CN107609913B - Data analysis tracking method and system - Google Patents
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Abstract
The method comprises the steps of generating an identification string of an object to be tracked in the current level by the identification string spliced by the previous level based on the object to be tracked; analyzing the identification string of the object to be tracked in the hierarchy to be queried to obtain identification string information and association information between the hierarchies; constructing a distribution tree of the object to be tracked according to the identification string information and the association information between each level, wherein each node of the distribution tree comprises all routing information of the object to be tracked from a root node to a current node; and determining data stream transfer information of the object to be tracked based on the distribution tree, and completing the tracking of the object to be tracked. The distribution condition of each device is automatically counted in real time, the economic value brought by each device is further counted, the multi-stage device tracking is realized, and the popularization and circulation of the objects to be tracked among various devices can be finally carried out.
Description
Technical Field
The present application relates to the field of computers, and in particular, to a method and system for analyzing and tracking data.
Background
With the development of information technology, big data analysis is more and more closely connected with the life of people, for example, distribution of some application software or advertisements, a developer or a publisher needs to consider benefit issues, and benefits of the application software or the advertisements can be obtained by analyzing related data, for example, in the aspect of advertisements, advertisement effect evaluation, advertisement psychological effect evaluation, advertisement economic benefit evaluation and the like can be performed. Wherein, the advertisement effect evaluation refers to the application of a scientific method to identify the benefit of the advertisement; the advertisement psychological effect evaluation is also called advertisement effect evaluation, and refers to a method for judging the advertisement effect based on factors indirectly promoting product sales such as advertisement arrival, popularity, preference, buying desire and the like, rather than directly judging the advertisement effect based on the quality of the sales condition; the advertisement economic benefit evaluation is to evaluate the change of sales and profit after a certain advertisement fee is invested and advertisement is published, and although the influence factors are many, such as advertisement promotion, sale time, region, economy, popular habits, price, quality and the like, the change of the economic benefit can be proved by data, so that objective and scientific appliance data are required to reflect the change in the evaluation.
The past advertisement economic benefit evaluation mainly comes from identification statistics of direct first-level distribution channel merchants, and the method is simple and effective. For software with a software classification function, effective economic evaluation cannot be completed, the software can be distributed in multiple stages after being distributed in one stage, and the statistics of the subsequent multiple-stage distribution is a difficult point.
Disclosure of Invention
An object of the present application is to provide a method and a system for analyzing and tracking data, which solve the problem of data tracking in the multi-level distribution process.
According to an aspect of the present application, there is provided a method of data analytics tracking, the method comprising:
generating an identification string of an object to be tracked at the current level based on the identification string of the object to be tracked spliced at the previous level;
analyzing the identification string of the object to be tracked in the hierarchy to be queried to obtain identification string information and association information between the hierarchies;
constructing a distribution tree of the object to be tracked according to the identification string information and the association information between each level, wherein each node of the distribution tree comprises all routing information of the object to be tracked from a root node to a current node;
and determining data stream transfer information of the object to be tracked based on the distribution tree, and completing the tracking of the object to be tracked.
Further, in the above method, when the object to be tracked includes an advertisement, determining data streaming information of the object to be tracked based on the distribution tree includes:
determining data flow information of the advertisement at the to-be-queried level based on the distribution tree;
and evaluating the economic benefit of the advertisement at the to-be-queried level according to the data circulation information of the advertisement and guiding market personnel to optimize the advertisement investment.
Further, the method comprises:
and determining whether the equipment of each level is a risk user according to a preset judgment strategy, wherein the preset judgment strategy is determined by any one or any combination of reported equipment information, reported times, reported intervals, reported network information and reported user information.
Further, the analyzing the identification string of the object to be tracked in the hierarchy to be queried simultaneously or before, includes:
and carrying out anomaly detection on the identification string of the object to be tracked in the hierarchy to be inquired or the analyzed data based on a preset strategy engine rule, and carrying out early warning according to the result of the anomaly detection.
Further, early warning is carried out according to the result of the abnormal detection, and the method comprises the following steps:
matching the statistical information of the hierarchy to be queried with a preset strategy engine rule, and if the matching result meets the early warning, performing early warning, wherein the statistical information comprises at least any one of the following items: the method comprises the steps of activating information, installing activation proportion, installing times within preset time limit and the like.
Further, after the distribution tree of the object to be tracked is constructed according to the identification string information and the association information between each hierarchy, the method includes:
and searching the nodes in the distribution tree based on a query request, and feeding back the relevant information of the searched nodes to a user, wherein the query request comprises a query request actively queried by a third party or a query request based on callback information reserved by the third party.
Further, generating an identification string of the object to be tracked at the current level based on the identification string of the object to be tracked spliced by the previous level, including:
acquiring an identification string of an object to be tracked spliced by the previous level or a plurality of levels;
and splicing the obtained spliced identification string with the unique identification of the equipment at the current level to generate the identification string of the object to be tracked at the current level.
According to another aspect of the present application, there is also provided a system for data analysis tracking, including: a tracking identifier management module, a device software module, a data acquisition module and a data association module, wherein,
the tracking identification management module is used for providing an original unique identification for an object to be tracked, determining data stream transfer information of the object to be tracked and finishing tracking the object to be tracked;
the device software module is used for writing in the identification string corresponding to the previous level device and completing the splicing of the identification string corresponding to the current level device;
the data acquisition module is used for acquiring the identification string of each level and the identification information of the equipment of each level;
the data association module is used for analyzing the received identification string of the hierarchy to be queried and determining identification string information and association information between the hierarchies.
Further, in the above system, the system includes:
the system comprises an anomaly analysis module, a risk analysis module and a risk analysis module, wherein the anomaly analysis module is used for determining whether equipment of each level is a risk user according to a preset judgment strategy, and the preset judgment strategy is determined by any one or any combination of reported equipment information, reported times, reported intervals, reported network information and reported user information;
and/or
And the system is used for carrying out abnormity detection on the identification string of the object to be tracked in the hierarchy to be inquired or the analyzed data based on a preset strategy engine rule, and carrying out early warning according to an abnormity detection result.
Further, in the above system, the object to be tracked includes an advertisement, and the system includes:
and the interface service module is used for searching the economic benefit and/or the advertisement production information of the advertisement at the to-be-searched level based on the query request tracked by the advertisement.
Further, in the above system, the tracking identifier management module is configured to:
and allocating unique advertisement identification for the advertisement page and the equipment based on the application request of the advertisement page and the equipment.
Further, in the above system, the device software module is configured to:
writing an identification string corresponding to the installation equipment into a designated position of target equipment when the equipment is installed;
and when the target equipment starts the software, the identification string is obtained by reading the file at the specified position.
Further, in the above system, the interface service module is configured to:
inquiring advertisement data circulation information corresponding to the unique identification through the unique identification of the object to be tracked, wherein the advertisement data circulation information comprises at least any one of the following items: distribution information, activation information, installation information, and advertisement placement benefit.
According to yet another aspect of the present application, there is also provided a computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to implement a method as described above.
According to yet another aspect of the present application, there is also provided an apparatus for data analytics tracking, wherein the apparatus comprises:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform operations of the method as previously described.
Compared with the prior art, the data tracking analysis method and the data tracking analysis system can automatically count the distribution condition of each device in real time, and further count economic values brought by each device, such as behaviors of consumption, purchase and the like; the multi-stage equipment trackable is realized, and the popularization and circulation of the object to be tracked among various kinds of equipment can be finally carried out. The method and the device have the advantages that the complete promotion track of the mark nesting record is realized through the mark strings, all nodes passing by the data stream are recorded by the mark strings, and further help is provided for promotion and optimization due to the promotion track of the completed computing software. On the other hand, the embedded device software module reduces the direct integration of additional development of a third party, and the device software can have the corresponding identification string tracking capability only by integrating the modules in the system. Meanwhile, by using the equipment, a user with a fraudulent behavior or a malicious behavior can be identified to carry out early warning in time, a rich interface is provided finally, and the user and the service system obtain the economic benefit and the like of the release of the object to be tracked of the current level through the interface.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 illustrates a flow diagram of a method of data analytics tracking provided in accordance with an aspect of the present application;
FIG. 2 is a schematic diagram illustrating identification string generation in one embodiment of the present application;
FIG. 3 illustrates a system diagram of data analytics tracking provided in accordance with another aspect of the subject application.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The present application is described in further detail below with reference to the attached figures.
In a typical configuration of the present application, the terminal, the device serving the network, and the trusted party each include one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
Fig. 1 shows a schematic flow chart of a method for data analysis tracking according to an aspect of the present application, the method comprising: step S11 to step S14,
in step S11, generating an identification string of the object to be tracked at the current level based on the identification string of the object to be tracked spliced at the previous level; here, the object to be tracked is a data stream, and may be distribution data of an advertisement, application software, and the like, in an embodiment of the present application, for example, if the advertisement m is distributed through 3 devices, the current device C is a current hierarchy, and the device a and the device B are two upper hierarchies of the current hierarchy, then an identification string of the advertisement m after being spliced by the device a is a, and when the advertisement m is distributed to the device B, the device B is spliced based on the identification string a after being spliced by the device a, and is an identification string B, and the identification string B contains the identification string a, then when the device C is at the current hierarchy, the generated identification string is an identification string after being spliced based on the identification string B, so that a relationship between arbitrary distribution hierarchies can be identified through the identification string.
In step S12, analyzing the identification string of the object to be tracked in the hierarchy to be queried to obtain identification string information and association information between the hierarchies; here, after the object to be tracked is distributed in multiple levels, information about the object to be tracked in any level may be tracked, for example, when the level to be queried is the level of the device C, the identifier string spliced by the device C may be analyzed, the identifier string may be restored, and association information between the device C and the device a and between the device C and the device B may be obtained, where the association information may describe where the object a is installed, installed device information, installed software information, and the like.
In step S13, a distribution tree of the object to be tracked is constructed according to the identification string information and the association information between the levels, where each node of the distribution tree includes all the routing information of the object to be tracked from a root node to a current node; the identification string records all the passing hierarchies of the data stream, can contain identifications of any hierarchy, and constructs a distribution tree for tracking the data stream according to the front-back relationship of the identifications, namely the association information between the hierarchies. So that in step S14, the data flow information of the object to be tracked is determined based on the distribution tree, and the tracking of the object to be tracked is completed. For example, in advertisement tracking, the source of each advertisement click or installation may be identified based on the distribution tree.
Further, in step S11, acquiring an identification string of the object to be tracked spliced by the previous level or multiple levels; and splicing the obtained spliced identification string with the unique identification of the equipment at the current level to generate the identification string of the object to be tracked at the current level. As shown in fig. 2, in an exemplary embodiment of the present application, an original identifier is a basic identifier, and is a unique identifier allocated after each channel provider applies for the channel, and uniquely represents its own channel, and data provided by the channel provider is distributed to a parent device, such as a pc device, and an identifier string is generated at the parent device and is formed by splicing the original identifier and a parent device tracking identifier, where the parent device tracking identifier is a device unique identifier of the parent device; when the data stream passes through the parent device and then reaches the child device, the child device can be a mobile device, and an identification string is generated in the child device and is spliced with the unique identification of the child device based on the original identification and the parent device tracking identification; similarly, when the data stream passes through the child device and then reaches the grandchild device, the grandchild device may be a mobile device, and an identification string is generated at the grandchild device, and the identification string is formed by splicing the original identification, the parent device tracking identification, the unique identification of the child device, and the unique identification of the grandchild device. The identification string can adopt a compression algorithm, so that the length is reduced, and meanwhile, the data transmission of a plaintext is avoided. The relation between any advertisement levels can be identified through the identification string, the situation where the user installs the advertisement is described, the activation tracking of multiple advertisement levels such as the equipment and the software installed is also described, and the advertisement settlement is accurately carried out. The identification string is used for connecting the equipment identification of each circulation and storing the equipment identification in local, and the data is compressed and encrypted to prevent information leakage. For example, after a piece of software is installed on the mobile device, the identification string of the pc device is also written into the mobile device. After the mobile device is started, the software generates a brand new identification string of the pc identification string and the channel identification string, and the generated brand new identification string is reported.
Further, when the object to be tracked includes an advertisement, in step S14, determining data flow information of the advertisement at the level to be queried based on the distribution tree; and evaluating the economic benefit and/or optimizing the advertisement investment of the advertisement at the to-be-queried level according to the data circulation information of the advertisement. In an embodiment of the present application, for example, for distribution of advertisements, multi-level tracking of data may be utilized, data may be analyzed, advertisement economic benefits may be evaluated, and the like; performing data evaluation on the popularization condition and the grading condition, and further guiding market staff to optimize the advertisement investment according to an evaluation result; the traced distribution tree can be monitored in real time, and the activation condition of the application software can be checked in real time.
Further, the method comprises: step S15, determining whether the device at each level is a risk user according to a preset determination policy, wherein the preset determination policy is determined by any one or any combination of device information, reporting times, reporting intervals, network information and user information. In an embodiment of the present application, a risk level of a user may be determined according to reported device information, reporting times, reporting intervals, reported network information, and reported user information, where the determination mode is determined by a preset policy, and may be a determination for determining whether the reporting times of the same device in a time period exceed a quantity threshold, or a determination for determining a weighted value based on the reported information, and the like, for example, if the same device reports 5 times in 1 minute, the same device is considered as a risk user, and it can be understood that specific parameters for the determination may be flexibly set.
In an embodiment of the application, the identification string of the object to be tracked in the hierarchy to be queried or the analyzed data may be subjected to anomaly detection based on a preset policy engine rule, and early warning is performed according to the anomaly detection result. The received data can be identified by abnormal data when the association analysis of the identification string is carried out, abnormal detection is carried out by a strategy engine mode, and early warning is carried out according to the detection result. Further, when early warning is performed according to the result of the abnormality detection, the method can be realized in the following manner: matching the statistical information of the hierarchy to be queried with a preset strategy engine rule, and if the matching result meets the early warning, performing early warning, wherein the statistical information comprises at least any one of the following items: the method comprises the steps of activating information, installing activation proportion and installing frequency information in a preset time limit. In an embodiment of the present application, the preset policy engine rules include, but are not limited to, the following ways: a) maximum number of installations within the last hour; b) maximum number of activations within the last hour; c) whether the installation activation ratio exceeds 50% within the last hour; d) and the same channel device installs more than 20 pieces of application software in the last hour. In an embodiment of the present application, the adopted method performs a per-minute timing check on a specific policy, and once a preset policy is triggered, performs a message notification including office network communication information, mail information, and instant messaging information, and simultaneously sends the message to a user in a designated user group. It should be understood by those skilled in the art that the above predefined policy engine rules are merely exemplary of the present application, and that other existing or future predefined policy engine rules, as applicable to the present application, are also included within the scope of the present application and are hereby incorporated by reference.
Further, after the distribution tree of the object to be tracked is constructed according to the identification string information and the association information between each hierarchy, the node may also be searched in the distribution tree based on a query request, and relevant information of the searched node is fed back to a user, where the query request includes a query request actively queried by a third party or a query request based on callback information reserved by the third party. The identification string is composed of identifiers, the identifiers are applied to the server, the server records the meaning and the corresponding content of each identifier, node information needing to be inquired is identified in the distribution tree through transmitting the identifiers, upper node information and lower node information are returned, and a user can popularize and optimize data according to the returned node information.
Fig. 3 shows a schematic diagram of a system for data analysis tracking according to another aspect of the present application, the system comprising: a tracking identity management module 11, a device software module 12, a data acquisition module 13 and a data association module 14. In the following embodiments, the following description will be made when an object to be tracked is taken as an advertisement:
the tracking identifier management module 11 is configured to provide an original unique identifier for an object to be tracked, determine data stream transfer information of the object to be tracked, and complete tracking of the object to be tracked; each channel provider (advertising distributor) has its own unique channel identifier, which is registered and unique in the management module. The method is characterized in that the father channel identification of the user does not need to be specified when the identification is applied, and the automatic identification can be carried out through the identification string when the identification is analyzed subsequently. Each channel identifier contains a core identifier and also stores related information, such as user information, channel type, distribution type, settlement mode, settlement amount and the like.
The device software module 12 is configured to write in an identification string corresponding to a previous-level device and complete concatenation of the identification strings corresponding to the current-level device; here, the device software module 12 is configured to: writing an identification string corresponding to the installation equipment into a designated position of target equipment when the equipment is installed; and when the target equipment starts the software, the identification string is obtained by reading the file at the specified position. In an embodiment of the present application, the device software module 12 may include a pc software module and a mobile software module, and the set of modules mainly completes automatic writing of the identifier and splicing of the identifier string. When the device is installed, the identification string is written into the designated position of the target device, and when the target device starts software, the identification string information is obtained by reading the file at the designated position. Meanwhile, another method for obtaining the identification string through the server is provided, for example, when the pc installs the mobile device, the device identification and the device information of the mobile device are handed to the server for storage, and when the mobile device is started, the identification string is obtained through the device information of the mobile device in the server, and the generation of the local identification string is completed so as to be used for subsequent advertisement tracking.
The data acquisition module 13 is configured to acquire an identification string of each level and identification information of a device of each level; further, the tracking identifier management module 11 is configured to: and allocating unique advertisement identification for the advertisement page and the equipment based on the application request of the advertisement page and the equipment. Here, the advertisement publisher applies for the unique identifier in the tracking identifier management module 11 to publish the advertisement on the ground page, then the associated pc software module and the associated mobile software module register and apply for the unique identifier after the first initialization, when the software distribution or activation action occurs, the advertisement identifier string and the device identifier information processed by the mobile software module are timely returned to the data acquisition module, and when the subsequent advertisement action events such as activation starting occur, the data are reported to the data acquisition module 13, so that the subsequent association analysis on the data is facilitated, and the popularization effect and the economic benefit of different advertisement publishers are identified.
The data association module 14 is configured to analyze the received identification string of the tier to be queried, and determine identification string information and association information between tiers. Here, the data association module 14 receives the identification string and the device information delivered from the client, decrypts and decompresses the identification string, and restores the identification string information. The request tracking identification management module 11 recognizes all identification information within the identification string and confirms activation sequence information of the advertisement according to the sequence of the identification string. The key is that the identification string may contain any level of identification, each identification must be recorded in the tracking identification management module 11, and otherwise will be deleted. According to the context of the identification, an identification string dependency tree tracked by the advertisement is constructed, namely a distribution tree is constructed, the source of each advertisement click or installation can be identified through the distribution tree, the calculation information is summarized to a formal channel main body, and one record of effective popularization of one advertisement is completed.
Further, in the above system, the system includes: an anomaly analysis module 15, configured to determine whether the device at each level is a risk user according to a preset determination policy, where the preset determination policy is determined by any one or a combination of any two or more of device information, reporting times, reporting intervals, network information and user information; and/or the system is used for carrying out anomaly detection on the identification string of the object to be tracked in the hierarchy to be inquired or the analyzed data based on a preset strategy engine rule, and carrying out early warning according to the result of the anomaly detection. In an embodiment of the present application, the anomaly analysis module 15 determines the risk level of the user according to the reported device information, the reporting times, the reporting interval, the reported network information, and the reported user information. The judgment mode is judged in a mode of presetting a strategy, for example, the same equipment reports 5 in 1 minute, which is considered as a risk user, and specific parameters can be flexibly set. The received data is identified when the correlation analysis of the identifier is carried out, the abnormal data is detected in a strategy engine mode (specific index items are set), the result is early warned, and meanwhile, the query can be carried out on an interface to carry out optimization in time. Wherein, carry out the early warning to data, for example set up that every equipment can only install and promote within 10 times, prevent malicious robbery and brush.
Further, in the above system, the system includes: and the interface service module 16 is used for searching the economic benefit and/or the advertisement production information of the advertisement at the to-be-searched level based on the query request of the advertisement tracking. And identifying the node information needing to be inquired in the identification tree by transmitting the identifier, and returning the upper node information and the lower node information. And the user guides a third party to carry out data popularization and optimization. The interface is divided into two modes, one mode is that a third party actively inquires, and the second mode is that callback information reserved by the third party actively carries out callback. Here, the callback information is provided with a web url address by a third party, and when a device is activated, the activated device information is called through a designated url, and the information is notified to the third party, and the third party evaluates and optimizes, for example, a user and a business system obtain a current advertisement delivery effect through an interface service module (API interface).
The interface service module 16 is configured to: inquiring advertisement data circulation information corresponding to the unique identification through the unique identification of the object to be tracked, wherein the advertisement data circulation information comprises at least any one of the following items: distribution information, activation information, installation information, and advertisement placement benefit. In the constructed distribution tree, each node stores all routing information from a root node to the current node, wherein the routing information comprises that the current identified equipment is activated by the advertisement of which equipment, and the other equipment is which mother channel or acquires the mother channel through a network; by changing the interface, the user can inquire economic data such as distribution, activation and the like of the channel corresponding to the relevant identification through the unique identification of the user, so that the channel side can conveniently master the data in real time, and the popularization mode of the user is adjusted. The method mainly adopts the mode that the identifier of the channel is uploaded through an interface, the corresponding node is found in the generated identifier number, and the related data of the node is returned. The interface service module 16 may enable users, including third parties, to obtain user information specifying the identity for use in optimizing reverse flow advertisement usage.
In summary, by the method and the system for data tracking analysis, the distribution condition of each device is automatically counted in real time, and economic values such as consumption and purchase and other behaviors brought by each device are further counted; realize that multistage equipment can be tracked, can be final treat between multiple equipment that the tracking object promotes the circulation, for example the volume of transforming of pc product, the volume of transforming of removal end to and how much the volume of the pc of transformation has changed into the installation volume of removal again. And identifying the real source of the user popularization by identifying the identification string, and further accurately counting the economic index. The method and the device realize the complete promotion track of the identification nested record through the identification string, the identification string is composed of identifiers, the identifiers are applied by the server, and the server records the meaning and the corresponding content of each identifier. And then, the identification string records all nodes passed by the data stream, so that the promotion track of the software is calculated, and further help is provided for promotion and optimization. On the other hand, the embedded pc software module and mobile software module mode reduces the direct integration of additional development of a third party, and the pc software and the mobile software can have the corresponding identification string tracking capability only by integrating the modules in the system. Meanwhile, by using the equipment, the user with fraudulent behavior or malicious behavior can be identified to carry out early warning in time, and finally a rich API interface is provided, and the user and the service system obtain the current advertisement putting effect through the API interface.
According to yet another aspect of the present application, there is also provided a computer readable medium having stored thereon computer readable instructions, which, when executed by a processor, cause the processor to implement a method of data trace analysis as described above.
According to yet another aspect of the present application, there is also provided an apparatus for data analytics tracking, wherein the apparatus comprises:
one or more processors; and
a memory having computer-readable instructions stored thereon that, when executed, cause the one or more processors to implement a method of data trace analysis as described above.
Here, the details of each embodiment of the device may specifically refer to the corresponding part of the method embodiment of the device side, and are not described herein again.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the steps or functions described above. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Additionally, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
In addition, some of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application through the operation of the computer. Program instructions which invoke the methods of the present application may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium and/or stored within a working memory of a computer device operating in accordance with the program instructions. An embodiment according to the present application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a solution according to the aforementioned embodiments of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Claims (11)
1. A method of data analytics tracking, wherein the method comprises:
when a mobile device is installed on a pc, the device identification and the device information of the mobile device are handed to a server for storage, and when the mobile device is started, an identification string is obtained in the server through the device information of the mobile device, so that the generation of a local identification string is completed;
acquiring an identification string of an object to be tracked spliced by a previous level, splicing the acquired spliced identification string with a unique identification of equipment of a current level, and generating the identification string of the object to be tracked at the current level;
analyzing the identification string of the object to be tracked in the hierarchy to be queried to obtain identification string information and associated information between the hierarchies, wherein the associated information comprises installation source information, installed equipment information and installed software information of the object to be tracked;
constructing a distribution tree of the object to be tracked according to the identification string information and the association information between each level, wherein each node of the distribution tree comprises all routing information of the object to be tracked from a root node to a current node;
determining data stream transfer information of the object to be tracked based on the distribution tree, and completing tracking of the object to be tracked;
when the object to be tracked comprises the advertisement, determining data stream transfer information of the object to be tracked based on the distribution tree, wherein the data stream transfer information comprises:
determining data flow information of the advertisement at the to-be-queried level based on the distribution tree;
evaluating the economic benefit and/or optimizing the advertisement investment of the advertisement at the to-be-queried level according to the data circulation information of the advertisement;
and determining whether the equipment of each level is a risk user according to a preset judgment strategy, wherein the preset judgment strategy is determined by any one or any combination of reported equipment information, reported times, reported intervals, reported network information and reported user information.
2. The method of claim 1, wherein parsing the identification string of the object to be tracked at the level to be queried simultaneously or before comprises:
and carrying out anomaly detection on the identification string of the object to be tracked in the hierarchy to be inquired or the analyzed data based on a preset strategy engine rule, and carrying out early warning according to the result of the anomaly detection.
3. The method of claim 2, wherein the pre-warning based on the result of the anomaly detection comprises:
matching the statistical information of the hierarchy to be queried with a preset strategy engine rule, and if the matching result meets the early warning, performing early warning, wherein the statistical information comprises at least any one of the following items: the method comprises the steps of activating information, installing activation proportion and installing frequency information in a preset time limit.
4. The method according to claim 1, wherein after constructing the distribution tree of the object to be tracked according to the identification string information and the association information between the levels, the method comprises:
and searching the nodes in the distribution tree based on a query request, and feeding back the relevant information of the searched nodes to a user, wherein the query request comprises a query request actively queried by a third party or a query request based on callback information reserved by the third party.
5. A system for data analytics tracking, comprising: the system comprises a tracking identifier management module, an equipment software module, a data acquisition module, a data association module, an interface service module and an anomaly analysis module, wherein the tracking identifier management module is used for providing an original unique identifier for an object to be tracked, determining data flow conversion information of the object to be tracked and finishing tracking the object to be tracked;
the device software module is used for writing in the identification string corresponding to the previous level device and completing the splicing of the identification string corresponding to the current level device;
the device software module comprises a pc software module and a mobile software module, the pc software module is used for handing the device identification and the device information of the mobile device to a server for storage when the mobile device is installed on the pc, and the mobile software module is used for acquiring the identification string in the server through the device information of the mobile device when the mobile device is started to complete the generation of the local identification string;
the data acquisition module is used for acquiring the identification string of each level and the identification information of the equipment of each level;
the data association module is used for analyzing the received identification string of the hierarchy to be queried and determining identification string information and association information among the hierarchies, wherein the association information comprises installation source information, installed equipment information and installed software information of the object to be tracked;
the object to be tracked comprises an advertisement, and the interface service module is used for searching the economic benefit and/or the advertisement investment information of the advertisement in a hierarchy to be searched based on the query request of advertisement tracking;
and the anomaly analysis module is used for determining whether the equipment of each level is a risk user according to a preset judgment strategy, wherein the preset judgment strategy is determined by any one or any combination of reported equipment information, reported times, reported intervals, reported network information and reported user information.
6. The system of claim 5, wherein the anomaly analysis module is to:
and the system is used for carrying out abnormity detection on the identification string of the object to be tracked in the hierarchy to be inquired or the analyzed data based on a preset strategy engine rule, and carrying out early warning according to an abnormity detection result.
7. The system of claim 5, wherein the tracking identity management module is to:
and allocating unique advertisement identification for the advertisement page and the equipment based on the application request of the advertisement page and the equipment.
8. The system of claim 5, wherein the device software module is to:
writing an identification string corresponding to the installation equipment into a designated position of target equipment when the equipment is installed;
and when the target equipment starts the software, the identification string is obtained by reading the file at the specified position.
9. The system of claim 5, wherein the interface service module is to:
inquiring advertisement data circulation information corresponding to the unique identification through the unique identification of the object to be tracked, wherein the advertisement data circulation information comprises at least any one of the following items: distribution information, activation information, installation information, and advertisement placement benefit.
10. A computer readable medium having computer readable instructions stored thereon which are executable by a processor to implement the method of any one of claims 1 to 4.
11. An apparatus for data analytics tracking, wherein the apparatus comprises:
one or more processors; and
memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method of any of claims 1 to 4.
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| CN111221659B (en) * | 2018-11-23 | 2023-10-03 | 北京图森智途科技有限公司 | Subscription performance tracking system of multi-robot operating system environment |
| CN111259275B (en) * | 2018-12-03 | 2023-12-15 | 阿里巴巴集团控股有限公司 | Data tracking method, device and storage medium |
| CN111241105B (en) * | 2020-01-15 | 2023-08-15 | 中国联合网络通信集团有限公司 | Tracking method and device, electronic equipment and storage medium |
| CN111539665B (en) * | 2020-03-26 | 2023-09-19 | 平安科技（深圳）有限公司 | Mail monitoring method, device, equipment and storage medium |
| CN111460338B (en) * | 2020-03-31 | 2023-06-23 | 北京创鑫旅程网络技术有限公司 | Information query method and device |
| CN111882275B (en) * | 2020-07-24 | 2024-02-06 | 浙江商擎达电子商务有限公司 | Trade big data management method and system based on industrial identification analysis |
| CN111861582B (en) * | 2020-07-30 | 2022-05-06 | 成都新潮传媒集团有限公司 | Method and device for generating advertisement and periodical broadcasting and photographing scheme and computer equipment |
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