Provided is an information processing apparatus including a sorting unit configured to sort a second data set as evaluation data with a sorter generated by learning through supervised learning that uses a first data set as teacher data, an input unit configured to receive label correction for the second data set in accordance with a sorting result from the sorting unit, and an update unit configured to update the second data set to reflect the correction received by the input unit.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An information processing apparatus comprising: a sorting unit configured to sort a second data set as evaluation data with a sorter generated by learning through supervised learning that uses a first data set as teacher data; an input unit configured to receive label correction for the second data set in accordance with a sorting result from the sorting unit; and an update unit configured to update the second data set to reflect the correction received by the input unit. 2. The information processing apparatus according to claim 1, wherein the first data set and the second data set are sets of sorting objects to which labels are set, the sorting unit sorts the sorting objects and predicts corresponding labels, and the input unit receives correction of a label set for at least one of the sorting objects when the label set for the at least one of the sorting objects is different from the label predicted by the sorting unit. 3. The information processing apparatus according to claim 2, further comprising: an output unit configured to output information indicating the sorting object whose set label is different from the label predicted by the sorting unit. 4. The information processing apparatus according to claim 2, further comprising: an evaluation unit configured to evaluate the sorting result with a confusion matrix that compares the labels set for the sorting objects and the labels predicted by the sorting unit. 5. The information processing apparatus according to claim 1, further comprising: a control unit configured to control first re-labeling processing including sorting the first data set as evaluation data with the sorter generated by learning through the supervised learning that uses, as teacher data, the second data set updated by the update unit, receiving label correction for the first data set by the input unit, and updating the first data set by the update unit. 6. The information processing apparatus according to claim 5, wherein the control unit controls second re-labeling processing including sorting the second data set as evaluation data with the sorter generated by learning through the supervised learning that uses, as teacher data, the first data set updated by the first re-labeling processing, receiving label correction for the second data set by the input unit, and updating the second data set by the update unit. 7. The information processing apparatus according to claim 6, wherein the control unit alternately repeats the first re-labeling processing and the second re-labeling processing. 8. The information processing apparatus according to claim 7, wherein the control unit alternately repeats the first re-labeling processing and the second re-labeling processing until the input unit no longer receives label correction. 9. The information processing apparatus according to claim 5, wherein the control unit adds a third data set to at least one of the first data set and the second data set. 10. The information processing apparatus according to claim 1, further comprising: a learning unit configured to perform learning of the sorter through the supervised learning that uses the first data set or the second data set as teacher data. 11. The information processing apparatus according to claim 2, wherein the sorting objects are moving images, static images, or sounds and other contents. 12. A method for information processing executed by a processor of an information processing apparatus, the method comprising: sorting a second data set as evaluation data with a sorter generated by learning through supervised learning that uses a first data set as teacher data; receiving label correction for the second data set in accordance with a sorting result; and updating the second data set to reflect the received correction.