CN111241105B - Tracking method and device, electronic equipment and storage medium - Google Patents

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

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Publication number
CN111241105B
CN111241105B CN202010040007.1A CN202010040007A CN111241105B CN 111241105 B CN111241105 B CN 111241105B CN 202010040007 A CN202010040007 A CN 202010040007A CN 111241105 B CN111241105 B CN 111241105B
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China
Prior art keywords
data
tracked
tree structure
level tree
information
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CN111241105A (en
Inventor
王志军
陈海波
谢攀
王蓉
谢继刚
戴智
苏轶
李梦圆
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China United Network Communications Group Co Ltd
China Unicom System Integration Ltd Corp
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China United Network Communications Group Co Ltd
China Unicom System Integration Ltd Corp
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    • 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 device, electronic equipment and storage medium. The method comprises the following steps: and collecting communication data of a plurality of users, constructing a multi-level tree structure model comprising mobile phone signaling data and internet surfing detailed list data, receiving a query 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 to-be-tracked data and the acquired communication data are compared for tracking, but in the embodiment of the disclosure, the to-be-tracked user information corresponding to the to-be-tracked data is generated according to the multi-level tree structure model through the constructed multi-level tree structure model, so that the problems of long time consumption and the like caused by sequentially comparing the to-be-tracked data with call records of all users in the prior art are avoided, the to-be-tracked user information is rapidly determined, and the technical effect of improving the tracking efficiency is further realized.

Description

Tracking method and device, electronic equipment and storage medium
Technical Field
The disclosure relates to the technical field of internet, in particular to the technical field of data processing, and particularly relates to a tracking method and device, electronic equipment and a storage medium.
Background
With the development of internet technology, telephone fraud events occur more frequently, so how to locate and track agents of telephone fraud events has become a focus of attention.
In the prior art, when a query request of data to be tracked is received, call records of all users obtained based on monitoring are obtained, and the data to be tracked and the call records of all users in the call records are sequentially compared until the call records corresponding to the data to be tracked are determined, and agents of fraud events are tracked based on the call records.
However, in 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 all users in the call records in turn is long, so that the tracking efficiency is low.
Disclosure of Invention
The disclosure provides a tracking method and device, electronic equipment and a storage medium, which are used for solving the problems of long time consumption and low tracking efficiency caused by sequentially comparing data to be tracked with call records of all users in call records in the prior art.
In one aspect, embodiments of the present disclosure provide a tracking method, the method comprising:
Collecting communication data of a plurality of users, wherein the communication data comprises mobile phone signaling data and internet surfing detail data;
constructing a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detail data;
receiving a query request carrying data to be tracked, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed 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, wherein the user information to be tracked at least comprises telephone numbers and position information.
In some embodiments, the building a multi-level tree structure model including the handset signaling data and the internet surfing detail data includes:
constructing the multi-level tree structure model according to the region information in the communication data; or alternatively, the process may be performed,
and constructing the multi-level tree structure model according to the region information and the sex information in the communication data.
In some embodiments, the constructing the multi-level tree structure model from the region information in the communication data includes:
extracting the region information in the communication data;
Constructing branches of an initial tree structure by taking areas in the area information as nodes to obtain a multi-level tree structure;
generating the multi-level tree structure model according to the multi-level tree structure, the mobile phone signaling data and the internet detail 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 includes:
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 a region in the region information as a node to obtain a first multi-level tree structure;
constructing sub branches of the first multi-level tree structure by taking the gender in the gender information as a node to obtain a second multi-level 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 detail data.
In some embodiments, the generating the to-be-tracked user information corresponding to the to-be-tracked data according to the multi-level tree structure model includes:
matching the mobile phone signaling data to be tracked and/or the internet surfing detail 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 internet surfing detail data to be tracked, wherein the matching data comprises the mobile phone signaling data to be matched and/or the internet surfing detail data to be matched;
And extracting the telephone number and the position information in the matching data.
In some embodiments, after the generating the to-be-tracked user information corresponding to the to-be-tracked data according to the multi-level tree structure model, the 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;
pushing the phone number and the location track to the object.
In another aspect, embodiments of the present disclosure further provide a tracking device, the device including:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring communication data of a plurality of users, wherein the communication data comprises mobile phone signaling data and Internet surfing detailed list data;
the construction module is used for constructing a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detailed list data;
the device comprises a receiving module, a processing module and a processing module, wherein the receiving module is used for receiving a query request carrying data to be tracked, which is sent by an object, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detail 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 telephone numbers and position information.
In some embodiments, the building module is configured to build the multi-level tree structure model according to the region information in the communication data; or constructing the multi-level tree structure model according to the region information and the sex information in the communication data.
In some embodiments, the building module is configured to extract the area information in the communication data, build branches of an initial tree structure with an area in the area information as a node, 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 detail data.
In some embodiments, the building module is configured to extract the region information in the communication data, extract the gender information in the communication data, build a first branch of an initial tree structure with a region in the region information as a node, 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, 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 detail data.
In some embodiments, the building module is configured to match the to-be-tracked mobile phone signaling data and/or to-be-tracked internet surfing detailed data with the communication data in the multi-level tree structure model to obtain matching data corresponding to the to-be-tracked mobile phone signaling data and/or to-be-tracked internet surfing detailed data, where the matching data includes matching mobile phone signaling data and/or matching internet surfing detailed data, and the phone number and the location information in the matching data are extracted.
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;
the memory is used for storing the processor executable instructions;
wherein the processor, when executing the instructions in the memory, is configured to implement the method as described in any of the embodiments above.
In another aspect, the disclosed embodiments also provide a computer-readable storage medium having stored therein computer-executable instructions that, when executed by a processor, are configured to implement the method of any of the above embodiments.
The disclosure provides a tracking method and device, an electronic device and a storage medium, wherein the tracking method comprises the following steps: and 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 a query request carrying data to be tracked sent by an object, 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 the data to be tracked with the acquired communication data, but in the embodiment of the 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 disclosure, the multi-level tree structure model is constructed so as to generate the user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, so that the problems of long time consumption and the like caused by sequentially comparing the data to be tracked with call records of all users in the prior art are avoided, the user information to be tracked is rapidly determined, and the technical effect of improving the tracking efficiency is further realized.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is an application scenario schematic diagram of a tracking method according to an embodiment of the disclosure;
FIG. 2 is a flow chart of a tracking method according to an embodiment of the disclosure;
FIG. 3 is a flow chart of a method of constructing a multi-level tree structure model from 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 present disclosure;
FIG. 5 is a flowchart of 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 disclosure;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
Specific embodiments of the present disclosure have been shown by way of the above drawings and will be described in more detail below. These drawings and the written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the disclosed concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
In the prior art, the call records corresponding to the to-be-tracked data are determined from the call records mainly by comparing the to-be-tracked data with the call records of each user in turn, and the comparison time is long when the call records of each user are compared one by one because the call records of each user are very large, so that the efficiency of determining the call records of the to-be-tracked user is lower, and the tracking efficiency is low. In order to solve the problems caused by sequential comparison in the prior art, the inventor obtains the technical scheme implemented by the disclosure through creative labor. In the embodiment of the disclosure, the multi-level tree structure model is constructed so as to generate the user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, so that the problems of long time consumption and the like caused by sequentially comparing the data to be tracked with call records of all users are avoided, 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 a scene shown in fig. 1.
In the application scenario shown in fig. 1, the base station 100 establishes communication links of each mobile phone 200 (3 mobile phones are exemplarily shown in fig. 1, which is only for exemplary illustration, and is not to be construed as limiting the embodiments of the present disclosure), so as to perform telephone communication, sms communication, etc. between users of each mobile phone 200, to form mobile phone signaling data. And each cell phone 200 can also form internet surfing detailed data based on the internet surfing of the communication link.
The base station 100 transmits the mobile phone signaling data and the internet detail data to the server 300.
The user 400 sends a query request to the server 300 through the computer 500.
The server 300 performs the tracking method of the embodiments of the present disclosure, and determines the user information to be tracked, that is, determines the phone number and 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 telephone number and the location information.
The user 400 monitors and apprehends the user to be tracked based on the telephone number and the location information, and the like.
The following describes the technical scheme of the present disclosure and how the technical scheme of the present disclosure solves the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present disclosure will be described below with reference to the accompanying drawings.
In one aspect, an embodiment of the present disclosure provides a tracking method applicable to the above application scenario.
Referring to fig. 2, fig. 2 is a flowchart illustrating a tracking method according to an embodiment of the disclosure.
As shown in fig. 2, the method includes:
s101: and 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 according to the embodiments of the present disclosure may be a tracking device, and the tracking device may be a server (see the above examples) or a terminal (such as a computer).
The mobile phone signaling data may include call detail data generated when the user calls through the user terminal, such as calling number, called number, call duration, call starting time, call ending time, calling number attribution and called number attribution; the mobile phone signaling data may also include data generated when the user receives and transmits a short message through the user terminal.
The internet details data may include data generated by the user browsing the web page through the user terminal using traffic and free network (such as WiFi and hot spot, etc.), such as web site browsing the web page, browsing frequency and browsing duration, etc.
User terminals include, but are not limited to, cell phones, smart bracelets, and ipads.
S102: and constructing a multi-level tree structure model comprising mobile phone signaling data and internet surfing detail data.
The multi-level tree structure model is a model of a tree structure comprising a plurality of branches, and one branch at least comprises one piece of mobile phone signaling data or one piece of internet detail data.
In the prior art, data to be tracked is compared with acquired communication data, so that communication data corresponding to the tracked data is determined from the communication data, and telephone numbers and position information are determined from the determined communication data.
In the embodiment of the disclosure, after the mobile phone signaling data and the internet detail data are acquired, a multi-level tree structure model is constructed based on the mobile phone signaling data and the internet detail data so as to perform subsequent tracking operation based on the multi-level tree structure model.
In some embodiments, handset signaling data and internet detail data are aggregated into a queue test cluster (kafka cluster) to build a multi-level tree structure model based on the kafka cluster.
S103: and receiving a query request carrying data to be tracked, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed data to be tracked.
When the main body for executing the tracking method of the embodiment of the present disclosure is a server, then the object may be a computer. Specifically, the user inputs a query request to the computer through a clicking operation (such as clicking a keyboard or a display interface of the computer) or a voice operation, and the computer transmits the query request input by the user to the server.
When the main body for 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 (such as 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 detail data, and the mobile phone signaling data and the internet detail data are generated in real time, the multi-level tree structure model is also in a continuously updated state. In some embodiments, the multi-level tree structure model may be updated by setting a time interval based on the cell signaling data and the internet detail data acquired during 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 derivative stream (streamlet).
Compared with the prior art that data processing is realized through discrete stream (spark stream), the slipdream has the characteristics of lower time delay and high data processing efficiency. Therefore, in the embodiment of the disclosure, generating the user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model is realized based on the streamlining, so that the efficiency of determining the user to be tracked can be improved.
The embodiment of the disclosure provides a novel tracking method, which comprises the following steps: and 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 a query request carrying data to be tracked sent by an object, 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 the data to be tracked with the acquired communication data, but in the embodiment of the 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 disclosure, the multi-level tree structure model is constructed so as to generate the user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model, so that the problems of long time consumption and the like caused by sequentially comparing the data to be tracked with call records of all users in the prior art are avoided, the user information to be tracked is rapidly determined, and the technical effect of improving the tracking efficiency is further realized.
In some embodiments, S102 comprises:
s1021: and constructing a multi-level tree structure model according to the region information in the communication data. Or alternatively, the process may be performed,
s1022: and constructing a multi-level tree structure model according to the region information and the sex information in the communication data.
In the embodiment of the disclosure, two methods for constructing a multi-level tree structure model are provided, one is to construct the multi-level 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 can be seen in conjunction with fig. 3 (fig. 3 is a flow chart 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), in some embodiments, S1021 includes:
s11: region information in the 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 will carry the area information of the mobile phone a, such as province, city, county, etc. to which the mobile phone a belongs.
S12: and constructing branches of an initial tree structure by taking areas in the regional information as nodes to obtain a multi-level tree structure.
As can be seen from the above examples, the multi-level tree structure may include a provincial region parent branch including at least one municipal region branch including at least one county region branch, and so on.
S13: generating a multi-level tree structure model according to the multi-level tree structure, the mobile phone signaling data and the internet detail data.
In this step, it may specifically include: after the multi-level tree structure is built, the mobile phone signaling data and the internet surfing detailed list data are written into the corresponding branches to generate a multi-level 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 C city, the mobile phone signaling data of the user a calling the user B is written into the branch corresponding to C city.
As can be seen in conjunction with fig. 4 (fig. 4 is a flow chart 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 present disclosure), in some embodiments, S1022 includes:
s21: region information in the communication data is extracted, and sex information in the communication data is extracted, respectively.
In the embodiment of the disclosure, information of two aspects in communication data is extracted, the information of one aspect is area information, and the information of the other aspect is gender information. Wherein, the description of the extraction area information can be seen in S11. The description about extracting sex information is as follows:
if the gender information is extracted from the mobile phone signaling data, based on the above example, 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 mobile phone a mobile phone number, the identity information (such as identity card information) of the user a used when the mobile phone number is registered is obtained from the mobile phone signaling data, and the gender information is extracted from the identity information.
If the gender information is extracted from the internet detail data, such as that the user a browses a certain webpage (such as a webpage corresponding to a mailbox) to generate the internet detail data, the registration information (such as user and identity information) when the user a registers the webpage is obtained from the internet detail data, and the gender information is extracted from the registration information.
Wherein the sex information includes male and female.
S22: and constructing a first branch of the initial tree structure by taking the region in the regional information as a node to obtain a first multi-level tree structure.
The description of S22 may refer to S12, and will not be repeated here.
S23: and constructing sub branches of the first multi-level tree structure by taking the gender in the gender information as a node to obtain a second multi-level tree structure.
After the first multi-level tree structure is constructed, sub branches with gender as nodes are added on the basis of the first multi-level tree structure. For example, based on the above example, two sub-branches are added on the basis of the sub-branches of the county region, so as to obtain the sub-branches of the male sex and the female sex corresponding to the county region.
S24: generating a multi-level tree structure model according to the second multi-level tree structure, the mobile phone signaling data and the Internet detail data.
In this step, it may specifically include: after the multi-level tree structure is built, the mobile phone signaling data and the internet surfing detailed list data are written into the corresponding branches to generate a multi-level 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 C city and the sex 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 sex of the female in C city.
In some embodiments, S104 comprises:
s41: and matching the mobile phone signaling data to be tracked and/or the internet detail data to be tracked with 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 internet detail data to be tracked, wherein the matching data comprises the mobile phone signaling data to be matched and/or the internet detail data to be matched.
In some embodiments, if the data to be tracked includes 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 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 call times, call addresses, call frequencies, call duration and sex information, and mobile phone signaling data matched with the call times, call addresses, call frequencies, call duration and sex information is obtained from the multi-level tree structure model.
In some embodiments, the specific matching process comprises: extracting to-be-tracked area information (i.e. call address) in the to-be-tracked mobile phone signaling data, matching the to-be-tracked area information with the area information of the branches in the multi-level tree structure model, determining the branches corresponding to the to-be-tracked area information, and matching the to-be-tracked mobile phone signaling data with the determined branches according to other auxiliary information (such as call times, call frequency and call duration) to obtain mobile phone signaling data corresponding to the to-be-tracked mobile phone signaling data.
In other embodiments, if the multi-level tree structure model is a sub-branch that also includes gender information, the specific matching process includes: extracting area information to be tracked (namely call addresses) in the mobile phone signaling data to be tracked, matching the area information to be tracked with the area information of branches in the multi-level tree structure model, determining branches corresponding to the area information to be tracked, selecting 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 auxiliary 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 to-be-tracked data includes to-be-tracked internet details data, matching the to-be-tracked internet details data with internet details data in the multi-level tree structure model to obtain internet details data corresponding to the to-be-tracked internet details data.
For example, the internet detail data to be tracked includes access number, access address, access frequency, access duration and sex information, and the internet detail data matched with the access number, access address, access frequency, access duration and sex information is obtained from the multi-level tree structure model.
In some embodiments, the specific matching process comprises: extracting the to-be-tracked area information (i.e. call address) in the to-be-tracked internet detail data, matching the to-be-tracked area information with the area information of the branches in the multi-level tree structure model, determining the branches corresponding to the to-be-tracked area information, and matching the to-be-tracked internet detail data of the branches according to other auxiliary information (such as access times, access frequency and access time length) to obtain the internet detail data corresponding to the to-be-tracked internet detail data.
In other embodiments, if the multi-level tree structure model is a sub-branch that also includes gender information, the specific matching process includes: extracting area information to be tracked (i.e. access addresses) in the internet detail data to be tracked, matching the area information to be tracked with area information of branches in the multi-level tree structure model, determining branches corresponding to the area information to be tracked, selecting sub-branches corresponding to female gender from the determined branches, and matching the internet detail data of the determined sub-branches according to other auxiliary information (such as access times, access frequency and access time length) to obtain the internet detail data corresponding to the internet detail data to be tracked.
In some embodiments, if the to-be-tracked data includes to-be-tracked mobile phone signaling data and to-be-tracked internet detail data, matching the to-be-tracked mobile phone signaling data with mobile phone signaling data in the multi-level tree structure model to obtain matched mobile phone signaling data, and matching the to-be-tracked internet detail data with internet detail data in the multi-level tree structure model to obtain matched internet detail data.
For the specific matching method when the data to be tracked includes the signaling data of the mobile phone to be tracked and the internet details to be tracked, refer to the above example, and the details are not repeated here.
S42: telephone numbers and location information in the matching data are extracted.
Referring to fig. 5, fig. 5 is a flowchart illustrating a tracking method according to another embodiment of the disclosure.
As shown in fig. 5, the method includes:
s201: and collecting communication data of a plurality of users, wherein the communication data comprises mobile phone signaling data and Internet surfing detailed list data.
The description of S201 may refer to S101, and will not be repeated here.
S202: and constructing a multi-level tree structure model comprising mobile phone signaling data and internet surfing detail data.
The description of S202 may refer to S102, and will not be repeated here.
S203: and receiving a query request carrying data to be tracked, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed data to be tracked.
The description of S203 may refer to S103, and will not be repeated here.
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.
The description of S204 may refer to S104, and will not be repeated here.
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 examples, the mobile phone signaling data, the internet detail data and the multi-level tree structure model may be updated continuously, so that the phone number and the location information are written into a distributed database (hbase), and a location track of the location information within a preset duration, that is, a movement track of the user to be tracked, is generated.
S206: the phone number and the location track are pushed to the object.
In some embodiments, the phone number and location trajectory may be pushed to the object via file transfer protocol (ftp) for further tracking and monitoring of the user to be tracked by the object; or so that the object makes an arrest to the user to be tracked, etc.
In some embodiments, after constructing the multi-level tree structure model, the method further comprises: and if a target inquiry 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 multi-level 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 realize the inquiry based on the api interface.
According to another aspect of the disclosed embodiments, the disclosed embodiments also provide 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 processing module and a processing module, wherein the acquisition module 1 is used for acquiring communication data of a plurality of users, wherein the communication data comprises mobile phone signaling data and Internet surfing detailed list data;
the construction module 2 is used for constructing a multi-level tree structure model comprising the mobile phone signaling data and the internet detail list data;
the receiving module 3 is configured to receive a query request carrying data to be tracked sent by an object, where the data to be tracked includes signaling data of a mobile phone to be tracked and/or internet surfing detailed data to be tracked;
And the generating module 4 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 telephone numbers and position information.
In some embodiments, the building module 2 is configured to build the multi-level tree structure model according to the area information in the communication data; or constructing the multi-level tree structure model according to the region information and the sex information in the communication data.
In some embodiments, the building module 2 is configured to extract the area information in the communication data, build branches of an initial tree structure with an area in the area information as a node, 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 detail data.
In some embodiments, the building module 2 is configured to extract the region information in the communication data, extract the gender information in the communication data, build a first branch of an initial tree structure with a region in the region information as a node, 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, 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 detail data.
In some embodiments, the building module 2 is configured to match the to-be-tracked mobile phone signaling data and/or to-be-tracked internet surfing detailed data with the communication data in the multi-level tree structure model to obtain matching data corresponding to the to-be-tracked mobile phone signaling data and/or to-be-tracked internet surfing detailed data, where the matching data includes matching mobile phone signaling data and/or matching internet surfing detailed data, and extract the phone number and the location 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;
a pushing module 6, configured to push the phone number and the location 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 the processor, when executing the instructions in the memory, is configured to implement the method as described in 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 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 configured to execute executable modules, such as computer programs, stored in the memory.
The memory may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. Communication connection between the system network element and at least one other network element is achieved through at least one communication interface, which may be wired or wireless, and the internet, wide area network, local network, metropolitan area network, etc. may be used.
The bus may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be divided into address buses, data buses, control buses, etc.
The memory is used for storing a program, and the processor executes the program after receiving an execution instruction, so that the method disclosed in any embodiment of the foregoing disclosure may be applied to the processor or implemented by the processor.
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 by instructions in the form of software. The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but may also be a digital signal processor (Digital SignalProcessing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The steps of a method disclosed in connection with the embodiments of the present disclosure may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method.
According to another aspect of the disclosed embodiments, the disclosed embodiments also provide a computer-readable storage medium having stored therein computer-executable instructions that, when executed by a processor, are configured to implement a method as described in any of the above embodiments.
The reader will appreciate that in the description of this specification, a description of terms "one embodiment," "some embodiments," "an example," "a particular 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, schematic representations of the above terms are not necessarily directed 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, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and units described above may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purposes of the embodiments of the present disclosure.
In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present disclosure is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods 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, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It should also be understood that, in the embodiments of the present disclosure, the sequence number of each process described above does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.
The foregoing is merely a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto, and any equivalent modifications or substitutions will be apparent to those skilled in the art within the scope of the present disclosure, and these modifications or substitutions should be covered in the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.

Claims (12)

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 detail data;
constructing a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detail data;
receiving a query request carrying data to be tracked, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detailed 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, wherein the user information to be tracked at least comprises telephone numbers and position information;
the generating the user information to be tracked corresponding to the data to be tracked according to the multi-level tree structure model comprises the following steps:
Matching the mobile phone signaling data to be tracked and/or the internet surfing detail 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 internet surfing detail data to be tracked, wherein the matching data comprises the mobile phone signaling data to be matched and/or the internet surfing detail data to be matched;
and extracting the telephone number and the position information in the matching data.
2. The method of claim 1, wherein said constructing a multi-level tree structure model comprising said handset signaling data and said internet surfing detail data comprises:
constructing the multi-level tree structure model according to the region information in the communication data; or alternatively, the process may be performed,
and constructing the multi-level tree structure model according to the region information and the sex information in the communication data.
3. The method of claim 2, wherein constructing the multi-level tree structure model from 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 areas in the area information as nodes to obtain a multi-level tree structure;
Generating the multi-level tree structure model according to the multi-level tree structure, the mobile phone signaling data and the internet detail data.
4. The method of claim 2, wherein constructing the multi-level tree structure model from 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 a region in the region information as a node to obtain a first multi-level tree structure;
constructing sub branches of the first multi-level tree structure by taking the gender in the gender information as a node to obtain a second multi-level 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 detail data.
5. The method according to any one of claims 1 to 4, characterized in that after the generating of the user information to be tracked corresponding to the data to be tracked from the multi-level tree structure model, the 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;
Pushing the phone number and the location track to the object.
6. A tracking device, the device comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring communication data of a plurality of users, wherein the communication data comprises mobile phone signaling data and Internet surfing detailed list data;
the construction module is used for constructing a multi-level tree structure model comprising the mobile phone signaling data and the internet surfing detailed list data;
the device comprises a receiving module, a processing module and a processing module, wherein the receiving module is used for receiving a query request carrying data to be tracked, which is sent by an object, wherein the data to be tracked comprises mobile phone signaling data to be tracked and/or internet surfing detail data to be tracked;
the generation 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, and the user information to be tracked at least comprises telephone numbers and position information;
the construction module is used for matching the mobile phone signaling data to be tracked and/or the internet surfing detail 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 internet surfing detail data to be tracked, wherein the matching data comprises the mobile phone signaling data to be matched and/or the internet surfing detail data to be matched, and the telephone number and the position information in the matching data are extracted.
7. The apparatus of claim 6, wherein the building module is configured to build the multi-level tree structure model according to region information in the communication data; or constructing the multi-level tree structure model according to the region information and the sex information in the communication data.
8. The apparatus of claim 7, wherein the construction module is configured to extract the area information in the communication data, construct branches of an initial tree structure with an area in the area information as a node, 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 detail data.
9. The apparatus of claim 7, wherein the building module is configured to extract the region 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 region 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 detail data.
10. The apparatus according to any one of claims 6 to 9, 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.
11. An electronic device, comprising: a memory, a processor;
the memory is used for storing the processor executable instructions;
wherein the processor, when executing the instructions in the memory, is configured to implement the method of any one of claims 1 to 5.
12. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1 to 5.
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