WO2016110175A1

WO2016110175A1 - Method for data processing and big data platform

Info

Publication number: WO2016110175A1
Application number: PCT/CN2015/097621
Authority: WO
Inventors: 徐蓓; 胡达; 王国庆; 王金城
Original assignee: 华为技术有限公司
Priority date: 2015-01-05
Filing date: 2015-12-16
Publication date: 2016-07-14
Also published as: CN105824821A; CN105824821B

Abstract

A method for data processing and a big data platform, the method includes: the big data platform obtains user identification and user data corresponding to the user identification (101); the big data platform obtains screening conditions from user system (102); the big data platform mines out the target user matching the screening conditions and the target data of the target user from the user data (103); the big data platform changes the user identification of the target user to an anonymous identification; the big data platform sends the anonymous identification of the target user and the target data to the user system, so that the user system determines the object user and the strategy for the object user on the basis of the target data of the target user (104); the big data platform receives the anonymous identification of the object user and the strategy sent by the user system; the big data platform changes the anonymous identification of the object user to be a non anonymous identification, and executes the strategy (105). The method can be used for mining out the value of user information and ensuring the security of user information at the same time.

Description

Data processing method and big data platform

The present application claims priority to Chinese Patent Application No. 201510003947.2, filed on Jan. 5, 2015, the entire disclosure of which is hereby incorporated by reference. .

Technical field

The present invention relates to the field of communications technologies, and in particular, to a data processing method and a big data platform.

Background technique

Currently, user personal information is an important part of big data. For example, the popularity of smartphones and wearable devices has made information such as personal location, behavior, and even physiological changes a data resource that can be recorded and analyzed in real time. At the same time, social networks have emerged and users have become producers of all kinds of information on the Internet. The typical application of big data in the commercial field is reflected in the accurate analysis of user behavior, enhance user experience, enhance user stickiness, and carry out personalized marketing.

However, big data increases the risk of personal information security for users. In the Internet age, the value and security of users' personal information has become a contradiction. Internet service providers want to be able to get as much user personal information as possible, while users want to avoid public information as much as possible; business innovation requires information sharing, and users want to reduce the risk of information transfer.

In order to solve the above contradiction, an existing method is that the operator big data platform collects data from the inside, organizes the user data into an understanding according to the understanding of the network and the user, and then opens the analyzed user data to the user system, so that The user system does some value-added services. However, although the operator big data platform has user data, it is not familiar with and proficient in the industry where the user system is located. Therefore, the analyzed user data often cannot meet the requirements of the user system.

Summary of the invention

The embodiment of the invention provides a data processing method and a big data platform, which can deeply protect the value of the user's personal information while ensuring the security of the user's personal information.

A first aspect of the present invention provides a data processing method, including:

The big data platform obtains the user identifier and the user data corresponding to the user identifier;

The big data platform obtains screening conditions from a user system;

The big data platform excerpts target data of the target user and the target user that meet the screening condition from the user data;

The big data platform anonymizes the user identifier of the target user into an anonymous identifier;

The big data platform sends an anonymous identifier and target data of the target user to the user system, so that the user system determines an object user and a policy for the target user according to target data of the target user;

Receiving, by the big data platform, an anonymous identifier of the object user sent by the user system and the policy;

The big data platform de-anonymizes the anonymous identifier of the object user and executes the policy.

With reference to the first aspect, in a first implementation manner of the first aspect, the big data platform specifically obtains user identifiers and user data corresponding to the user identifiers from the PCRF and the Net probe.

With reference to the first aspect, in a second implementation manner of the first aspect, the policy specifically includes: sending a corresponding target content to a different user of the target user in a preset manner;

The execution of the policy by the big data platform specifically includes:

Transmitting, by the big data platform, the target content to a sending center corresponding to a sending manner of the target content, and instructing the sending center to send the target content to an object user corresponding to the target content .

With reference to the first aspect, in a third implementation manner of the first aspect, the policy specifically includes performing QoS guarantee on the target user when the target user performs a target operation in a preset period;

The execution of the policy by the big data platform specifically includes:

The big data platform monitors the target user during the preset period;

When the big data platform detects that the target user performs a target operation, the big data platform sends the user identifier of the target user to the PCRF, and instructs the PCRF to perform QoS guarantee on the target user.

A second aspect of the present invention provides a big data platform, including:

An obtaining module, configured to obtain a user identifier and user data corresponding to the user identifier, and is also used to The user system obtains the screening conditions;

a mining module, configured to mine, from the user data, target users that meet the screening condition and target data of the target user;

An anonymous module, configured to anonymize the user identifier of the target user into an anonymous identifier;

a sending module, configured to send an anonymous identifier and target data of the target user to the user system, so that the user system determines an object user and a policy for the target user according to target data of the target user;

a receiving module, configured to receive an anonymous identifier of the target user sent by the user system, and the policy;

An anonymous module for anonymizing the anonymous identifier of the object user;

An execution module for executing the policy.

With reference to the second aspect, in a first implementation manner of the second aspect, the acquiring module is configured to obtain user data corresponding to the user identifier and the user identifier from the PCRF and the Net probe.

With reference to the second aspect, in a second implementation manner of the second aspect, the policy specifically includes: sending, by using different preset users, the corresponding target content to different users of the target user;

The execution module is specifically configured to separately send the target content to a sending center corresponding to a sending manner of the target content, and instruct the sending center to send the target content to a content corresponding to the target content. Object user.

With reference to the second aspect, in a third implementation manner of the second aspect, the policy specifically includes performing QoS guarantee on the target user when the target user performs a target operation in a preset period;

The execution module is specifically configured to monitor the target user during the preset period, and when detecting that the target user performs a target operation, send the user identifier of the target user to the PCRF, and indicate the PCRF pair The target user performs QoS guarantee.

It can be seen from the above technical solutions that the embodiments of the present invention have the following advantages:

In this embodiment, after filtering the target data of the target user and the target user according to the screening conditions provided by the user system, the big data platform anonymizes the user identifier of the target user into an anonymous identifier, and then the anonymous identifier and target of the target user. The data is sent to the user system so that the user system can root According to their own needs, the target data is analyzed to determine the target user, and the policy for the target user is formulated. At the same time, since the user system can only receive the anonymous identifier of the target user instead of the user identifier, the user's personal information is avoided. Circulation ensures the security of the user's information; the user system then sends the anonymous identity and policy of the target user to the big data platform, so that the big data platform can use the communication network to execute the policy, so that the big data platform can hold the user data owned. Maximize value.

DRAWINGS

1 is a flow chart of an embodiment of a data processing method of the present invention;

2 is a schematic structural diagram of an embodiment of a big data platform of the present invention.

detailed description

The embodiment of the invention provides a data processing method and a big data platform, which can ensure the security of user information while mining the value of user information.

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is an embodiment of the invention, but not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of the present invention.

The terms "comprising" and "having", and any variations thereof, are intended to cover a non-exclusive inclusion, such as a process or method comprising a series of steps or units. The system, product or device is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not explicitly listed or are inherent to such processes, methods, systems, products or devices.

Referring to FIG. 1, a data processing method in an embodiment of the present invention includes:

101. The big data platform acquires a user identifier and user data corresponding to the user identifier.

In this embodiment, the big data platform may be an operator-based big data platform. Of course, the above is merely an example and is not limiting. Big data platform can be from the Policy and Charging Rules Function (English: Policy and Charging Rules Function, abbreviated: PCRF) and Internet probe (Net probe) Obtain at least part of the user identifier and user data corresponding to the user identifier.

102. The big data platform obtains a screening condition from a user system.

The big data platform receives the screening conditions sent by the user platform, such as specific content accessed by the user on the Internet, or the original document that the user accesses the Internet every month.

103. The big data platform excels target data of the target user that meets the screening condition and the target user from the user data.

After obtaining the screening condition, the big data platform mines the user data that meets the screening condition from the obtained user data, and the user identifier corresponding to the user data. For example, the user data may be the time, the number, the frequency, the location, the traffic, and the like of each target user accessing the specific content, or may also be the Internet traffic data of all users belonging to a certain place.

104. The big data platform anonymizes the user identifier of the target user into an anonymous identifier, and sends the anonymous identifier and target data of the target user to the user system, so that the user system is based on the target user. The data determines the object user and the policies for the object user.

Rules for anonymizing user IDs are pre-stored in the big data platform. After the target user is obtained, the big data platform anonymizes the user identifier of each target user into an anonymous identifier according to the rule, wherein the anonymous identifier of each user identifier and the user data corresponding to the user identifier still maintain a corresponding relationship.

The big data platform sends the anonymous identification of all target users, user data, and the correspondence between the anonymous identifier and the user data to the user system, so that the user system can analyze the user data according to their own needs and mine from the user data. The target user who meets his needs is developed a strategy for the user of the object. The policies corresponding to different target users may be the same or different.

105. The big data platform receives an anonymous identifier of the target user sent by the user system and the policy, anonymizes the anonymous identifier of the target user, and executes the policy.

After receiving the anonymous identifier of the target user, the big data platform anonymizes the anonymous identifier according to a preset rule to obtain a user identifier of the target user and a policy corresponding to the user identifier.

There are many situations in which a user system can develop a strategy. For example, the policy specifically includes using the object Different users in the user respectively send the corresponding target content in a preset manner. When the policy is executed, the big data platform separately transmits the target content to a sending center corresponding to a sending manner of the target content, and instructs the sending center to send the target content to the target The object user corresponding to the content.

Specifically, the user system is an advertisement system, and the advertisement system divides the target user into three types of potential users, general users, and important users of a certain product, and the strategy is to send the recommended content to the potential user text message to the general user. It is the recommended content of the phone push, and the important user is the corresponding marketing information when the important customer visits the website of the similar product. Then, when the big data platform executes the policy, the user identifier of the potential user and the short message recommendation content are sent to the short message center, and the short message center is instructed to send the short message recommendation content to the potential user; and the user identifier of the general user is also And the phone recommendation content is sent to the customer center, and the customer center is instructed to push the phone recommendation content to the general user; the user identification and marketing information of the key user are also sent to the Toolbar server, and the Toolbar server is instructed. The marketing information is pushed to the key user when the key user is detected to access the website of the similar product.

Alternatively, the policy specifically includes performing a Quality of Service (QoS) guarantee on the target user when the target user performs a target operation in a preset period. The big data platform monitors the object user during the preset period; when the big data platform detects that the object user performs a target operation, the big data platform sends the user identifier of the object user to PCRF, and instructing the PCRF to perform QoS guarantee for the target user.

For example, the user system is a website, and the policy formulated by the website is that the target user performs QoS guarantee on the target user when logging in to the website within a preset period. The big data platform monitors the target user during the preset period. When detecting that the object user logs in to the website, the big data platform sends the user identifier of the target user to the PCRF, and instructs the PCRF to perform QoS guarantee for the target user.

For ease of understanding, the data processing method of the embodiment of the present invention is described below in a practical application scenario.

Obtain all user IDs and each from PCRF and Net probe based on the operator's big data platform User data corresponding to the user ID. The big data platform also obtains screening conditions from a financial institution, which is specifically the user information related to the online behavior involving “financial management”.

According to the screening condition, the big data platform excavates the user identification of the "Internet management" from all the user data, and the online behavior corresponding to the user identifier relates to all user data of "financial management", and all the excavated The user ID is anonymous to an anonymous identifier.

The big data platform sends all the anonymous identifiers and all the user data corresponding to each anonymous identifier to the "finance" to the financial institution, so that the financial institution selects from all the anonymous identifiers according to the received user data. A target user who meets a financial product of the financial institution, and formulates a text message recommendation content for the target user.

The big data platform receives the anonymous identifier and the short message recommendation content of the target user sent by the financial institution, and anonymizes the anonymous identifier of the target user, and then sends the user identifier and the short message recommendation content of all the object users to the anonymized to short The message center and instruct the short message center to send the short message recommendation content to each target user.

The data processing method in the embodiment of the present invention is described above. The big data platform in the embodiment of the present invention is described below. Referring to FIG. 2, the mobile device 200 in the embodiment of the present invention includes:

The obtaining module 201 is configured to acquire user data corresponding to the user identifier and the user identifier, and is further configured to obtain a screening condition from the user system.

The mining module 202 is configured to mine, from the user data, target data that meets the screening condition and target data of the target user;

An anonymous module 203, configured to anonymize the user identifier of the target user into an anonymous identifier;

The sending module 204 is configured to send the anonymous identifier and target data of the target user to the user system, so that the user system determines an object user and a policy for the target user according to target data of the target user;

The receiving module 205 is configured to receive an anonymous identifier of the target user and the policy sent by the user system;

The anonymity module 206 is configured to anonymize the anonymous identifier of the object user;

The execution module 207 is configured to execute the policy.

In this embodiment, after filtering the target data of the target user and the target user according to the screening conditions provided by the user system, the big data platform anonymizes the user identifier of the target user into an anonymous identifier, and then the anonymous identifier and target of the target user. The data is sent to the user system, so that the user system can analyze the target data according to its own needs to determine the target user, and formulate a policy for the target user; meanwhile, since the user system can only receive the anonymous identifier of the target user. It is not a user identifier, which avoids the public circulation of the user's personal information, and protects the user's information security; the user system then sends the anonymous identifier and policy of the target user to the big data platform, so that the big data platform uses the communication network to execute the policy. Enables big data platforms to maximize the value of the user data they have.

Preferably, the obtaining module 201 is specifically configured to acquire user identifiers corresponding to the user identifiers and the user identifiers from the PCRF and the Net probe.

Preferably, the policy specifically includes sending corresponding target content in a preset manner to different users of the target users. The executing module 207 is specifically configured to separately send the target content to a sending center corresponding to a sending manner of the target content, and instruct the sending center to send the target content to correspond to the target content. Object user.

Alternatively, the policy specifically includes performing quality of service (QoS) guarantee on the target user when the target user performs a target operation within a preset period. The execution module 207 is specifically configured to monitor the target user during the preset period, and when detecting that the target user performs a target operation, send the user identifier of the target user to the PCRF, and indicate the PCRF Perform QoS guarantee on the target user.

A person skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the system, the device and the unit described above can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.

In the several embodiments provided by the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division, and the actual implementation may have another The manner of division, such as multiple units or components, may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium. A number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .

The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to be limiting; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that The technical solutions described in the embodiments are modified, or the equivalents of the technical features are replaced by the equivalents of the technical solutions of the embodiments of the present invention.

Claims

A data processing method, comprising:

The big data platform obtains the user identifier and the user data corresponding to the user identifier;

The big data platform obtains screening conditions from a user system;

The big data platform excerpts target data of the target user and the target user that meet the screening condition from the user data;

The big data platform anonymizes the user identifier of the target user into an anonymous identifier;

The big data platform sends an anonymous identifier and target data of the target user to the user system, so that the user system determines an object user and a policy for the target user according to target data of the target user;

Receiving, by the big data platform, an anonymous identifier of the object user sent by the user system and the policy;

The big data platform de-anonymizes the anonymous identifier of the object user and executes the policy.
The data processing method according to claim 1, wherein

The big data platform specifically obtains the user identifier and the user data corresponding to the user identifier from the policy and charging rule function unit PCRF and the Internet probe Net probe.
The data processing method according to claim 1, wherein the policy specifically comprises: transmitting, by a different user of the target users, corresponding target content in a preset manner;

The execution of the policy by the big data platform specifically includes:

Transmitting, by the big data platform, the target content to a sending center corresponding to a sending manner of the target content, and instructing the sending center to send the target content to an object user corresponding to the target content .
The data processing method according to claim 1, wherein the policy comprises: performing a quality of service QoS guarantee on the target user when the target user performs a target operation within a preset time period;

The execution of the policy by the big data platform specifically includes:

The big data platform monitors the target user during the preset period;

When the big data platform detects that the target user performs a target operation, the big data platform sends the user identifier of the target user to the PCRF, and instructs the PCRF to perform QoS guarantee on the target user.
A big data platform, characterized by comprising:

An obtaining module, configured to obtain user identifiers and user data corresponding to the user identifiers, and is also used to obtain a screening condition from the user system;

a mining module, configured to mine, from the user data, target users that meet the screening condition and target data of the target user;

An anonymous module, configured to anonymize the user identifier of the target user into an anonymous identifier;

a sending module, configured to send an anonymous identifier and target data of the target user to the user system, so that the user system determines an object user and a policy for the target user according to target data of the target user;

a receiving module, configured to receive an anonymous identifier of the target user sent by the user system, and the policy;

An anonymous module for anonymizing the anonymous identifier of the object user;

An execution module for executing the policy.
The big data platform according to claim 5, characterized in that

The acquiring module is specifically configured to acquire user identifiers corresponding to the user identifiers and the user identifiers from the PCRF and the Net probe.
The big data platform according to claim 5, wherein the policy specifically comprises: transmitting, by a different user of the target users, corresponding target content in a preset manner;

The execution module is specifically configured to separately send the target content to a sending center corresponding to a sending manner of the target content, and instruct the sending center to send the target content to a content corresponding to the target content. Object user.
The big data platform according to claim 5, wherein the policy specifically comprises: performing QoS guarantee on the target user when the target user performs a target operation in a preset period;

The execution module is specifically configured to monitor the target user during the preset period, and when detecting that the target user performs a target operation, send the user identifier of the target user to the PCRF, and indicate the PCRF pair The target user performs QoS guarantee.