Discrete calculating method of brand advertisement effect optimization

Discrete calculating method of brand advertisement effect optimization

  • CN 105,590,240 A
  • Filed: 12/30/2015
  • Published: 05/18/2016
  • Est. Priority Date: 12/30/2015
  • Status: Active Application
First Claim
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1. the discrete calculation method that advertising results are optimized, comprises the steps:

  • Data source is cleaned and integration step (S110);

    obtain four kinds of data as clicking rate optimizationThe data source of model, described four kinds of data comprise;

    User profile data;

    refer to user and watch and/or click advertisement in video websiteUser'"'"'s Concerned Industry preference information that behavior obtains and video website preference information,Material information data;

    refer to the material information of brand advertising,Advertising display log information;

    the relevant information of recording while referring to advertising display,Advertisement click logs information;

    the relevant information of recording when user clicks advertisement,Above-mentioned four kinds of data are carried out to integration and the cleaning of data, obtain user the ascribed characteristics of population andPreference information;

    Feature extraction and formatting step (S120);

    the data after cleaning and integrating are carried out to spyLevy and extract and format, the data after format are distributed and obtained mould according to certain ratioType training data and modelling verification data;

    Model training and verification step (S130);

    the training data that uses a model utilizes logistic regressionModel algorithm (LogisticRegression) obtains Logic Regression Models, uses a model and testsCard data are verified in Logic Regression Models, obtain the clicking rate threshold value of prediction;

    Model measurement and throw in step (S140);

    use described four kinds of nearest advertisement puttingData, utilize the method for feature extraction and formatting step to obtain described model measurement data, willDescribed model measurement data are input to the clicking rate value obtaining in Logic Regression Models and establish in advanceFixed clicking rate threshold value comparison, is more than or equal to described clicking rate threshold value and throws in, and is less than a littleThe rate threshold value of hitting is not thrown in.

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