Abstract: The claimed subject matter provides a method for hierarchical classification. The method includes receiving a hierarchical structure with a first level comprising a parent node and a sibling node. The structure also includes a second level comprising two child nodes. The method further includes receiving training examples. Each training example may be associated with a class of the parent node, the sibling node, or the two child nodes. The method also includes generating a first classifier for the first level. The first classifier includes a first hyperplane distinguishing the parent and sibling nodes. A first vector is normal to the first hyperplane. Additionally, the method includes generating a second classifier for the second level. The second classifier includes a second hyperplane distinguishing the two child nodes. A second vector is normal to the second hyperplane. An orthogonality of the second vector in relation to the first vector is maximized.

Abstract: Computer-readable media, computer systems, and computing methods are provided for classifying search results as either of good quality or of poor quality. Initially, a portion of the search results, such as the highest ranked documents, are selected for evaluation. A level of quality for each of the selected search results is determined using a classification process that includes the following steps: targeting features demonstrated by the selected search results to be evaluated; evaluating the selected features to generate a level-of-quality score for each of the selected search results; comparing the score against a predefined threshold value; and, based on the comparison, assigning each of the selected search results an absolute measurement. The absolute measurement indicates poor quality when the score is less than the threshold value. Upon recognizing that the selected search results are of poor quality, a corrective action that reformulates the issued search query is automatically invoked.