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Predicting a user behavior number of a word

  • US 8,849,738 B2
  • Filed: 07/29/2011
  • Issued: 09/30/2014
  • Est. Priority Date: 08/02/2010
  • Status: Active Grant
First Claim
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1. A method of predicting a user behavior number of a word, the method comprising:

  • converting a historical data sequence of user behavior numbers associated with the word from a time domain to a frequency domain;

    ascertaining one or more estimated cycles of the historical data sequence, and an effect rate value of each of the one or more estimated cycles based on the frequency domain of the historical data sequence;

    determining whether the historical data sequence is stable based on each of the one or more estimated cycles and the effect rate value of each of the one or more estimated cycles, the determining including determining whether the effect rate value of each of the one or more estimated cycles exceeds a configured effect rate threshold;

    if the historical data sequence is stable, calculating a user behavior number of a prediction point based on an average value of the user behavior numbers of the historical data sequence before the prediction point; and

    if the historical data sequence is not stable;

    selecting a main cycle and a singularity of the historical data sequence based on the one or more estimated cycles and the effect rate value of each of the one or more estimated cycles, the selecting including;

    selecting an estimated cycle of the one or more estimated cycles as the main cycle, the estimated cycle being within a configured main cycle range and having a largest effect rate value; and

    selecting another estimated cycle of the one or more estimated cycles as the singularity, an effect rate value of the another estimated cycle being larger than effect rate values of other estimated cycles of the one or more estimated cycles, the other estimated cycles excluding the estimated cycle selected as the main cycle, the one or more estimated cycles including multiple estimated cycles; and

    calculating the user behavior number of a prediction point based on the selected main cycle and the selected singularity.

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