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Recommendation data delivery analysis method and device
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A technology for recommending data and data, applied in the field of data analysis, can solve the problem of inability to recommend accurate and visual evaluation of information delivery effect.
Active Publication Date: 2018-08-07
BEIJING GRIDSUM TECH CO LTD
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[0004] The main purpose of the present invention is to provide a recommendation data delivery analysis method and device to solve the problem in the prior art that the delivery effect of recommendation information cannot be evaluated correctly, accurately and visually
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Embodiment 1
[0027] An embodiment of the present invention provides a method for analyzing recommendation data delivery.
[0028] figure 1 It is a flow chart of a method for analyzing recommendation data delivery according to an embodiment of the present invention. Such as figure 1 As shown, the method includes the following steps:
[0029] Step S10: Obtain delivery data of recommendation data.
[0030] Specifically, in the above step S10, the delivery data at least includes: product name, delivery time and delivery location; the product name is used to represent different types of recommended data; the delivery time is used to indicate the absolute natural time of recommendation data delivery, of course, It can be used to indicate the relative time when the recommended data is delivered relative to the delivery platform; the delivery location can be used to indicate a virtual address or an actual geographic location.
[0031] Step S20: Obtain an analysis type for analyzing the recommend...
Embodiment 2
[0070] The embodiment of the present invention also provides a recommendation data delivery analysis device, such as Figure 7 As shown, the device may include: a first acquisition unit 10 , a second acquisition unit 20 , a third acquisition unit 30 and an analysis unit 40 .
[0071]Wherein, the first acquiring unit 10 is configured to acquire delivery data of recommendation data, wherein the delivery data at least includes: product name, delivery time and delivery location.
[0072] The second acquiring unit 20 is configured to acquire an analysis type for analyzing the recommended data delivery data, wherein the analysis type at least includes: time comparative analysis and regional comparative analysis.
[0073] The third acquisition unit 30 is configured to acquire statistical data of the target website according to the product name and launch time.
[0074] The analysis unit 40 is configured to perform data analysis on the statistical data according to the delivery data ...
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Abstract
The invention discloses a recommended data issuing analysis method and a recommended data issuing analysis device. The method comprises the following steps of acquiring recommended data issuing data, wherein the issuing data at least comprise product names, issuing time and issuing sites; acquiring analysis types for analyzing the recommended data issuing data, wherein the analysis types at least comprise time comparison analysis and region comparison analysis; acquiring statistical data of a target website according to the product names and the issuing time; and performing data analysis on the statistical data according to the issuing data and the analysis types, thereby obtaining the analysis results corresponding to the analysis types. According to the recommended data issuing analysis method and the recommended data issuing analysis device, the problem that accurate, correct and visualized evaluation can not be performed on the recommended data issuing effect in the prior art is solved.
Description
technical field [0001] The present invention relates to the field of data analysis, in particular to a method and device for putting and analyzing recommended data. Background technique [0002] For the data information that people care about, such as notification messages, news data, promotion data, etc., publishers of data information often tend to understand the different effects of the data they publish through different publishing platforms, or the effectiveness before and after publishing on the same publishing platform. This effect usually includes the effect of time domain and region. This kind of feedback effectiveness information not only helps the publisher understand the impact of the published data, but also enables the publisher to achieve the expected effect as much as possible through pre-planning when publishing information in the future. Taking the most common TV advertisement as an example, the publisher chooses the TV channel and broadcasting time to put...
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