in classification SVMs [7], it is possible to approximate the solution by introducing (non-negative) slack variables ξi,j,k and minimizing the upper bound ∑ ξi,j,k. Adding SVM regularization for margin maximization to the objective leads to the following optimization problem, which is similar to the ordinal regression approach in [12]....

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...However, just like in classification SVMs [7], it is possible to approximate the solution by introducing (non-negative) slack variables ξi,j,k and minimizing the upper bound ∑ ξi,j,k....

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26,531 citations

### "Optimizing search engines using cli..." refers background or methods in this paper

...This makes it possible to use Kernels [4][25] and extend the Ranking SVM algorithm to non-linear retrieval functions....

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...Therefore, the following algorithm directly addresses (6), taking an empirical risk minimization approach [25]....

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...Note that (6) is (proportional to) a risk functional [25] with −τ as the loss function....

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11,211 citations

9,923 citations