o(n log n) is a notation that describes the time complexity of an algorithm, indicating that the running time grows proportionally to the product of the size of the input data, n, and the logarithm of that size. This complexity typically arises in efficient sorting algorithms and some other divide-and-conquer algorithms, representing a significant improvement over quadratic complexities like o(n^2). The 'o' signifies that it describes an upper bound that is loose, meaning the actual performance might be better but will not exceed this rate for larger inputs.
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