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Pushing method of medical-field we-media platform data under big-data architecture

A data push and big data technology, applied in big data applications and the medical field, can solve problems such as content lag and ineffective use, and achieve the effect of increasing work efficiency and saving time for screening information

Active Publication Date: 2017-12-01
QINGDAO UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] At present, the recommendation model based on statistics is simple and the results are easy to control, but the content is relatively lagging, and it cannot effectively use a large amount of doctor behavior data generated by the platform to improve the performance and accuracy of the model

Method used

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  • Pushing method of medical-field we-media platform data under big-data architecture
  • Pushing method of medical-field we-media platform data under big-data architecture
  • Pushing method of medical-field we-media platform data under big-data architecture

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Experimental program
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Embodiment 1

[0059] In order to verify the effectiveness of a recommendation method based on the handheld medical information doctor reading literature data of the present invention, the time range selected in this embodiment is 2016.4-2016.7 handheld medical information.

[0060] 1. Data selection and conversion:

[0061] The raw data statistics are as follows:

[0062]

[0063]

[0064] Table 1

[0065] According to the present invention, the data set has the following form: each row represents a reading record, and each column represents the user label, time, reading article label, and number of times. The format of the data set is as Table 1.

[0066]

[0067] Table 2

[0068] From 2,442,355 pieces of SDK behavior data, through record validity verification, 91,214*4 records were obtained, and then through data selection and conversion, the final number of tags was reduced from 200 to 83, and the number of active users was 13,815, and finally 13,815*83 records were obtained. ...

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Abstract

The invention provides a pushing method of medical-field we-media platform data under a big-data architecture. The method includes the following steps: step 1, data selection and transformation, wherein valid data are extracted from user behavior log information, and transformed into modeling data matrices; step 2, evaluation data matrix construction, wherein evaluation data matrices meeting recommendation model robustness evaluation are screened out from the modeling data matrices; step 3, recommendation model construction and estimation; and step 4, recommendation result combination and formation. According to the method, systematic analysis and modeling are carried out on the medical-field we-media platform relevant-data, an estimation method of model prediction is given, valid recommendation can be carried out for doctor reading on the basis of the medical-field we-media platform data through a model, a doctor is enabled to acquire relevant literature in real time when logging in a platform, and a basis is provided for achieving the best reading selection.

Description

technical field [0001] The present invention relates to the field of big data application technology, in particular to a method for pushing data from a self-media platform in the medical field under a big data framework. Background technique [0002] The self-media platform in the medical field is a new type of self-media serving doctors. The goal is to provide registered doctor users with the latest information in the professional field, and at the same time provide a platform for doctor users to exchange and learn from each other. Therefore, not only the content is complex, but also the amount of information is large Relatively large, how to better organize content and form better stickiness to doctor users is a practical problem that needs to be solved urgently. [0003] Accurately understanding the needs of doctors and at the same time guiding doctors' behaviors to better match the goals of the media itself is the direction of the self-media platforms in the medical fiel...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/212G06F16/2458G06F16/9535Y02D10/00
Inventor 纪俊喻海清于滨
Owner QINGDAO UNIV
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