CN112163088A - Method, system and equipment for mining short message user information of telecommunication network based on DenseNet - Google Patents
Method, system and equipment for mining short message user information of telecommunication network based on DenseNet Download PDFInfo
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- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- G06F40/279—Recognition of textual entities
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- H04W8/183—Processing at user equipment or user record carrier
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Abstract
The invention belongs to the technical field of telecommunication safety protection, in particular to a method, a system and equipment for mining short message user information of a telecommunication network based on DenseNet, comprising the following steps: constructing a short message database for storing the collected short message platform attribute data and short message text data; aiming at the attribute data of the short message platform, learning and training by using a DenseNet network model to obtain a classification model; and aiming at the short message text data, extracting element entities, combining the short message platform classification result of the classification model, confirming the relationship between the entity elements and the user, and acquiring image data for portrait of the user. The invention accurately extracts and analyzes the required information from a large amount of short message texts and carries out structurization, and draws the attribute portrait of the short message user; by means of the user portrait, the method has important significance for application scenes such as important user discovery, harassment short message prevention and the like, and has good application prospect.
Description
Technical Field
The invention belongs to the technical field of telecommunication safety protection, and particularly relates to a telecommunication network short message user information mining method, system and device based on DenseNet, which are applicable to key user discovery, harassment short message prevention and the like in a telecommunication network.
Background
With the rapid development of communication technology, smart phones have been integrated into our daily life and work, and communication modes represented by short message service have been widely used due to the characteristics of low price, simple operation, convenient use and the like. Currently, short message service has been integrated into people's life and work, where there is a lot of information. With the increasing demand of data analysis in telecommunication networks, personalized analysis and intelligent processing for short messages are gradually promoted. However, some lawbreakers also use short messages to carry out illegal acts such as advertising harassment and financial fraud, which causes certain damage to the stable development of the society. Therefore, it is necessary to take the necessary measures to minimize the adverse effect of spam messages on users and unnecessary economic loss.
Disclosure of Invention
Therefore, the invention provides a method, a system and equipment for mining short message user information of a telecommunication network based on DenseNet, which can draw a user portrait with practical value by integrating the mined fragment information and has important significance for application scenes such as important user discovery, short message disturbance prevention and the like.
According to the design scheme provided by the invention, the method for mining the short message user information of the telecommunication network based on the DenseNet comprises the following contents:
constructing a short message database for storing the collected short message platform attribute data and short message text data;
aiming at the attribute data of the short message platform, learning and training by using a DenseNet network model to obtain a classification model;
and aiming at the short message text data, extracting element entities, combining the short message platform classification result of the classification model, confirming the relationship between the entity elements and the user, and acquiring image data for portrait of the user.
The invention relates to a method for mining short message user information of a telecommunication network based on DenseNet, which further obtains short message text data by utilizing short message data flow between telecommunication terminals in the telecommunication network.
As the method for mining the short message user information of the telecommunication network based on the DenseNet, further, the extracted element entities include but are not limited to: name, age, birthday, job title, identification number, mobile phone number, address, unit, license plate number, credit degree, mobile phone model, consumption grade, hobby, trip information and application program sending platform.
As the method for mining the short message user information of the telecommunication network based on the DenseNet, further, various element entities in the short message text data are extracted by a word segmentation tool and/or a keyword matching and/or a regular expression intercepting method.
As the invention discloses a DenseNet-based short message user information mining method, further, aiming at short message text data, firstly reading a short message data source, reading information elements in an original short message text, and then extracting element entities for acquiring user portrait image data according to the information elements.
The DenseNet network model comprises a convolution layer, a pooling layer, a full-link layer and a classification layer which are connected in sequence and is used for acquiring the classification model through training and learning so as to predict the type of the short message platform according to the attribute data of the short message platform.
The method for mining the short message user information of the telecommunication network based on the DenseNet further comprises the steps of taking the type of a short message platform as a reference basis of the relation between a user and an entity aiming at the extracted element entity, and calibrating user image data by combining the classification result of the short message platform and the element entity so as to draw a user portrait corresponding to a short message text.
Further, the invention also provides a system for mining the short message user information of the telecommunication network based on the DenseNet, which comprises the following contents: a collection module, a learning module, and a calibration module, wherein,
the collection module is used for constructing a short message database and storing the collected short message platform attribute data and short message text data;
the learning module is used for performing learning training by using a DenseNet network model aiming at the attribute data of the short message platform to obtain a classification model;
and the calibration module is used for extracting element entities aiming at the short message text data, combining the short message platform classification results of the classification model, confirming the relationship between the entity elements and the user and acquiring image data used for user portrait.
Further, the present invention also provides a device for mining short message user information in a telecommunication network based on DenseNet, which is arranged between terminals in the telecommunication network for obtaining short message text data through short message data stream, and comprises: a collection module, a learning module, and a matching module, wherein,
the collection module is used for constructing a short message database and storing the collected short message platform attribute data and short message text data;
the learning module is used for performing learning training by using a DenseNet network model aiming at the attribute data of the short message platform to obtain a classification model;
and the calibration module is used for extracting element entities aiming at the short message text data, combining the short message platform classification results of the classification model, confirming the relationship between the entity elements and the user and acquiring image data used for user portrait.
The invention has the beneficial effects that:
the invention accurately extracts and analyzes the required information from a large amount of short message texts and carries out structurization, and draws the attribute portrait of the short message user; by means of the user portrait, the method has important significance for application scenes such as important user discovery, harassment short message prevention and the like, and has good application prospect.
Description of the drawings:
FIG. 1 is a schematic diagram of a short message user information mining process of a telecommunication network based on DenseNet in an embodiment;
FIG. 2 is an information representation of an embodiment;
FIG. 3 is a schematic diagram of short message text message element analysis in the embodiment;
FIG. 4 is a schematic diagram of short message text element entity extraction in the embodiment;
fig. 5 is a schematic structure of the network model in the embodiment.
The specific implementation mode is as follows:
in order to make the objects, technical solutions and advantages of the present invention clearer and more obvious, the present invention is further described in detail below with reference to the accompanying drawings and technical solutions.
The embodiment of the invention, as shown in fig. 1, provides a method for mining short message user information of a telecommunication network based on DenseNet, which comprises the following contents:
s101, constructing a short message database for storing collected short message platform attribute data and short message text data;
s102, aiming at the attribute data of the short message platform, learning and training by using a DenseNet network model to obtain a classification model;
s103, aiming at the short message text data, extracting element entities, combining the short message platform classification result of the classification model, confirming the relationship between the entity elements and the user, and acquiring image data for portrait of the user.
By integrating the excavated fragment information, the user portrait with practical value can be drawn, and the method has important significance for application scenes such as discovery of important users and prevention of harassment short messages.
As the method for mining the short message user information of the telecommunication network based on the DenseNet in the embodiment of the present invention, further, the extracted element entities include but are not limited to: name, age, birthday, job title, identification number, mobile phone number, address, unit, license plate number, credit degree, mobile phone model, consumption grade, hobby, trip information and application program sending platform. Further, aiming at the short message text data, firstly reading a short message data source, reading information elements in the original short message text, and then extracting element entities for acquiring the portrait image data of the user according to the information elements.
Referring to fig. 2 and 3, firstly writing short message text data from a short message database into a blocking queue 1, then performing entity analysis and extraction on the short message text in the blocking queue 1, writing an extracted result into a blocking queue 2, wherein a specific entity extraction process is shown in fig. 4, and finally writing the result in the blocking queue 2 into a JSON file. And finally, drawing the information portrait of the short message user according to the analysis result stored in the JSON file.
As the method for mining the short message user information of the telecommunication network based on the DenseNet in the embodiment of the invention, further, each element entity in the short message text data is extracted by a word segmentation tool and/or a keyword matching and/or a regular expression intercepting method. Furthermore, the DenseNet model comprises a convolution layer, a pooling layer, a full-link layer and a classification layer which are connected in sequence, and is used for obtaining the classification model through training and learning so as to predict the type of the short message platform according to the attribute data of the short message platform.
The entity analysis and extraction embodiment of the short message text is shown in table 1, the short message platform classification is shown in table 2, and the network model parameters are shown in table 3.
Table 1 information element extraction method
TABLE 2 short message platform Classification
TABLE 3 DenseNet model parameters
The user real-time portrait is realized by the short message platform classification model DenseNet training and combining the model training classification result and the short message text element entity, wherein the DenseNet training can be firstly independently carried out, and can also be continuously optimized by combining the result feedback obtained by the user portrait.
As the DenseNet-based method for mining the short message user information of the telecommunication network, the extracted element entities are further calibrated by using the short message platform type as a reference basis of the relationship between the user and the entity and combining the short message platform classification result and the element entities to draw the user portrait corresponding to the short message text.
For a single short message, reading a short message data source through a thread 1, and writing an original short message text into a blocking queue 1; reading an original short message text from the blocking queue 1 through the thread 2, and performing analysis and extraction operations (the analysis and extraction method of each element entity can adopt the content exemplified in the table 1); meanwhile, the name of the short message sending platform is sent into the trained DenseNet classification model to obtain the type of the short message platform. Encapsulating the entity data result into a Java class and writing the Java class into a blocking queue 2; writing the analyzed entity data result into a JSON file from the blocking queue 2 through a thread 3; the called number is used as the center (the number is desensitized), and short message elements in a time range are incrementally converged. Particularly, the platform name type is used as a main reference of the relation between the called number and the entity for each element, and joint judgment is carried out according to other keywords in the short message. And drawing the user portrait corresponding to the short message text according to the analysis result of the entity information elements after the relationship is calibrated.
In the embodiment of the invention, aiming at the short message text of the telecommunication network, the user portrait with practical value can be drawn by integrating the excavated fragment information; by means of the user portrait, the application in scenes such as key user discovery, harassment short message prevention and the like is realized, and the method has a better application prospect.
Further, based on the above method, an embodiment of the present invention further provides a system for mining short message user information in a telecommunication network based on DenseNet, including the following contents: a collection module, a learning module, and a calibration module, wherein,
the collection module is used for constructing a short message database and storing the collected short message platform attribute data and short message text data;
the learning module is used for performing learning training by using a DenseNet network model aiming at the attribute data of the short message platform to obtain a classification model;
and the calibration module is used for extracting element entities aiming at the short message text data, combining the short message platform classification results of the classification model, confirming the relationship between the entity elements and the user and acquiring image data used for user portrait.
Further, based on the above method, an embodiment of the present invention further provides a device for mining short message user information in a telecommunication network based on DenseNet, which is arranged between terminals in the telecommunication network and used for acquiring short message text data through a short message data stream, and includes: a collection module, a learning module, and a matching module, wherein,
the collection module is used for constructing a short message database and storing the collected short message platform attribute data and short message text data;
the learning module is used for performing learning training by using a DenseNet network model aiming at the attribute data of the short message platform to obtain a classification model;
and the calibration module is used for extracting element entities aiming at the short message text data, combining the short message platform classification results of the classification model, confirming the relationship between the entity elements and the user and acquiring image data used for user portrait.
The equipment is deployed between short message data streams of a telecommunication network, and a large number of element entities in a short message text are analyzed and extracted, so that a real and full figure image can be drawn, and the short message text drawing method has the advantages of high extraction speed, high accuracy, easiness in implementation and the like.
Unless specifically stated otherwise, the relative steps, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of the present invention.
Based on the foregoing system, an embodiment of the present invention further provides a server, including: one or more processors; a storage device to store one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the system as described above.
Based on the above system, the embodiment of the present invention further provides a computer readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the above system.
The device provided by the embodiment of the present invention has the same implementation principle and technical effect as the system embodiment, and for the sake of brief description, reference may be made to the corresponding content in the system embodiment for the part where the device embodiment is not mentioned.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing system embodiments, and are not described herein again.
In all examples shown and described herein, any particular value should be construed as merely exemplary, and not as a limitation, and thus other examples of example embodiments may have different values.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus, and system may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
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 functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the system according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for mining short message user information of a telecommunication network based on DenseNet is characterized by comprising the following contents:
constructing a short message database for storing the collected short message platform attribute data and short message text data;
aiming at the attribute data of the short message platform, learning and training by using a DenseNet network model to obtain a classification model;
and aiming at the short message text data, extracting element entities, combining the short message platform classification result of the classification model, confirming the relationship between the entity elements and the user, and acquiring image data for portrait of the user.
2. The DenseNet-based short message user information mining method of telecommunication network as claimed in claim 1, wherein the short message text data is obtained by using short message data flow between telecommunication terminals in the telecommunication network.
3. The DenseNet-based short message user information mining method of telecommunication network as claimed in claim 1, wherein the extracted element entities include but are not limited to: name, age, birthday, job title, identification number, mobile phone number, address, unit, license plate number, credit degree, mobile phone model, consumption grade, hobby, trip information and application program sending platform.
4. The DenseNet-based short message user information mining method for telecommunication network according to claim 1 or 3, characterized in that each element entity in the short message text data is extracted by a word segmentation tool and/or a keyword matching and/or a regular expression interception method.
5. The DenseNet-based short message user information mining method of telecommunication network as claimed in claim 1, wherein for the short message text data, first reading the short message data source, reading the information elements in the original short message text, and then extracting the element entities for obtaining the user portrait image data according to the information elements.
6. The Densenet-based method for mining short message user information in telecommunication network according to claim 1, wherein the Densenet network model comprises a convolutional layer, a pooling layer, a full-link layer and a classification layer which are connected in sequence, and is used for obtaining a classification model through training and learning so as to predict the type of the short message platform according to the attribute data of the short message platform.
7. The DenseNet-based short message user information mining method as claimed in claim 1, wherein for the extracted element entities, the short message platform type is used as a reference basis for the relationship between the user and the entity, and the short message platform classification result and the element entities are combined to calibrate user image data so as to draw a user portrait corresponding to the short message text.
8. A telecommunication network short message user information mining system based on DenseNet is characterized by comprising the following contents: a collection module, a learning module, and a calibration module, wherein,
the collection module is used for constructing a short message database and storing the collected short message platform attribute data and short message text data;
the learning module is used for performing learning training by using a DenseNet network model aiming at the attribute data of the short message platform to obtain a classification model;
and the calibration module is used for extracting element entities aiming at the short message text data, combining the short message platform classification results of the classification model, confirming the relationship between the entity elements and the user and acquiring image data used for user portrait.
9. A telecommunication network short message user information mining device based on DenseNet is characterized in that the mining device is arranged between telecommunication network terminals and used for acquiring short message text data through short message data flow, and the mining device comprises: the short message learning system comprises a collection module, a learning module and a matching module, wherein the collection module is used for constructing a short message database and storing collected short message platform attribute data and short message text data;
the learning module is used for performing learning training by using a DenseNet network model aiming at the attribute data of the short message platform to obtain a classification model;
and the calibration module is used for extracting element entities aiming at the short message text data, combining the short message platform classification results of the classification model, confirming the relationship between the entity elements and the user and acquiring image data used for user portrait.
10. A computer readable medium, on which a computer program is stored, wherein the program, when executed by a processor, performs the steps of the method for mining information of a user of a DenseNet-based short message service in a telecommunication network according to any one of claims 1 to 7.
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