Method and device for evaluating rationality of embedding points

Abstract

The embodiment of this specification provides a method and device for evaluating the rationality of buried points. The method includes: obtaining the index data corresponding to multiple evaluation indexes of buried points to be evaluated within the evaluation period, and obtaining each of the above evaluation indexes Then, according to the index data corresponding to each evaluation index and the weight value of each evaluation index, the rationality of the above-mentioned buried points to be evaluated is evaluated; wherein, the above-mentioned evaluation indexes are based on the same buried point The buried point data is set; the weights of the above evaluation indicators are obtained by using multiple sample buried point data to train the buried point rationality evaluation model.

Description

Technical field [0001] The present application relates to the field of data processing, and more particularly to an assessment method and apparatus for a reasonableness of buried point. Background technique [0002] With the rapid development of the computer and the Internet, various application clients have been widely used in people's lives and work. In order to provide users with better services, many clients will continue to improve, so the client often has the need to collect user action behavior, client background event needs. For example, the client background event can be a network switching event, a picture load event, and the like. [0003] In order to achieve the acquisition of client data, you can make a clutch in the client, and the collection of client data is performed by buried points. For example, a programmer developed by the page will add the embedded code to the corresponding page for data acquisition. However, there is a possibility that there may be unreason...

AI Technical Summary

Problems solved by technology

However, some buried point settings may not be reasonable, which may lead to unreasonable reported buried point data. For example, the reported buried point data has a large amount of data, etc.

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