CN108280139B - POI data processing method, device, equipment and computer readable storage medium - Google Patents
POI data processing method, device, equipment and computer readable storage medium Download PDFInfo
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- CN108280139B CN108280139B CN201711456176.8A CN201711456176A CN108280139B CN 108280139 B CN108280139 B CN 108280139B CN 201711456176 A CN201711456176 A CN 201711456176A CN 108280139 B CN108280139 B CN 108280139B
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
Abstract
The invention provides a POI data processing method, a POI data processing device, POI data processing equipment and a computer readable storage medium. According to the method and the device, the POI data of the POI submitted by the user are obtained, and then risk identification processing is carried out on the POI data according to the historical behavior data of the user and the pre-established risk database to obtain a risk identification processing result, so that online decision processing can be carried out on the POI data according to the risk identification processing result, and the POI data which are not allowed to be online are identified in time.
Description
[ technical field ] A method for producing a semiconductor device
The present invention relates to electronic map technologies, and in particular, to a method, an apparatus, a device, and a computer-readable storage medium for processing Point of Interest (POI) data.
[ background of the invention ]
With the development of communication technology, terminals integrate more and more functions, so that more and more corresponding Applications (APPs) are included in a system function list of the terminal. Some applications may involve Location Based Services (LBS), also called Location services, such as hundred degree maps. In LBS, a server corresponding to an application stores a large amount of Point of Interest (POI) data, so as to provide a query result based on LBS query to the application, i.e., a client. Generally, POI data may include information about name, address, coordinates, picture, phone, etc. and may be obtained by manual field collection. In the prior art, a new POI data function is provided for a user, and the user can submit some POI data that are not included in an electronic map by using the new POI data function.
However, due to the randomness of data submission by the user, in some cases, for example, the data submission is illegal, the data submission relates to promotion content, and the like, the POI data may be POI data that is not allowed to be online, that is, is not allowed to be added to the POI data of the electronic map, and therefore, how to identify the POI data that is not allowed to be online is a problem to be solved urgently.
[ summary of the invention ]
Aspects of the present invention provide a method, an apparatus, a device and a computer-readable storage medium for processing POI data, which are used to identify POI data that are not allowed to be added.
In one aspect of the present invention, a method for processing POI data is provided, including:
the method comprises the steps of obtaining POI data of POI submitted by a user;
according to the historical behavior data of the user and a pre-established risk database, carrying out risk identification processing on the POI data to obtain a risk identification processing result;
and performing online decision processing on the POI data according to the risk identification processing result.
The above-described aspects and any possible implementations further provide an implementation in which the risk identification data includes at least one of:
risk keyword data;
risk coordinate data;
risk picture data;
risk user data; and
risk POI data.
The above-described aspect and any possible implementation manner further provide an implementation manner, where performing online decision processing on the POI data according to the risk identification processing result includes:
if the risk identification processing result indicates that no risk exists, performing online processing on the POI data;
and if the risk identification processing result indicates that a risk exists, the POI data is not executed with online processing.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, where performing online decision processing on the POI data according to the risk identification processing result further includes:
and if the risk identification processing result indicates that a risk exists, executing the POI data discarding processing.
In another aspect of the present invention, there is provided a POI data processing apparatus, including:
an acquisition unit configured to acquire POI data of a POI submitted by a user
The identification unit is used for carrying out risk identification processing on the POI data according to the historical behavior data of the user and a pre-established risk database so as to obtain a risk identification processing result;
and the decision unit is used for performing online decision processing on the POI data according to the risk identification processing result.
The above-described aspects and any possible implementations further provide an implementation in which the risk identification data includes at least one of:
risk keyword data;
risk coordinate data;
risk picture data;
risk user data; and
risk POI data;
the above-mentioned aspects and any possible implementation further provide an implementation, and the decision unit is specifically configured to
If the risk identification processing result indicates that no risk exists, performing online processing on the POI data;
and if the risk identification processing result indicates that a risk exists, the POI data is not executed with online processing.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, where the decision unit is further configured to
And if the risk identification processing result indicates that a risk exists, executing the POI data discarding processing.
In another aspect of the present invention, there is provided an apparatus comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a method of processing POI data as provided in an aspect above.
In another aspect of the present invention, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of processing POI data as provided in the above-described aspect.
According to the technical scheme, the POI data of the POI submitted by the user are obtained, and then the risk identification processing is carried out on the POI data according to the historical behavior data of the user and the pre-established risk database to obtain the risk identification processing result, so that the POI data can be subjected to online decision processing according to the risk identification processing result, and the POI data which are not allowed to be online are identified in time.
In addition, by adopting the technical scheme provided by the invention, the quality reduction of the online POI data caused by the submission of malicious POI data by lawless persons can be avoided, and the reliability of the online POI data can be effectively improved.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed in the embodiments or the prior art descriptions will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without inventive labor.
Fig. 1 is a schematic flowchart of a POI data processing method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a POI data processing apparatus according to another embodiment of the present invention;
FIG. 3 is a block diagram of an exemplary computer system/server 12 suitable for use in implementing embodiments of the present invention.
[ detailed description ] embodiments
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
It should be noted that the terminal according to the embodiment of the present invention may include, but is not limited to, a mobile phone, a Personal Digital Assistant (PDA), a wireless handheld device, a Tablet Computer (Tablet Computer), a Personal Computer (PC), an MP3 player, an MP4 player, a wearable device (e.g., smart glasses, smart watch, smart bracelet, etc.), and the like.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Fig. 1 is a schematic flowchart of a method for processing POI data according to an embodiment of the present invention, as shown in fig. 1.
101. And acquiring POI data of the POI submitted by the user.
102. And performing risk identification processing on the POI data according to the historical behavior data of the user and a pre-established risk database to obtain a risk identification processing result.
103. And performing online decision processing on the POI data according to the risk identification processing result.
It should be noted that part or all of the execution subjects 101 to 103 may be an application located at the local terminal, or may also be a functional unit such as a plug-in or Software Development Kit (SDK) set in the application located at the local terminal, or may also be a processing engine located in a server on the network side, or may also be a distributed system located on the network side, which is not particularly limited in this embodiment.
It is to be understood that the application may be a native app (native app) installed on the terminal, or may also be a web page program (webApp) of a browser on the terminal, and this embodiment is not particularly limited thereto.
In this way, risk identification processing is performed on POI data according to historical behavior data of the user and a pre-established risk database by acquiring POI data of POI submitted by the user to obtain a risk identification processing result, so that online decision processing can be performed on the POI data according to the risk identification processing result, and POI data which are not allowed to be online are identified in time.
Optionally, in a possible implementation manner of this embodiment, before 101, a new POI page may be further provided for the user to provide POI data of the POI. Generally, POI data to be provided may include information of several aspects, such as name, address, coordinate, picture, phone, etc., if the POI data provided by the user lacks specified content, such as the content of name, address, coordinate, picture, etc., the user cannot submit the data when operating the submission control, and the POI data submission fails. Only if the POI data provided by the user contains all the specified contents, the data can be successfully submitted when the user operates the submission control. The POI data of these successfully submitted POIs becomes the data source acquired in 101.
Currently, some websites record user behavior for a particular user. The data obtained from these records is the user's historical behavior data employed in 102.
For example, according to the historical behavior of the registered user, the user historical behavior data of the user is recorded. In this case, it is necessary to record the historical behavior of the registered user after login, so as to form the user historical behavior data of the registered user. Therefore, the user history behavior data at this time is premised on the fact that a registered user is required to perform a login operation.
Or, for another example, according to the historical behavior of the browser user, recording the user historical behavior data of the user. In this case, it is necessary to record the historical behavior generated by any user after using the browser of the same terminal to form the user historical behavior data of the browser user. Therefore, the historical behavior data of the user at this time is based on the premise that a browsing operation needs to be performed by using a specific browser, and is not targeted to a specific user.
Or, for another example, according to the historical behavior of the end user, recording the user historical behavior data of the user. In this case, it is necessary to record the historical behavior generated by any user after using the same terminal to form the user historical behavior data of the terminal user. Therefore, the historical behavior data of the user at this time is based on the premise that a browsing operation needs to be performed by using a specific terminal, and is not targeted to a specific user.
Taking the user historical behavior data generated by the user operating based on the newly added POI page as an example, the user historical behavior data adopted in the implementation may include, but is not limited to, at least one of the following data:
the submission frequency of the POI data submitted by the user;
a user submits geographical distribution of POI data;
the user submits the historical adoption rate of the POI data;
the number of accounts of the user; and
number of terminals of the user.
Specifically, some existing data mining methods may be specifically adopted to mine the user historical behavior data of the user to determine whether the user is a risk user, for example, data mining methods such as classification, regression analysis, clustering, association rule, feature, variation and deviation analysis, and Web page mining, which is not particularly limited in this embodiment.
For example, if the submission frequency of the POI data submitted by the user is greater than or equal to the preset frequency domain threshold, it can be confirmed that the POI data submitted by the user is at risk.
Or, for another example, the location of the user is near a certain coordinate, but the POI data of the multiple POIs submitted by the user are distributed in different cities or are distributed at a position far away from the location of the user, so that it can be confirmed that the POI data submitted by the user is at risk.
Or, for another example, if the historical adoption rate of the POI data submitted by the user is less than or equal to the preset adoption rate threshold, it may be determined that the POI data submitted by the user is at risk.
Or, for another example, if the number of accounts or the number of terminals of the user is greater than or equal to a preset number threshold, it may be determined that the POI data submitted by the user is at risk.
Optionally, in a possible implementation manner of this embodiment, in 102, the risk identification data may include, but is not limited to, at least one of the following data:
risk keyword data;
risk coordinate data;
risk picture data;
risk user data; and
risk POI data.
Wherein the content of the first and second substances,
the risk keyword data may include at least one wind control entry, each wind control entry may include a matching word and a plurality of exemption words, and may be specifically represented by a regular expression, as shown in table 1.
TABLE 1 Risk keywords data List
When the name or address included in the POI data submitted by the user contains the wind control entry hit by using the risk keyword data, it can be confirmed that the POI data has a risk.
The risk coordinate data may be a designated area, for example, a circular area with a 1 km radius and a skyhook as a center. When the coordinates included in the POI data submitted by the user are within the designated area, it can be confirmed that the POI data is at risk.
The risk picture data can be designated picture characteristic information, such as yellow-related information, gambling-related information and the like. When the pictures included in the POI data submitted by the user are identified to contain the characteristic information of the specified pictures, the POI data can be confirmed to have risks.
The risky user data may include user data of a user who may be at risk, such as an identifier of a terminal used by the user, an IP address of the terminal used by the user, and the like. When the terminal identifier used by the user or the IP address of the terminal used by the user is in the risk user data, it can be confirmed that the POI data submitted by the user has a risk. Further, user data of the user is added to the risky user data.
The risk POI data may include POI data of POIs that may be at risk, such as names, addresses, coordinates, pictures, phones, and the like of POIs. When the name or address included in the POI data provided by the user is in the risky user data, it may be confirmed that the POI data submitted by the user is risky. Further, the POI data is added to the risk POI data.
Optionally, in a possible implementation manner of this embodiment, in 103, the online processing of the POI data may be specifically executed according to the risk identification processing result, or the online processing of the POI data is not executed.
For example, if the risk identification processing result indicates that no risk exists, the online processing of the POI data may be performed;
or, for another example, if the risk identification processing result indicates that there is a risk, the online processing of the POI data may not be performed.
Further, if the risk identification processing result indicates that there is a risk, the POI data discarding process may be performed.
By this, the work of adding POIs on the electronic map is completed.
In this embodiment, risk identification processing is performed on the POI data according to the historical behavior data of the user and a pre-established risk database by acquiring the POI data of the POI submitted by the user to obtain a risk identification processing result, so that online decision processing can be performed on the POI data according to the risk identification processing result, and the POI data which is not allowed to be online can be identified in time.
In addition, by adopting the technical scheme provided by the invention, the quality reduction of the online POI data caused by the submission of malicious POI data by lawless persons can be avoided, and the reliability of the online POI data can be effectively improved.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
Fig. 2 is a schematic structural diagram of a POI data processing apparatus according to another embodiment of the present invention, as shown in fig. 2. The POI data processing apparatus of the present embodiment may include an acquisition unit 21, a recognition unit 22, and a decision unit 23. The acquiring unit 21 is configured to acquire POI data of a POI submitted by a user; the identification unit 22 is configured to perform risk identification processing on the POI data according to the historical behavior data of the user and a pre-established risk database to obtain a risk identification processing result; and the decision unit 23 is configured to perform online decision processing on the POI data according to the risk identification processing result.
It should be noted that, part or all of the POI data processing apparatus provided in this embodiment may be an application located in the local terminal, or may also be a functional unit such as a Software Development Kit (SDK) or a plug-in provided in the application located in the local terminal, or may also be a processing engine located in a server on the network side, or may also be a distributed system located on the network side, which is not particularly limited in this embodiment.
It is to be understood that the application may be a native app (native app) installed on the terminal, or may also be a web page program (webApp) of a browser on the terminal, and this embodiment is not particularly limited thereto.
Optionally, in a possible implementation manner of this embodiment, the risk identification data may include, but is not limited to, at least one of the following data:
risk keyword data;
risk coordinate data;
risk picture data;
risk user data; and
risk POI data.
Optionally, in a possible implementation manner of this embodiment, the decision unit 23 may be specifically configured to, if the risk identification processing result indicates that no risk exists, execute online processing of the POI data; and if the risk identification processing result indicates that a risk exists, the POI data is not executed with online processing.
In this implementation manner, the decision unit 23 may be further configured to perform discarding processing on the POI data if the risk identification processing result indicates that there is a risk.
It should be noted that the method in the embodiment corresponding to fig. 1 may be implemented by the processing apparatus of POI data provided in this embodiment. For a detailed description, reference may be made to relevant contents in the embodiment corresponding to fig. 1, and details are not described here.
In this embodiment, the POI data of the POI submitted by the user is acquired by the acquisition unit, and then the identification unit performs risk identification processing on the POI data according to the historical behavior data of the user and the pre-established risk database to obtain a risk identification processing result, so that the decision unit can perform online decision processing on the POI data according to the risk identification processing result, thereby identifying the POI data which is not allowed to be online in time.
In addition, by adopting the technical scheme provided by the invention, the quality reduction of the online POI data caused by the submission of malicious POI data by lawless persons can be avoided, and the reliability of the online POI data can be effectively improved.
FIG. 3 illustrates a block diagram of an exemplary computer system/server 12 suitable for use in implementing embodiments of the present invention. The computer system/server 12 shown in FIG. 3 is only one example and should not be taken to limit the scope of use or functionality of embodiments of the present invention.
As shown in FIG. 3, computer system/server 12 is in the form of a general purpose computing device. The components of computer system/server 12 may include, but are not limited to: one or more processors or processing units 16, a storage device or system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Computer system/server 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The computer system/server 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 3, and commonly referred to as a "hard drive"). Although not shown in FIG. 3, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The computer system/server 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 26, etc.), with one or more devices that enable a user to interact with the computer system/server 12, and/or with any devices (e.g., network card, modem, etc.) that enable the computer system/server 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 44. Also, the computer system/server 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet) via the network adapter 20. As shown, network adapter 20 communicates with the other modules of computer system/server 12 via bus 18. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the computer system/server 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing the POI data processing method provided in the embodiment corresponding to fig. 1.
Another embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for processing POI data provided in the embodiment corresponding to fig. 1.
In particular, any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or page components may be combined or integrated into another system, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The 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 embodiment.
In addition, functional units in the embodiments of the present invention 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, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for processing POI data, comprising:
the method comprises the steps of obtaining POI data of POI submitted by a user;
according to the historical behavior data of the user and a pre-established risk database, carrying out risk identification processing on risk identification data on the POI data to obtain a risk identification processing result;
and performing online decision processing on the POI data according to the risk identification processing result.
2. The method of claim 1, wherein the risk identification data comprises at least one of:
risk keyword data;
risk coordinate data;
risk picture data;
risk user data; and
risk POI data.
3. The method according to claim 1, wherein the performing an online decision-making process on the POI data according to the risk identification processing result comprises:
if the risk identification processing result indicates that no risk exists, performing online processing on the POI data;
and if the risk identification processing result indicates that a risk exists, the POI data is not executed with online processing.
4. The method according to any one of claims 1 to 3, wherein the performing online decision processing on the POI data according to the risk identification processing result further comprises:
and if the risk identification processing result indicates that a risk exists, executing the POI data discarding processing.
5. An apparatus for processing POI data, comprising:
the system comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring POI data of POI submitted by a user;
the identification unit is used for carrying out risk identification processing on the POI data according to historical behavior data of the user and a pre-established risk database so as to obtain a risk identification processing result;
and the decision unit is used for performing online decision processing on the POI data according to the risk identification processing result.
6. The apparatus of claim 5, wherein the risk identification data comprises at least one of:
risk keyword data;
risk coordinate data;
risk picture data;
risk user data; and
risk POI data.
7. Device according to claim 5, wherein the decision unit is specifically configured to
If the risk identification processing result indicates that no risk exists, performing online processing on the POI data;
and if the risk identification processing result indicates that a risk exists, the POI data is not executed with online processing.
8. The apparatus according to any of claims 5 to 7, wherein the decision unit is further configured to determine whether the apparatus is suitable for use in a mobile communication system
And if the risk identification processing result indicates that a risk exists, executing the POI data discarding processing.
9. An apparatus, characterized in that the apparatus comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-4.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1 to 4.
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| CN201711456176.8A CN108280139B (en) | 2017-12-28 | 2017-12-28 | POI data processing method, device, equipment and computer readable storage medium |
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| CN201711456176.8A CN108280139B (en) | 2017-12-28 | 2017-12-28 | POI data processing method, device, equipment and computer readable storage medium |
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| CN108280139A CN108280139A (en) | 2018-07-13 |
| CN108280139B true CN108280139B (en) | 2022-01-28 |
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| CN103220288A (en) * | 2013-04-12 | 2013-07-24 | 苏州通付盾信息技术有限公司 | Safe-operation method of social platform |
| CN104036037A (en) * | 2014-06-30 | 2014-09-10 | 小米科技有限责任公司 | Method and device for processing junk user |
| CN104123328A (en) * | 2013-04-28 | 2014-10-29 | 北京千橡网景科技发展有限公司 | Method and device used for inhibiting spam comments in website |
| CN104866542A (en) * | 2015-05-05 | 2015-08-26 | 腾讯科技（深圳）有限公司 | POI data verification method and device |
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| CN103220288A (en) * | 2013-04-12 | 2013-07-24 | 苏州通付盾信息技术有限公司 | Safe-operation method of social platform |
| CN104123328A (en) * | 2013-04-28 | 2014-10-29 | 北京千橡网景科技发展有限公司 | Method and device used for inhibiting spam comments in website |
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