CN111241105A - Tracking method and device, electronic equipment and storage medium - Google Patents

Tracking method and device, electronic equipment and storage medium Download PDF

Info

Publication number
CN111241105A
CN111241105A CN202010040007.1A CN202010040007A CN111241105A CN 111241105 A CN111241105 A CN 111241105A CN 202010040007 A CN202010040007 A CN 202010040007A CN 111241105 A CN111241105 A CN 111241105A
Authority
CN
China
Prior art keywords
data
tracked
tree structure
information
level tree
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010040007.1A
Other languages
Chinese (zh)
Other versions
CN111241105B (en
Inventor
王志军
陈海波
谢攀
王蓉
谢继刚
戴智
苏轶
李梦圆
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China United Network Communications Group Co Ltd
China Unicom System Integration Ltd Corp
Original Assignee
China United Network Communications Group Co Ltd
China Unicom System Integration Ltd Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China United Network Communications Group Co Ltd, China Unicom System Integration Ltd Corp filed Critical China United Network Communications Group Co Ltd
Priority to CN202010040007.1A priority Critical patent/CN111241105B/en
Publication of CN111241105A publication Critical patent/CN111241105A/en
Application granted granted Critical
Publication of CN111241105B publication Critical patent/CN111241105B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures
    • G06F16/2246—Trees, e.g. B+trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • G06Q50/265—Personal security, identity or safety
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The disclosure provides a tracking method and apparatus, an electronic device, and a storage medium. The method comprises the following steps: the method comprises the steps of collecting communication data of a plurality of users, constructing a multi-level tree structure model comprising mobile phone signaling data and internet detailed list data, receiving an inquiry request carrying data to be tracked sent by an object, and generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model. In the prior art, the data to be tracked and the acquired communication data are tracked in a comparison mode, in the embodiment of the disclosure, the user information to be tracked corresponding to the data to be tracked is generated according to the multi-level tree structure model through the built multi-level tree structure model, so that the problems that the time consumption is long and the like caused by the fact that the data to be tracked and call records of users are sequentially compared in the prior art are solved, the user information to be tracked is rapidly determined, and the technical effect of improving the tracking efficiency is further achieved.

Description

Tracking method and device, electronic equipment and storage medium
Technical Field
The present disclosure relates to the field of internet technologies, and in particular, to a tracking method and apparatus, an electronic device, and a storage medium.
Background
As internet technology develops, telephone fraud events occur more frequently, and thus, an agent how to locate and track telephone fraud events becomes a focus of much attention.
In the prior art, when an inquiry request of data to be tracked is received, call records of each user obtained based on monitoring are obtained, the data to be tracked and the call records of each user in the call records are sequentially compared until the call records corresponding to the data to be tracked are determined, and an agent of a fraud event is tracked based on the call records.
However, in the process of implementing the present disclosure, the inventors found that at least the following problems exist: the time consumption caused by comparing the data to be tracked with the call records of each user in the call records in sequence is long, so that the tracking efficiency is low.
Disclosure of Invention
The disclosure provides a tracking method and device, an electronic device and a storage medium, which are used for solving the problem that in the prior art, the tracking efficiency is low due to long time consumption caused by comparing data to be tracked with call records of users in the call records in sequence.
In one aspect, an embodiment of the present disclosure provides a tracking method, where the method includes:
collecting communication data of a plurality of users, wherein the communication data comprises mobile phone signaling data and Internet surfing detailed list data;
constructing a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detailed list data;
receiving an inquiry request which is sent by an object and carries data to be tracked, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed list data to be tracked;
and generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, wherein the user information to be tracked at least comprises telephone numbers and position information.
In some embodiments, the constructing a multi-level tree structure model including the cell phone signaling data and the internet surfing detailed information data includes:
constructing the multi-level tree structure model according to the region information in the communication data; alternatively, the first and second electrodes may be,
and constructing the multi-level tree structure model according to the region information and the gender information in the communication data.
In some embodiments, said building said multi-level tree structure model from region information in said communication data comprises:
extracting the region information in the communication data;
constructing branches of an initial tree structure by taking the regions in the region information as nodes to obtain a multi-level tree structure;
and generating the multistage tree structure model according to the multistage tree structure, the mobile phone signaling data and the internet surfing detailed list data.
In some embodiments, the constructing the multi-level tree structure model according to the region information and the gender information in the communication data comprises:
extracting the region information in the communication data, and respectively extracting the gender information in the communication data;
constructing a first branch of an initial tree structure by taking the region in the region information as a node to obtain a first multilevel tree structure;
constructing a sub-branch of the first multilevel tree structure by taking the gender in the gender information as a node to obtain a second multilevel tree structure;
and generating the multi-level tree structure model according to the second multi-level tree structure, the mobile phone signaling data and the internet surfing detailed list data.
In some embodiments, the generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model includes:
matching the mobile phone signaling data to be tracked and/or the detailed internet surfing data to be tracked with the communication data in the multi-level tree structure model to obtain matching data corresponding to the mobile phone signaling data to be tracked and/or the detailed internet surfing data to be tracked, wherein the matching data comprises matching mobile phone signaling data and/or matching detailed internet surfing data;
and extracting the telephone number and the position information in the matching data.
In some embodiments, after the generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, the method further includes:
writing the telephone number and the position information into a distributed database, and generating a position track of the position information within a preset duration;
and pushing the telephone number and the position track to the object.
In another aspect, an embodiment of the present disclosure further provides a tracking apparatus, where the apparatus includes:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring communication data of a plurality of users, and the communication data comprises mobile phone signaling data and Internet surfing detailed list data;
the building module is used for building a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detailed list data;
the system comprises a receiving module, a tracking module and a processing module, wherein the receiving module is used for receiving an inquiry request which is sent by an object and carries data to be tracked, and the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed list data to be tracked;
and the generating module is used for generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, wherein the user information to be tracked at least comprises a telephone number and position information.
In some embodiments, the building module is configured to build the multi-level tree structure model according to region information in the communication data; or, the multi-level tree structure model is constructed according to the region information and the gender information in the communication data.
In some embodiments, the building module is configured to extract the area information in the communication data, build a branch of an initial tree structure with a region in the area information as a node to obtain a multi-level tree structure, and generate the multi-level tree structure model according to the multi-level tree structure, the mobile phone signaling data, and the internet surfing detailed information data.
In some embodiments, the building module is configured to extract the area information in the communication data, extract the gender information in the communication data, respectively, build a first branch of an initial tree structure with a region in the area information as a node to obtain a first multi-level tree structure, build a sub-branch of the first multi-level tree structure with a gender in the gender information as a node to obtain a second multi-level tree structure, and generate the multi-level tree structure model according to the second multi-level tree structure, the mobile phone signaling data, and the internet surfing detailed information data.
In some embodiments, the building module is configured to match the to-be-tracked mobile phone signaling data and/or the to-be-tracked internet detail list data with the communication data in the multistage tree structure model to obtain matching data corresponding to the to-be-tracked mobile phone signaling data and/or the to-be-tracked internet detail list data, where the matching data includes matching mobile phone signaling data and/or matching internet detail list data, and extract the phone number and the position information in the matching data.
In some embodiments, the apparatus further comprises:
the writing module is used for writing the telephone number and the position information into a distributed database and generating a position track of the position information within a preset duration;
and the pushing module is used for pushing the telephone number and the position track to the object.
In another aspect, an embodiment of the present disclosure further provides an electronic device, including: a memory, a processor;
a memory for storing the processor-executable instructions;
wherein the processor, when executing the instructions in the memory, is configured to implement a method as in any of the embodiments above.
In another aspect, the disclosed embodiments also provide a computer-readable storage medium, in which computer-executable instructions are stored, and when executed by a processor, the computer-executable instructions are used to implement the method according to any one of the above embodiments.
The present disclosure provides a tracking method and apparatus, an electronic device, and a storage medium, including: the method comprises the steps of collecting communication data of a plurality of users, wherein the communication data comprise mobile phone signaling data and internet surfing detailed list data, constructing a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detailed list data, receiving an inquiry request which is sent by an object and carries data to be tracked, wherein the data to be tracked comprises the mobile phone signaling data to be tracked and/or the internet surfing detailed list data to be tracked, generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, and the user information to be tracked at least comprises telephone numbers and position information. In the prior art, tracking is performed by comparing data to be tracked with acquired communication data, but in the embodiment of the present disclosure, a multi-level tree structure model is constructed so as to perform tracking based on the multi-level tree structure model and the data to be tracked. In addition, in the embodiment of the present disclosure, the multi-level tree structure model is constructed, so that the user information to be tracked corresponding to the data to be tracked is generated according to the multi-level tree structure model, and the problems of long time consumption and the like caused by comparing the data to be tracked with the call records of each user in sequence in the prior art are avoided, so that the user information to be tracked is determined rapidly, and the technical effect of improving the tracking efficiency is achieved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a schematic view of an application scenario of a tracking method according to an embodiment of the disclosure;
FIG. 2 is a schematic flow chart diagram illustrating a tracking method according to an embodiment of the present disclosure;
FIG. 3 is a flowchart illustrating a method for constructing a multi-level tree structure model according to region information in communication data according to an embodiment of the disclosure;
fig. 4 is a flowchart illustrating a method for constructing a multi-level tree structure model according to region information and gender information in communication data according to an embodiment of the disclosure;
FIG. 5 is a flowchart illustrating a tracking method according to another embodiment of the disclosure;
FIG. 6 is a schematic diagram of a tracking device according to an embodiment of the disclosure;
FIG. 7 is a schematic diagram of a tracking device according to another embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
In the prior art, the call records corresponding to the data to be tracked are determined from the call records mainly by sequentially comparing the data to be tracked with the call records of each user in the call records, and the problem of long comparison time is caused when the call records of each user are compared one by one due to the extremely large quantity of the call records of each user, so that the efficiency of determining the call records of the users to be tracked is low, and the tracking efficiency is low. In order to solve the above problems caused by sequential comparison in the prior art, the inventors have obtained a technical solution implemented by the present disclosure through creative efforts. In the embodiment of the disclosure, the multi-level tree structure model is constructed, so that the user information to be tracked corresponding to the data to be tracked is generated according to the multi-level tree structure model, and the problems of long time consumption and the like caused by the fact that the data to be tracked and call records of each user are sequentially compared are avoided, so that the user information to be tracked is rapidly determined, and the technical effect of improving the tracking efficiency is further realized.
The tracking method provided by the embodiment of the disclosure can be applied to the scene shown in fig. 1.
In the application scenario shown in fig. 1, the base station 100 establishes a communication link for each mobile phone 200 (3 mobile phones are exemplarily shown in fig. 1 for illustrative purposes only and are not to be construed as a limitation of the embodiment of the present disclosure), so that a user of each mobile phone 200 can perform telephone communication, short message communication, and the like to form mobile phone signaling data. And each mobile phone 200 can also surf the internet based on the communication link to form the detailed internet surfing data.
The base station 100 sends the mobile phone signaling data and the internet surfing detailed information data to the server 300.
The user 400 sends a query request to the server 300 through the computer 500.
The server 300 executes the tracking method of the embodiment of the present disclosure to determine the information of the user to be tracked, i.e., to determine the phone number and the location information of the user to be tracked.
The server 300 transmits the phone number and the location information to the computer 500.
The computer 500 displays the phone number and the location information.
The user 400 monitors and appreciates the user to be tracked based on the phone number and the location information, and the like.
The following describes the technical solutions of the present disclosure and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present disclosure will be described below with reference to the accompanying drawings.
In one aspect, the embodiment of the present disclosure provides a tracking method suitable for the application scenario.
Referring to fig. 2, fig. 2 is a schematic flow chart illustrating a tracking method according to an embodiment of the disclosure.
As shown in fig. 2, the method includes:
s101: the method comprises the steps of collecting communication data of a plurality of users, wherein the communication data comprises mobile phone signaling data and internet surfing detailed list data.
The main body for executing the tracking method of the embodiment of the present disclosure may be a tracking device, and the tracking device may be a server (see the above examples), or may be a terminal (such as a computer).
The mobile phone signaling data may include call detail data generated when a user makes a call through a user terminal, such as a calling number, a called number, call duration, call start time, call end time, a calling number attribution and a called number attribution, and the like; the mobile phone signaling data can also comprise data generated when a user receives and sends short messages through the user terminal.
The internet surfing detailed data may include data generated when a user browses a webpage through a user terminal using traffic and a free network (such as WiFi, hotspot, and the like), such as a website address, browsing frequency, and browsing duration of the webpage.
The user terminal includes, but is not limited to, a mobile phone, a smart band, and an iPad.
S102: and constructing a multi-level tree structure model comprising mobile phone signaling data and Internet surfing detailed list data.
The multi-level tree structure model is a tree structure model comprising a plurality of branches, and one branch at least comprises one piece of mobile phone signaling data or one piece of internet detail list data.
In the prior art, data to be tracked is compared with acquired communication data, so that communication data corresponding to the tracking data is determined from the communication data, and a telephone number and position information are determined from the determined communication data.
In the embodiment of the present disclosure, after the mobile phone signaling data and the internet surfing detailed statement data are collected, the multi-level tree structure model is constructed based on the mobile phone signaling data and the internet surfing detailed statement data, so as to perform subsequent tracking operation based on the multi-level tree structure model.
In some embodiments, the cell phone signaling data and the internet surfing detailed data are aggregated into a queue test cluster (kafka cluster) so as to construct a multi-level tree structure model based on the kafka cluster.
S103: and receiving an inquiry request which is sent by an object and carries data to be tracked, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed list data to be tracked.
When the main body executing the tracking method of the embodiment of the present disclosure is a server, the object may be a computer. Specifically, a user inputs a query request to the computer through a click operation (such as clicking a keyboard or a display interface of the computer) or a voice operation, and the computer sends the query request input by the user to the server.
When the main body executing the tracking method of the embodiment of the present disclosure is a computer, the object is a user, and the user inputs a query request to the computer through a click operation (for example, clicking a keyboard or a display interface of the computer) or a voice operation.
S104: and generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, wherein the user information to be tracked at least comprises telephone numbers and position information.
It can be understood that, because the multi-level tree structure model is constructed based on the mobile phone signaling data and the internet surfing detailed list data, which are generated in real time, the multi-level tree structure model is also in a continuous updating state. In some embodiments, the multi-level tree structure model may be updated by setting a time interval based on the mobile phone signaling data and the internet surfing detailed list data acquired in the time interval.
In some embodiments, generating user information to be tracked corresponding to data to be tracked according to a multi-level tree structure model is implemented based on a derived stream (slipstream).
Compared with the prior art in which data processing is realized through discrete stream (spark stream), the slipstream has the characteristics of low time delay and high data processing efficiency. Therefore, in the embodiment of the present disclosure, the information of the user to be tracked corresponding to the data to be tracked is generated according to the multi-level tree structure model based on the slipstream, and the efficiency of determining the user to be tracked can be improved.
The disclosed embodiment provides a new tracking method, which includes: the method comprises the steps of collecting communication data of a plurality of users, wherein the communication data comprise mobile phone signaling data and internet surfing detailed list data, constructing a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detailed list data, receiving an inquiry request which is sent by an object and carries data to be tracked, wherein the data to be tracked comprises the mobile phone signaling data to be tracked and/or the internet surfing detailed list data to be tracked, generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, and the user information to be tracked at least comprises telephone numbers and position information. In the prior art, tracking is performed by comparing data to be tracked with acquired communication data, but in the embodiment of the present disclosure, a multi-level tree structure model is constructed so as to perform tracking based on the multi-level tree structure model and the data to be tracked. In addition, in the embodiment of the present disclosure, the multi-level tree structure model is constructed, so that the user information to be tracked corresponding to the data to be tracked is generated according to the multi-level tree structure model, and the problems of long time consumption and the like caused by comparing the data to be tracked with the call records of each user in sequence in the prior art are avoided, so that the user information to be tracked is determined rapidly, and the technical effect of improving the tracking efficiency is achieved.
In some embodiments, S102 comprises:
s1021: and constructing a multilevel tree structure model according to the region information in the communication data. Alternatively, the first and second electrodes may be,
s1022: and constructing a multi-level tree structure model according to the region information and the gender information in the communication data.
In the embodiment of the disclosure, two methods for constructing a multilevel tree structure model are provided, one is to construct the multilevel tree structure model according to the region information; and the other is to construct a multi-level tree structure model according to the region information and the gender information.
As shown in fig. 3 (fig. 3 is a flowchart illustrating a method for constructing a multi-level tree structure model according to area information in communication data according to an embodiment of the present disclosure), in some embodiments, S1021 includes:
s11: area information in communication data is extracted.
If a user a initiates a call request to a mobile phone B of a user B through a mobile phone a, the call request carries the regional information of the mobile phone a, such as the province, city, county, etc. to which the mobile phone a belongs.
S12: and (4) constructing branches of the initial tree structure by taking the regions in the region information as nodes to obtain a multi-level tree structure.
As can be appreciated from the above example, the multi-level tree structure can include a provincial parent branch including at least one municipality branch, a municipality branch including at least one county branch, and so on.
S13: and generating a multi-level tree structure model according to the multi-level tree structure, the mobile phone signaling data and the internet surfing detailed list data.
In this step, it may specifically include: after the multilevel tree structure is constructed, writing the mobile phone signaling data and the internet surfing detailed list data into the corresponding branches to generate a multilevel tree structure model.
For example, if the area information carried in the mobile phone signaling data of the user a calling the user B is city C, the mobile phone signaling data of the user a calling the user B is written into the branch corresponding to city C.
As can be seen from fig. 4 (fig. 4 is a flowchart illustrating a method for constructing a multi-level tree structure model according to the region information and the gender information in the communication data according to the embodiment of the disclosure), in some embodiments, S1022 includes:
s21: region information in the communication data is extracted, and gender information in the communication data is extracted respectively.
In the embodiment of the disclosure, two aspects of information in the communication data are extracted, wherein one aspect of information is area information, and the other aspect of information is gender information. A description of extracting the region information may be found in S11. The description about extracting gender information is as follows:
if the gender information is extracted from the mobile phone signaling data, based on the above example, a certain user a initiates a call request to a mobile phone B of a user B through a mobile phone a, the call request carries a mobile phone number of the mobile phone a, the identity information (such as identity card information) of the user a used when the mobile phone number is registered is acquired from the mobile phone signaling data, and the gender information is extracted from the identity information.
If the internet surfing detailed document data is generated for extracting the gender information from the internet surfing detailed document data, for example, if the user A browses a certain webpage (for example, a webpage corresponding to a mailbox), the registration information (for example, user and identity information and the like) when the user A registers the webpage is obtained from the internet surfing detailed document data, and the gender information is extracted from the registration information.
Wherein the gender information includes a male and a female.
S22: and constructing a first branch of the initial tree structure by taking the region in the region information as a node to obtain a first multilevel tree structure.
The description of S22 can be referred to S12, which is not repeated here.
S23: and constructing sub-branches of the first multilevel tree structure by taking the gender in the gender information as a node to obtain a second multilevel tree structure.
After the first multi-level tree structure is constructed, child branches having gender as nodes are added on the basis of the first multi-level tree structure. For example, based on the above example, two more sub-branches are added on the basis of the sub-branches of the county area, so as to obtain the male gender sub-branch and the female gender sub-branch corresponding to the county area.
S24: and generating a multi-level tree structure model according to the second multi-level tree structure, the mobile phone signaling data and the internet surfing detailed list data.
In this step, it may specifically include: after the multilevel tree structure is constructed, writing the mobile phone signaling data and the internet surfing detailed list data into the corresponding branches to generate a multilevel tree structure model.
Based on the above example, if the area information carried in the mobile phone signaling data of the user a calling the user B is city C, and the gender of the user a is female, the mobile phone signaling data of the user a calling the user B is written into the branch corresponding to the gender of the female city C.
In some embodiments, S104 comprises:
s41: and matching the mobile phone signaling data to be tracked and/or the detailed internet surfing data to be tracked with the communication data in the multi-level tree structure model to obtain matching data corresponding to the mobile phone signaling data to be tracked and/or the detailed internet surfing data to be tracked, wherein the matching data comprises the matching mobile phone signaling data and/or the matching detailed internet surfing data.
In some embodiments, if the data to be tracked includes the mobile phone signaling data to be tracked, the mobile phone signaling data to be tracked is matched with the mobile phone signaling data in the multi-level tree structure model, so as to obtain the mobile phone signaling data corresponding to the mobile phone signaling data to be tracked.
For example, the mobile phone signaling data to be tracked includes the number of calls, the call address, the call frequency, the call duration and the gender information, and the mobile phone signaling data matched with the number of calls, the call address, the call frequency, the call duration and the gender information are obtained from the multi-level tree structure model.
In some embodiments, the specific matching process comprises: extracting the information (namely call address) of the area to be tracked in the mobile phone signaling data to be tracked, matching the information of the area to be tracked with the area information of the branches in the multi-level tree structure model, determining the branches corresponding to the information of the area to be tracked, and matching the determined mobile phone signaling data of the branches according to other accessory information (such as call times, call frequency and call duration) to obtain the mobile phone signaling data corresponding to the mobile phone signaling data to be tracked.
In other embodiments, if the multi-level tree structure model is a sub-branch further including gender information, the specific matching process includes: extracting the information (namely call address) of the area to be tracked in the mobile phone signaling data to be tracked, matching the information of the area to be tracked with the area information of the branches in the multi-level tree structure model, determining the branches corresponding to the information of the area to be tracked, selecting the sub-branches corresponding to female gender from the determined branches, and matching the mobile phone signaling data of the determined sub-branches according to other accessory information (such as call times, call frequency and call duration) to obtain the mobile phone signaling data corresponding to the signaling data to be tracked.
In some embodiments, if the data to be tracked includes the detailed internet surfing data to be tracked, matching the detailed internet surfing data to be tracked with detailed internet surfing data in the multi-level tree structure model to obtain detailed internet surfing data corresponding to the detailed internet surfing data to be tracked.
For example, the detailed internet surfing data to be tracked comprises the access number, the access address, the access frequency, the access duration and the gender information, and the detailed internet surfing data matched with the access frequency, the access address, the access frequency, the access duration and the gender information are obtained from the multi-level tree structure model.
In some embodiments, the specific matching process comprises: extracting information (namely a call address) of an area to be tracked in the detailed online form data to be tracked, matching the information of the area to be tracked with the area information of the branches in the multi-level tree structure model, determining the branches corresponding to the information of the area to be tracked, and matching the determined detailed online form data of the branches according to other accessory information (such as access times, access frequency and access duration) to obtain the detailed online form data corresponding to the detailed online form data to be tracked.
In other embodiments, if the multi-level tree structure model is a sub-branch further including gender information, the specific matching process includes: extracting information (namely access address) of an area to be tracked in the detailed online form data to be tracked, matching the information of the area to be tracked with the area information of branches in the multi-level tree structure model, determining branches corresponding to the information of the area to be tracked, selecting sub-branches corresponding to female gender from the determined branches, and matching the detailed online form data of the determined sub-branches according to other accessory information (such as access times, access frequency and access duration) to obtain the detailed online form data corresponding to the detailed online form data to be tracked.
In some embodiments, if the data to be tracked includes the mobile phone signaling data to be tracked and the detailed internet surfing data to be tracked, the mobile phone signaling data to be tracked is matched with the mobile phone signaling data in the multi-level tree structure model to obtain matched mobile phone signaling data, and the detailed internet surfing data to be tracked is matched with the detailed internet surfing data in the multi-level tree structure model to obtain matched detailed internet surfing data.
For a specific matching method of the to-be-tracked data including the to-be-tracked mobile phone signaling data and the to-be-tracked internet surfing detailed list data, reference may be made to the above example, which is not described herein again.
S42: and extracting the telephone number and the position information in the matching data.
Referring to fig. 5, fig. 5 is a schematic flow chart of a tracking method according to another embodiment of the disclosure.
As illustrated in fig. 5, the method includes:
s201: the method comprises the steps of collecting communication data of a plurality of users, wherein the communication data comprises mobile phone signaling data and internet surfing detailed list data.
For the description of S201, reference may be made to S101, which is not described herein again.
S202: and constructing a multi-level tree structure model comprising mobile phone signaling data and Internet surfing detailed list data.
For the description of S202, reference may be made to S102, which is not described herein again.
S203: and receiving an inquiry request which is sent by an object and carries data to be tracked, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed list data to be tracked.
For the description of S203, reference may be made to S103, which is not described herein again.
S204: and generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, wherein the user information to be tracked at least comprises telephone numbers and position information.
For the description of S204, reference may be made to S104, which is not described herein again.
S205: and writing the telephone number and the position information into a distributed database, and generating a position track of the position information within a preset duration.
Based on the above example, the mobile phone signaling data, the internet surfing detailed data and the multi-level tree structure model can be continuously updated, so that the phone number and the position information are written into a distributed database (hbase) and a position track of the position information within a preset time length, that is, a movement track of the user to be tracked, is generated.
S206: and pushing the telephone number and the position track to the object.
In some embodiments, the phone number and location track may be pushed to the object by file transfer protocol (ftp) for the object to further track and monitor the user to be tracked; or for the object to make an arrest of the user to be traced, etc.
In some embodiments, after the building of the multi-level tree structure model, the method further comprises: and if a target query request which is sent by a target user and carries a target telephone number is received, extracting target position information corresponding to the target telephone number from the multilevel tree structure model, and pushing the target position information to the target user.
Of course, in other embodiments, the target location information corresponding to the target phone number may be extracted from the distributed data and pushed to the target user.
Wherein the target user can implement the query based on the api interface.
According to another aspect of the embodiments of the present disclosure, there is also provided a tracking device.
Referring to fig. 6, fig. 6 is a schematic diagram of a tracking device according to an embodiment of the disclosure.
As shown in fig. 6, the apparatus includes:
the system comprises an acquisition module 1, a storage module and a control module, wherein the acquisition module is used for acquiring communication data of a plurality of users, and the communication data comprises mobile phone signaling data and internet surfing detailed list data;
the building module 2 is used for building a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detailed list data;
the receiving module 3 is configured to receive an inquiry request carrying to-be-tracked data sent by an object, where the to-be-tracked data includes to-be-tracked mobile phone signaling data and/or to-be-tracked internet detail data;
and the generating module 4 is configured to generate user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, where the user information to be tracked at least includes a telephone number and location information.
In some embodiments, the building module 2 is configured to build the multi-level tree structure model according to the region information in the communication data; or, the multi-level tree structure model is constructed according to the region information and the gender information in the communication data.
In some embodiments, the building module 2 is configured to extract the area information in the communication data, build a branch of an initial tree structure with a region in the area information as a node to obtain a multi-level tree structure, and generate the multi-level tree structure model according to the multi-level tree structure, the mobile phone signaling data, and the internet surfing detailed statement data.
In some embodiments, the constructing module 2 is configured to extract the area information in the communication data, extract the gender information in the communication data, construct a first branch of an initial tree structure with a region in the area information as a node to obtain a first multi-level tree structure, construct a sub-branch of the first multi-level tree structure with a gender in the gender information as a node to obtain a second multi-level tree structure, and generate the multi-level tree structure model according to the second multi-level tree structure, the mobile phone signaling data, and the internet surfing detailed information data.
In some embodiments, the building module 2 is configured to match the to-be-tracked mobile phone signaling data and/or the to-be-tracked internet detail list data with the communication data in the multistage tree structure model to obtain matching data corresponding to the to-be-tracked mobile phone signaling data and/or the to-be-tracked internet detail list data, where the matching data includes matching mobile phone signaling data and/or matching internet detail list data, and extract the phone number and the position information in the matching data.
As can be seen in conjunction with fig. 7, in some embodiments, the apparatus further comprises:
the writing module 5 is used for writing the telephone number and the position information into a distributed database and generating a position track of the position information within a preset duration;
and the pushing module 6 is used for pushing the telephone number and the position track to the object.
According to another aspect of the embodiments of the present disclosure, there is also provided an electronic device, including: a memory, a processor;
a memory for storing processor-executable instructions;
wherein, when executing the instructions in the memory, the processor is configured to implement the method of any of the embodiments above.
Referring to fig. 8, fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
As shown in fig. 8, the electronic device includes a memory and a processor, and the electronic device may further include a communication interface and a bus, wherein the processor, the communication interface, and the memory are connected by the bus; the processor is used to execute executable modules, such as computer programs, stored in the memory.
The Memory may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Via at least one communication interface, which may be wired or wireless), the communication connection between the network element of the system and at least one other network element may be implemented using the internet, a wide area network, a local network, a metropolitan area network, etc.
The bus may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc.
The memory is used for storing a program, and the processor executes the program after receiving an execution instruction.
The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component. The steps of the method disclosed in connection with the embodiments of the present disclosure may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
According to another aspect of the embodiments of the present disclosure, there is also provided a computer-readable storage medium having stored therein computer-executable instructions, which when executed by a processor, are configured to implement the method according to any one of the embodiments.
The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present disclosure.
In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a 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 stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present disclosure may be substantially or partially contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present disclosure. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should also be understood that, in the embodiments of the present disclosure, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.
While the present disclosure has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.

Claims (14)

1. A method of tracking, the method comprising:
collecting communication data of a plurality of users, wherein the communication data comprises mobile phone signaling data and Internet surfing detailed list data;
constructing a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detailed list data;
receiving an inquiry request which is sent by an object and carries data to be tracked, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed list data to be tracked;
and generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, wherein the user information to be tracked at least comprises telephone numbers and position information.
2. The method of claim 1, wherein constructing the multi-level tree structure model including the cell phone signaling data and the network details data comprises:
constructing the multi-level tree structure model according to the region information in the communication data; alternatively, the first and second electrodes may be,
and constructing the multi-level tree structure model according to the region information and the gender information in the communication data.
3. The method of claim 2, wherein the constructing the multi-level tree structure model according to the region information in the communication data comprises:
extracting the region information in the communication data;
constructing branches of an initial tree structure by taking the regions in the region information as nodes to obtain a multi-level tree structure;
and generating the multistage tree structure model according to the multistage tree structure, the mobile phone signaling data and the internet surfing detailed list data.
4. The method according to claim 2, wherein the constructing the multi-level tree structure model according to the region information and the gender information in the communication data comprises:
extracting the region information in the communication data, and respectively extracting the gender information in the communication data;
constructing a first branch of an initial tree structure by taking the region in the region information as a node to obtain a first multilevel tree structure;
constructing a sub-branch of the first multilevel tree structure by taking the gender in the gender information as a node to obtain a second multilevel tree structure;
and generating the multi-level tree structure model according to the second multi-level tree structure, the mobile phone signaling data and the internet surfing detailed list data.
5. The method according to any one of claims 1 to 4, wherein the generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model comprises:
matching the mobile phone signaling data to be tracked and/or the detailed internet surfing data to be tracked with the communication data in the multi-level tree structure model to obtain matching data corresponding to the mobile phone signaling data to be tracked and/or the detailed internet surfing data to be tracked, wherein the matching data comprises matching mobile phone signaling data and/or matching detailed internet surfing data;
and extracting the telephone number and the position information in the matching data.
6. The method according to any one of claims 1 to 4, wherein after said generating user information to be tracked corresponding to said data to be tracked from said multi-level tree structure model, said method further comprises:
writing the telephone number and the position information into a distributed database, and generating a position track of the position information within a preset duration;
and pushing the telephone number and the position track to the object.
7. A tracking device, the device comprising:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring communication data of a plurality of users, and the communication data comprises mobile phone signaling data and Internet surfing detailed list data;
the building module is used for building a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detailed list data;
the system comprises a receiving module, a tracking module and a processing module, wherein the receiving module is used for receiving an inquiry request which is sent by an object and carries data to be tracked, and the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed list data to be tracked;
and the generating module is used for generating user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, wherein the user information to be tracked at least comprises a telephone number and position information.
8. The apparatus according to claim 7, wherein the constructing module is configured to construct the multi-level tree structure model according to region information in the communication data; or, the multi-level tree structure model is constructed according to the region information and the gender information in the communication data.
9. The apparatus according to claim 8, wherein the building module is configured to extract the area information in the communication data, build a branch of an initial tree structure with a region in the area information as a node to obtain a multi-level tree structure, and generate the multi-level tree structure model according to the multi-level tree structure, the mobile phone signaling data, and the internet surfing detailed information data.
10. The apparatus according to claim 8, wherein the constructing module is configured to extract the area information in the communication data, extract the gender information in the communication data, respectively, construct a first branch of an initial tree structure with a region in the area information as a node to obtain a first multi-level tree structure, construct a sub-branch of the first multi-level tree structure with a gender in the gender information as a node to obtain a second multi-level tree structure, and generate the multi-level tree structure model according to the second multi-level tree structure, the mobile phone signaling data, and the internet surfing detailed information data.
11. The device according to any one of claims 7 to 10, wherein the building module is configured to match the to-be-tracked handset signaling data and/or the to-be-tracked internet detail data with the communication data in the multi-level tree structure model to obtain matching data corresponding to the to-be-tracked handset signaling data and/or the to-be-tracked internet detail data, where the matching data includes matching handset signaling data and/or matching internet detail data, and extract the phone number and the location information in the matching data.
12. The apparatus of any one of claims 7 to 10, further comprising:
the writing module is used for writing the telephone number and the position information into a distributed database and generating a position track of the position information within a preset duration;
and the pushing module is used for pushing the telephone number and the position track to the object.
13. An electronic device, comprising: a memory, a processor;
a memory for storing the processor-executable instructions;
wherein the processor, when executing the instructions in the memory, is configured to implement the method of any of claims 1 to 6.
14. A computer-readable storage medium having computer-executable instructions stored therein, which when executed by a processor, are configured to implement the method of any one of claims 1 to 6.
CN202010040007.1A 2020-01-15 2020-01-15 Tracking method and device, electronic equipment and storage medium Active CN111241105B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010040007.1A CN111241105B (en) 2020-01-15 2020-01-15 Tracking method and device, electronic equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010040007.1A CN111241105B (en) 2020-01-15 2020-01-15 Tracking method and device, electronic equipment and storage medium

Publications (2)

Publication Number Publication Date
CN111241105A true CN111241105A (en) 2020-06-05
CN111241105B CN111241105B (en) 2023-08-15

Family

ID=70865790

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010040007.1A Active CN111241105B (en) 2020-01-15 2020-01-15 Tracking method and device, electronic equipment and storage medium

Country Status (1)

Country Link
CN (1) CN111241105B (en)

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104717743A (en) * 2013-12-16 2015-06-17 蓝燕君 Mobile terminal tracking method and system based on signaling analysis
CN105704153A (en) * 2016-03-30 2016-06-22 中国联合网络通信集团有限公司 Method and system for tracking network access information in real time
CN107609913A (en) * 2017-09-19 2018-01-19 上海恺英网络科技有限公司 A kind of method and system of data analysis tracking
CN108174354A (en) * 2017-12-26 2018-06-15 中国联合网络通信集团有限公司 NPO mobile phones fraud recourse method and system
CN109086290A (en) * 2018-06-08 2018-12-25 广东万丈金数信息技术股份有限公司 Registration information judgment method of authenticity and system based on multi-source data decision tree
CN109218984A (en) * 2018-07-10 2019-01-15 维沃移动通信有限公司 A kind of method for tracing and mobile terminal
US20190268465A1 (en) * 2018-02-27 2019-08-29 Circinus, LLC Automated speech-to-text processing and analysis of call data apparatuses, methods and systems

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104717743A (en) * 2013-12-16 2015-06-17 蓝燕君 Mobile terminal tracking method and system based on signaling analysis
CN105704153A (en) * 2016-03-30 2016-06-22 中国联合网络通信集团有限公司 Method and system for tracking network access information in real time
CN107609913A (en) * 2017-09-19 2018-01-19 上海恺英网络科技有限公司 A kind of method and system of data analysis tracking
CN108174354A (en) * 2017-12-26 2018-06-15 中国联合网络通信集团有限公司 NPO mobile phones fraud recourse method and system
US20190268465A1 (en) * 2018-02-27 2019-08-29 Circinus, LLC Automated speech-to-text processing and analysis of call data apparatuses, methods and systems
CN109086290A (en) * 2018-06-08 2018-12-25 广东万丈金数信息技术股份有限公司 Registration information judgment method of authenticity and system based on multi-source data decision tree
CN109218984A (en) * 2018-07-10 2019-01-15 维沃移动通信有限公司 A kind of method for tracing and mobile terminal

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
郑邦峰;: "分布式系统服务链追踪与监控" *

Also Published As

Publication number Publication date
CN111241105B (en) 2023-08-15

Similar Documents

Publication Publication Date Title
CN108810116B (en) Message processing method and related product
WO2020094035A1 (en) Wireless network connection method for terminal
CN113412608B (en) Content pushing method and device, server and storage medium
CN104516918A (en) User identity information maintenance method and device, server and system
CN109582655B (en) Method and device for positioning system log and computer readable storage medium
CN111026749B (en) Service alarm method and device
CN108769142B (en) Transaction information processing method and block generation node
CN102801817A (en) Subscriber context-based pushing method and device
CN113412607B (en) Content pushing method and device, mobile terminal and storage medium
CN104244206A (en) Method, device and terminal device for processing short message
CN110569249A (en) data change pushing method and device and electronic equipment
CN107864044B (en) Information processing method and device, terminal and readable storage medium
CN103856568A (en) Terminal and system for prompting safety state of user terminal and implementation method
CN109933595B (en) Internet of things equipment information sharing system and device and terminal equipment
CN108111591B (en) Method and device for pushing message and computer readable storage medium
US10979554B2 (en) Communication method, wearable device, server, and system
CN109168138A (en) The recognition methods for the number of changing, device and equipment in net
JP6197112B2 (en) Automatic carrier detection for mobile network devices
CN111182522B (en) Group partner determining method, device, electronic equipment and computer storage medium
CN111241105B (en) Tracking method and device, electronic equipment and storage medium
CN107819761B (en) Data processing method and device and readable storage medium
CN110750561A (en) Method and device for mining associated application program
US11395129B2 (en) Virtual sim card acquisition method, subscriber terminal and server
CN109450885B (en) Network data interception method and device, electronic equipment and storage medium
CN109379704B (en) Method, device and equipment for correcting regional information of short message and storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant