Abstract: A rotor of an electric rotating machine, more particularly an axial flux machine, and an electric rotating machine equipped therewith. The rotor of the electric rotating machine, more particularly an axial flux machine, includes a plurality of magnets and a magnet carrier for fixing the magnets, with which carrier the magnets are positioned on a periphery with respect to a hub of the rotor. The magnet carrier extends radially outwards further than the magnets and has a first axial width at the periphery of the positioning of the magnets and forms a widened portion radially outside the magnets which has a second axial width which is greater than the first axial width. Using the rotor proposed here and the electric rotating machine equipped therewith, devices can be provided which, in a simple and cost-effective manner, guarantee efficient and low-wear operation.

Abstract: A stator for an axial flux motor having a laminated stator core which is fastened to a flange, wherein the laminated stator core has a rear side which is interlockingly and frictionally fastened to a front side of the flange, and/or a cooling channel between the laminated stator core and the flange is formed in the region of the fastening. An axial flux motor is also provided having a rotor which is arranged between two stators, of which one or both are as described above.

Abstract: Non-linear classifiers and dimension reduction techniques may be applied to text classification. Non-linear classifiers such as random forest, Nyström/Fisher, and others, may be used to determine criteria usable to classify text into one of a plurality of categories. Dimension reduction techniques may also be used to reduce feature space size. Machine learning techniques may be used to develop criteria (e.g., trained models) that can be used to automatically classify text. Automatic classification rates may be improved and result in fewer numbers of text samples being unclassifiable or being incorrectly classified. User-generated content may be classified, in some embodiments.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a generalized edit distance for queries. In one aspect, a method includes selecting query pairs of consecutive queries, each query pair being a first query and a second query consecutively submitted as separate queries, each first and second query including at least one term. For each query pair, the method includes selecting term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each term pair. The method also includes determining transition costs based on the co-occurrence values for term pairs, each transition cost indicative of a cost of transitioning from a first term in a first query to a second term in a second query consecutive to the first query.

Abstract: Non-linear classifiers and dimension reduction techniques may be applied to text classification. Non-linear classifiers such as random forest, Nyström/Fisher, and others, may be used to determine criteria usable to classify text into one of a plurality of categories. Dimension reduction techniques may also be used to reduce feature space size. Machine learning techniques may be used to develop criteria (e.g., trained models) that can be used to automatically classify text. Automatic classification rates may be improved and result in fewer numbers of text samples being unclassifiable or being incorrectly classified. User-generated content may be classified, in some embodiments.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a generalized edit distance for queries. In one aspect, a method includes selecting query pairs of consecutive queries, each query pair being a first query and a second query consecutively submitted as separate queries, each first and second query including at least one term. For each query pair, the method includes selecting term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each term pair. The method also includes determining transition costs based on the co-occurrence values for term pairs, each transition cost indicative of a cost of transitioning from a first term in a first query to a second term in a second query consecutive to the first query.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a generalized edit distance for queries. In one aspect, a method includes selecting query pairs of consecutive queries, each query pair being a first query and a second query consecutively submitted as separate queries, each first and second query including at least one term. For each query pair, the method includes selecting term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each term pair. The method also includes determining transition costs based on the co-occurrence values for term pairs, each transition cost indicative of a cost of transitioning from a first term in a first query to a second term in a second query consecutive to the first query.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a generalized edit distance for queries. In one aspect, a method includes selecting query pairs of consecutive queries, each query pair being a first query and a second query consecutively submitted as separate queries, each first and second query including at least one term. For each query pair, the method includes selecting term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each term pair. The method also includes determining transition costs based on the co-occurrence values for term pairs, each transition cost indicative of a cost of transitioning from a first term in a first query to a second term in a second query consecutive to the first query.