CN116992267B - Regional population gender identification method and system based on signaling data - Google Patents
Regional population gender identification method and system based on signaling data Download PDFInfo
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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Abstract
The invention discloses a regional population sex identification method and a system based on signaling data, wherein the method comprises the following steps: acquiring mobile phone signaling data information of a preset area based on a preset first time period; dividing the mobile phone signaling data to obtain local mobile phone signaling data and remote mobile phone signaling data; inquiring in a preset local database according to the local mobile phone signaling data to obtain the gender of the user corresponding to the local mobile phone signaling data; extracting characteristic values in the signaling data of the mobile phones in different places, and sending the characteristic values to a preset population gender identification model to obtain the gender of the user corresponding to the signaling data of the mobile phones in different places; and combining and counting the local mobile phone signaling data corresponding user and the remote mobile phone signaling data corresponding user according to the same gender. According to the invention, the supervised learning algorithm is used for identifying and counting the gender of the population in the region based on the signaling data, so that the method is more accurate than the estimation according to the population equal proportion of the known gender, and the signaling data is convenient to acquire.
Description
Technical Field
The invention relates to the field of space-time big data processing, in particular to a regional population sex identification method and system based on signaling data.
Background
The existing regional population sex identification and statistics technology is characterized in that the traditional method is that population census mode is adopted to conduct manual investigation and statistics, and the new technology is adopted to conduct identification and statistics through technologies such as face recognition and the like. Traditional census methods are most accurate, but are time-consuming and labor-consuming, and cannot identify and count different gender populations in the current area due to population flow. The novel technology uses the face recognition technology to carry out sex identification statistics on population by collecting face information through the monitoring equipment, is accurate, can identify and count the population with different sexes in the current area, but can not comprehensively identify and count the population with different sexes in the whole area because the monitoring equipment can not cover the whole area (such as a certain urban area).
Accordingly, there is a need for improvement in the art.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a method and a system for identifying regional population gender based on signaling data, which can more conveniently count population with different sexes in a whole region.
The first aspect of the present invention provides a method for identifying regional population gender based on signaling data, comprising:
acquiring mobile phone signaling data information of a preset area based on a preset first time period;
dividing the mobile phone signaling data to obtain local mobile phone signaling data and remote mobile phone signaling data;
Inquiring in a preset local database according to the local mobile phone signaling data to obtain the gender of the user corresponding to the local mobile phone signaling data;
extracting characteristic values in the signaling data of the mobile phones in different places, and sending the characteristic values to a preset population gender identification model to obtain the gender of the user corresponding to the signaling data of the mobile phones in different places;
and combining and counting the local mobile phone signaling data corresponding user and the remote mobile phone signaling data corresponding user according to the same gender.
In this scheme, still include:
obtaining mobile track information of a user corresponding to the mobile phone signaling data according to the mobile phone signaling data;
extracting resident point information in the movement track information of the corresponding user;
obtaining a characteristic value in corresponding mobile phone signaling data according to resident point information in the movement track information of the corresponding user;
the characteristic values in the mobile phone signaling data comprise characteristic values in local mobile phone signaling data and characteristic values in remote mobile phone signaling data.
In this scheme, still include:
extracting a characteristic value in local mobile phone signaling data;
performing feature processing on the feature values in the local mobile phone signaling data to obtain a space-time behavior feature rule of a user corresponding to the local mobile phone signaling data;
The method comprises the steps of sorting space-time behavior characteristic rules of users corresponding to local mobile phone signaling data and sexes of users corresponding to the local mobile phone signaling data, and dividing the space-time behavior characteristic rules and sexes into training samples and verification samples;
the training samples are sent to a preset initialization model for training, and the preset initialization model after training is obtained;
transmitting the verification sample to a preset initialization model after training to obtain gender prediction accuracy;
and when the gender prediction accuracy is greater than a preset accuracy threshold, stopping training by the preset initialization model to obtain a preset population gender identification model.
In this scheme, the step of extracting the characteristic value in the remote mobile phone signaling data and sending the characteristic value to a preset population gender identification model to obtain the gender of the user corresponding to the remote mobile phone signaling data specifically includes:
comparing and analyzing the characteristic value in the signaling data of the remote mobile phone with a corresponding preset characteristic threshold value, judging whether the characteristic value in the signaling data of the remote mobile phone is larger than the corresponding preset characteristic threshold value, and if so, setting the characteristic value in the signaling data of the remote mobile phone as a main characteristic value; if not, setting the characteristic value in the corresponding remote mobile phone signaling data as a secondary characteristic value;
The main characteristic value is preferentially sent to a preset population gender identification model, and if the gender of the user corresponding to the signaling data of the mobile phone in different places is determined, the secondary characteristic value does not need to be sent to the preset population gender identification model; if the gender of the user corresponding to the remote mobile phone signaling data is not determined, the secondary characteristic value is sent to a preset population gender identification model to judge the gender of the user corresponding to the remote mobile phone signaling data again.
In this solution, after the main feature value is preferentially sent to the preset population sex identification model, the method specifically includes:
preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
comparing and calculating the difference value between the first male index and the first female index to obtain a first sex index difference value;
if the absolute value of the first sex index difference value is larger than a preset sex index difference threshold value, the sex with the large sex index is set as the sex corresponding to the user of the remote mobile phone signaling data;
if the absolute value of the first sex index difference value is not greater than the preset sex index difference threshold value, the sex of the user corresponding to the remote mobile phone signaling data is not determined.
In this solution, the step of sending the secondary feature value to a preset population gender identification model to determine the gender of the user corresponding to the remote mobile phone signaling data again specifically includes:
preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
transmitting the secondary characteristic value to a preset population sex identification model to obtain a second male index and a second female index;
accumulating the first male index and the second male index to obtain male index;
accumulating the first female index and the second female index to obtain female indexes;
comparing and analyzing the male index and the female index, and setting the gender of the user corresponding to the remote mobile phone signaling data as male if the male index is larger than the female index;
if the male index is smaller than the female index, the gender of the user corresponding to the remote mobile phone signaling data is set as female;
and if the male index is equal to the female index, judging through the maximum characteristic value in the signaling data of the remote mobile phone.
In this solution, if the male index is equal to the female index, the step of determining by the maximum eigenvalue in the signaling data of the mobile phone in different places specifically includes:
Arranging the characteristic values in the signaling data of the remote mobile phone in order from small to large to obtain a first large characteristic value in the signaling data of the remote mobile phone;
transmitting a first large characteristic value in the signaling data of the remote mobile phone to a preset population sex identification model to obtain a third male index and a third female index;
comparing and analyzing the third male index and the third female index, and setting the gender with the large gender index as the gender of the user corresponding to the remote mobile phone signaling data;
and if the third male index and the third female index are equal, extracting a second large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and if the gender index corresponding to the second large characteristic value in the remote mobile phone signaling data is the same, continuously extracting a third large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and the like until the gender of the user corresponding to the remote mobile phone signaling data is distinguished.
The second aspect of the present invention provides a regional population sex identification system based on signaling data, comprising a memory and a processor, wherein the memory stores a regional population sex identification method program based on signaling data, and the regional population sex identification method program based on signaling data realizes the following steps when executed by the processor:
Acquiring mobile phone signaling data information of a preset area based on a preset first time period;
dividing the mobile phone signaling data to obtain local mobile phone signaling data and remote mobile phone signaling data;
inquiring in a preset local database according to the local mobile phone signaling data to obtain the gender of the user corresponding to the local mobile phone signaling data;
extracting characteristic values in the signaling data of the mobile phones in different places, and sending the characteristic values to a preset population gender identification model to obtain the gender of the user corresponding to the signaling data of the mobile phones in different places;
and combining and counting the local mobile phone signaling data corresponding user and the remote mobile phone signaling data corresponding user according to the same gender.
In this scheme, still include:
obtaining mobile track information of a user corresponding to the mobile phone signaling data according to the mobile phone signaling data;
extracting resident point information in the movement track information of the corresponding user;
obtaining a characteristic value in corresponding mobile phone signaling data according to resident point information in the movement track information of the corresponding user;
the characteristic values in the mobile phone signaling data comprise characteristic values in local mobile phone signaling data and characteristic values in remote mobile phone signaling data.
In this scheme, still include:
Extracting a characteristic value in local mobile phone signaling data;
performing feature processing on the feature values in the local mobile phone signaling data to obtain a space-time behavior feature rule of a user corresponding to the local mobile phone signaling data;
the method comprises the steps of sorting space-time behavior characteristic rules of users corresponding to local mobile phone signaling data and sexes of users corresponding to the local mobile phone signaling data, and dividing the space-time behavior characteristic rules and sexes into training samples and verification samples;
the training samples are sent to a preset initialization model for training, and the preset initialization model after training is obtained;
transmitting the verification sample to a preset initialization model after training to obtain gender prediction accuracy;
and when the gender prediction accuracy is greater than a preset accuracy threshold, stopping training by the preset initialization model to obtain a preset population gender identification model.
In this scheme, the step of extracting the characteristic value in the remote mobile phone signaling data and sending the characteristic value to a preset population gender identification model to obtain the gender of the user corresponding to the remote mobile phone signaling data specifically includes:
comparing and analyzing the characteristic value in the signaling data of the remote mobile phone with a corresponding preset characteristic threshold value, judging whether the characteristic value in the signaling data of the remote mobile phone is larger than the corresponding preset characteristic threshold value, and if so, setting the characteristic value in the signaling data of the remote mobile phone as a main characteristic value; if not, setting the characteristic value in the corresponding remote mobile phone signaling data as a secondary characteristic value;
The main characteristic value is preferentially sent to a preset population gender identification model, and if the gender of the user corresponding to the signaling data of the mobile phone in different places is determined, the secondary characteristic value does not need to be sent to the preset population gender identification model; if the gender of the user corresponding to the remote mobile phone signaling data is not determined, the secondary characteristic value is sent to a preset population gender identification model to judge the gender of the user corresponding to the remote mobile phone signaling data again.
In this solution, after the main feature value is preferentially sent to the preset population sex identification model, the method specifically includes:
preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
comparing and calculating the difference value between the first male index and the first female index to obtain a first sex index difference value;
if the absolute value of the first sex index difference value is larger than a preset sex index difference threshold value, the sex with the large sex index is set as the sex corresponding to the user of the remote mobile phone signaling data;
if the absolute value of the first sex index difference value is not greater than the preset sex index difference threshold value, the sex of the user corresponding to the remote mobile phone signaling data is not determined.
In this solution, the step of sending the secondary feature value to a preset population gender identification model to determine the gender of the user corresponding to the remote mobile phone signaling data again specifically includes:
preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
transmitting the secondary characteristic value to a preset population sex identification model to obtain a second male index and a second female index;
accumulating the first male index and the second male index to obtain male index;
accumulating the first female index and the second female index to obtain female indexes;
comparing and analyzing the male index and the female index, and setting the gender of the user corresponding to the remote mobile phone signaling data as male if the male index is larger than the female index;
if the male index is smaller than the female index, the gender of the user corresponding to the remote mobile phone signaling data is set as female;
and if the male index is equal to the female index, judging through the maximum characteristic value in the signaling data of the remote mobile phone.
In this solution, if the male index is equal to the female index, the step of determining by the maximum eigenvalue in the signaling data of the mobile phone in different places specifically includes:
Arranging the characteristic values in the signaling data of the remote mobile phone in order from small to large to obtain a first large characteristic value in the signaling data of the remote mobile phone;
transmitting a first large characteristic value in the signaling data of the remote mobile phone to a preset population sex identification model to obtain a third male index and a third female index;
comparing and analyzing the third male index and the third female index, and setting the gender with the large gender index as the gender of the user corresponding to the remote mobile phone signaling data;
and if the third male index and the third female index are equal, extracting a second large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and if the gender index corresponding to the second large characteristic value in the remote mobile phone signaling data is the same, continuously extracting a third large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and the like until the gender of the user corresponding to the remote mobile phone signaling data is distinguished.
According to the regional population gender identification method and system based on the signaling data, the regional population gender is identified and counted by using the supervised learning algorithm based on the signaling data, and the regional population gender identification method and system are more accurate than the regional population gender identification method and system based on the signaling data, and the signaling data is convenient to acquire.
Drawings
FIG. 1 is a flow chart of a regional population gender identification method based on signaling data according to the present invention;
fig. 2 shows a block diagram of a regional population sex identification system based on signaling data according to the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
Fig. 1 shows a flow chart of a regional population sex identification method based on signaling data according to the present invention.
As shown in fig. 1, the invention discloses a regional population sex identification method based on signaling data, which comprises the following steps:
s101, acquiring mobile phone signaling data information of a preset area based on a preset first time period;
S102, dividing the mobile phone signaling data to obtain local mobile phone signaling data and remote mobile phone signaling data;
s103, inquiring in a preset local database according to the local mobile phone signaling data to obtain the gender of the user corresponding to the local mobile phone signaling data;
s104, extracting characteristic values in the remote mobile phone signaling data, and sending the characteristic values to a preset population gender identification model to obtain the gender of the user corresponding to the remote mobile phone signaling data;
s105, combining and counting the local mobile phone signaling data corresponding user and the remote mobile phone signaling data corresponding user according to the same gender.
According to the embodiment of the invention, all base stations in the preset area are selected according to the boundary box of the preset area, the signaling track under the selected base stations is extracted, only part of the signaling track is cleaned, for example, the preset first time period is one day, the signaling track which does not meet one day is cleaned, the mobile phone signaling data information of the preset area is obtained, then the mobile phone signaling data is classified to obtain the local mobile phone signaling data and the remote mobile phone signaling data, the local mobile phone signaling data is the signaling data of the preset area belonging to the mobile phone number, the remote mobile phone signaling data is the signaling data of the preset area not belonging to the mobile phone number, and the local mobile phone signaling data is recorded in the preset local database, so that the registration information of the corresponding local mobile phone signaling data when the corresponding user purchases the mobile phone number can be determined, and the gender of the corresponding user of the corresponding local mobile phone signaling data can be queried through the preset local database; and carrying out evaluation and prediction on the remote mobile phone signaling data through a preset population gender identification model to obtain the gender of the user corresponding to the remote mobile phone signaling data.
According to an embodiment of the present invention, further comprising:
obtaining mobile track information of a user corresponding to the mobile phone signaling data according to the mobile phone signaling data;
extracting resident point information in the movement track information of the corresponding user;
obtaining a characteristic value in corresponding mobile phone signaling data according to resident point information in the movement track information of the corresponding user;
the characteristic values in the mobile phone signaling data comprise characteristic values in local mobile phone signaling data and characteristic values in remote mobile phone signaling data.
It should be noted that, the mobile track information of the corresponding user of the mobile phone signaling data includes the mobile track distribution, the residence place, the travel OD (origin destination) place, the residence time period and duration, the workresidence place and other aspects, and the feature value in the corresponding mobile phone signaling data is obtained by combining the dimensions of day/night, workday/holiday and the like.
According to an embodiment of the present invention, further comprising:
extracting a characteristic value in local mobile phone signaling data;
performing feature processing on the feature values in the local mobile phone signaling data to obtain a space-time behavior feature rule of a user corresponding to the local mobile phone signaling data;
the method comprises the steps of sorting space-time behavior characteristic rules of users corresponding to local mobile phone signaling data and sexes of users corresponding to the local mobile phone signaling data, and dividing the space-time behavior characteristic rules and sexes into training samples and verification samples;
The training samples are sent to a preset initialization model for training, and the preset initialization model after training is obtained;
transmitting the verification sample to a preset initialization model after training to obtain gender prediction accuracy;
and when the gender prediction accuracy is greater than a preset accuracy threshold, stopping training by the preset initialization model to obtain a preset population gender identification model.
It should be noted that, the feature processing includes feature preprocessing, feature single/multi-variable analysis, feature elimination and other feature engineering, the space-time behavior feature rule of different people mouth users is mined through a supervised learning classification recognition algorithm, the preset initialization model is a neural network model, for example, the preset accuracy threshold is 95%, when the verification sample is sent to the trained preset initialization model, and when the obtained gender prediction accuracy is greater than 95%, the training of the preset initialization model is stopped, and the trained preset initialization model is set as the preset population gender recognition model.
According to the embodiment of the invention, the step of extracting the characteristic value in the remote mobile phone signaling data and sending the characteristic value to a preset population gender identification model to obtain the gender of the user corresponding to the remote mobile phone signaling data specifically comprises the following steps:
Comparing and analyzing the characteristic value in the signaling data of the remote mobile phone with a corresponding preset characteristic threshold value, judging whether the characteristic value in the signaling data of the remote mobile phone is larger than the corresponding preset characteristic threshold value, and if so, setting the characteristic value in the signaling data of the remote mobile phone as a main characteristic value; if not, setting the characteristic value in the corresponding remote mobile phone signaling data as a secondary characteristic value;
the main characteristic value is preferentially sent to a preset population gender identification model, and if the gender of the user corresponding to the signaling data of the mobile phone in different places is determined, the secondary characteristic value does not need to be sent to the preset population gender identification model; if the gender of the user corresponding to the remote mobile phone signaling data is not determined, the secondary characteristic value is sent to a preset population gender identification model to judge the gender of the user corresponding to the remote mobile phone signaling data again.
It should be noted that, the feature values in the corresponding remote mobile phone signaling data are divided into a main feature value and a secondary feature value, where if the main feature value can determine the gender of the corresponding user of the remote mobile phone signaling data, the secondary feature value does not need to be sent to the preset population gender identification model to save the calculation time.
According to an embodiment of the present invention, after the main feature value is preferentially sent to the preset population sex identification model, the method specifically includes:
Preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
comparing and calculating the difference value between the first male index and the first female index to obtain a first sex index difference value;
if the absolute value of the first sex index difference value is larger than a preset sex index difference threshold value, the sex with the large sex index is set as the sex corresponding to the user of the remote mobile phone signaling data;
if the absolute value of the first sex index difference value is not greater than the preset sex index difference threshold value, the sex of the user corresponding to the remote mobile phone signaling data is not determined.
It should be noted that, the gender of the user corresponding to the remote mobile phone signaling data is judged by the absolute value of the first gender index difference value, for example, the first gender index difference value is equal to the first male index minus the first female index, when the first gender index difference value is greater than the preset gender index difference threshold value, the gender of the user corresponding to the remote mobile phone signaling data is male, when the first gender difference value is negative and the absolute value of the corresponding first gender difference value is greater than the preset gender index difference threshold value, the gender of the user corresponding to the remote mobile phone signaling data is female, otherwise, the remote mobile phone signaling data needs to be judged by the secondary features.
According to an embodiment of the present invention, the step of sending the secondary feature value to a preset population gender identification model to determine the gender of the user corresponding to the signaling data of the remote mobile phone again specifically includes:
preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
transmitting the secondary characteristic value to a preset population sex identification model to obtain a second male index and a second female index;
accumulating the first male index and the second male index to obtain male index;
accumulating the first female index and the second female index to obtain female indexes;
comparing and analyzing the male index and the female index, and setting the gender of the user corresponding to the remote mobile phone signaling data as male if the male index is larger than the female index;
if the male index is smaller than the female index, the gender of the user corresponding to the remote mobile phone signaling data is set as female;
and if the male index is equal to the female index, judging through the maximum characteristic value in the signaling data of the remote mobile phone.
When the gender index corresponding to the main characteristic cannot judge the gender of the user corresponding to the remote mobile phone signaling data, the secondary characteristic is sent to a preset population gender identification model to obtain a second male index and a second female index, and if the male index is larger than the female index, the gender of the user corresponding to the remote mobile phone signaling data is set as a male; if the male index is smaller than the female index, the sex of the user corresponding to the remote mobile phone signaling data is set as female, otherwise, the judgment is carried out again according to the maximum characteristic value in the remote mobile phone signaling data.
According to the embodiment of the invention, if the male index is equal to the female index, the step of determining by the maximum eigenvalue in the signaling data of the mobile phone in different places specifically includes:
arranging the characteristic values in the signaling data of the remote mobile phone in order from small to large to obtain a first large characteristic value in the signaling data of the remote mobile phone;
transmitting a first large characteristic value in the signaling data of the remote mobile phone to a preset population sex identification model to obtain a third male index and a third female index;
comparing and analyzing the third male index and the third female index, and setting the gender with the large gender index as the gender of the user corresponding to the remote mobile phone signaling data;
and if the third male index and the third female index are equal, extracting a second large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and if the gender index corresponding to the second large characteristic value in the remote mobile phone signaling data is the same, continuously extracting a third large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and the like until the gender of the user corresponding to the remote mobile phone signaling data is distinguished.
When the male index is equal to the female sex index, the characteristic values in the remote mobile phone signaling data are arranged in the order from small to large, the first large characteristic value is firstly sent to a preset population sex identification model to obtain a third male index and a third female index, if the third male index is the same as the third female index, the second large characteristic value is continuously extracted for judgment, if the male index and the female index corresponding to the second large characteristic value are the same, the third large characteristic value is extracted for judgment, and the like, and if the male index and the female index are different, the sex with the large sex index is set as the sex of the user corresponding to the remote mobile phone signaling data.
Fig. 2 shows a block diagram of a regional population sex identification system based on signaling data according to the present invention.
As shown in fig. 2, a second aspect of the present invention provides a regional population sex identification system 2 based on signaling data, including a memory 21 and a processor 22, where the memory stores a regional population sex identification method program based on signaling data, and the processor executes the regional population sex identification method program based on signaling data to implement the following steps:
Acquiring mobile phone signaling data information of a preset area based on a preset first time period;
dividing the mobile phone signaling data to obtain local mobile phone signaling data and remote mobile phone signaling data;
inquiring in a preset local database according to the local mobile phone signaling data to obtain the gender of the user corresponding to the local mobile phone signaling data;
extracting characteristic values in the signaling data of the mobile phones in different places, and sending the characteristic values to a preset population gender identification model to obtain the gender of the user corresponding to the signaling data of the mobile phones in different places;
and combining and counting the local mobile phone signaling data corresponding user and the remote mobile phone signaling data corresponding user according to the same gender.
According to the embodiment of the invention, all base stations in the preset area are selected according to the boundary box of the preset area, the signaling track under the selected base stations is extracted, only part of the signaling track is cleaned, for example, the preset first time period is one day, the signaling track which does not meet one day is cleaned, the mobile phone signaling data information of the preset area is obtained, then the mobile phone signaling data is classified to obtain the local mobile phone signaling data and the remote mobile phone signaling data, the local mobile phone signaling data is the signaling data of the preset area belonging to the mobile phone number, the remote mobile phone signaling data is the signaling data of the preset area not belonging to the mobile phone number, and the local mobile phone signaling data is recorded in the preset local database, so that the registration information of the corresponding local mobile phone signaling data when the corresponding user purchases the mobile phone number can be determined, and the gender of the corresponding user of the corresponding local mobile phone signaling data can be queried through the preset local database; and carrying out evaluation and prediction on the remote mobile phone signaling data through a preset population gender identification model to obtain the gender of the user corresponding to the remote mobile phone signaling data.
According to an embodiment of the present invention, further comprising:
obtaining mobile track information of a user corresponding to the mobile phone signaling data according to the mobile phone signaling data;
extracting resident point information in the movement track information of the corresponding user;
obtaining a characteristic value in corresponding mobile phone signaling data according to resident point information in the movement track information of the corresponding user;
the characteristic values in the mobile phone signaling data comprise characteristic values in local mobile phone signaling data and characteristic values in remote mobile phone signaling data.
It should be noted that, the mobile track information of the corresponding user of the mobile phone signaling data includes the mobile track distribution, the residence place, the travel OD (origin destination) place, the residence time period and duration, the workresidence place and other aspects, and the feature value in the corresponding mobile phone signaling data is obtained by combining the dimensions of day/night, workday/holiday and the like.
According to an embodiment of the present invention, further comprising:
extracting a characteristic value in local mobile phone signaling data;
performing feature processing on the feature values in the local mobile phone signaling data to obtain a space-time behavior feature rule of a user corresponding to the local mobile phone signaling data;
the method comprises the steps of sorting space-time behavior characteristic rules of users corresponding to local mobile phone signaling data and sexes of users corresponding to the local mobile phone signaling data, and dividing the space-time behavior characteristic rules and sexes into training samples and verification samples;
The training samples are sent to a preset initialization model for training, and the preset initialization model after training is obtained;
transmitting the verification sample to a preset initialization model after training to obtain gender prediction accuracy;
and when the gender prediction accuracy is greater than a preset accuracy threshold, stopping training by the preset initialization model to obtain a preset population gender identification model.
It should be noted that, the feature processing includes feature preprocessing, feature single/multi-variable analysis, feature elimination and other feature engineering, the space-time behavior feature rule of different people mouth users is mined through a supervised learning classification recognition algorithm, the preset initialization model is a neural network model, for example, the preset accuracy threshold is 95%, when the verification sample is sent to the trained preset initialization model, and when the obtained gender prediction accuracy is greater than 95%, the training of the preset initialization model is stopped, and the trained preset initialization model is set as the preset population gender recognition model.
According to the embodiment of the invention, the step of extracting the characteristic value in the remote mobile phone signaling data and sending the characteristic value to a preset population gender identification model to obtain the gender of the user corresponding to the remote mobile phone signaling data specifically comprises the following steps:
Comparing and analyzing the characteristic value in the signaling data of the remote mobile phone with a corresponding preset characteristic threshold value, judging whether the characteristic value in the signaling data of the remote mobile phone is larger than the corresponding preset characteristic threshold value, and if so, setting the characteristic value in the signaling data of the remote mobile phone as a main characteristic value; if not, setting the characteristic value in the corresponding remote mobile phone signaling data as a secondary characteristic value;
the main characteristic value is preferentially sent to a preset population gender identification model, and if the gender of the user corresponding to the signaling data of the mobile phone in different places is determined, the secondary characteristic value does not need to be sent to the preset population gender identification model; if the gender of the user corresponding to the remote mobile phone signaling data is not determined, the secondary characteristic value is sent to a preset population gender identification model to judge the gender of the user corresponding to the remote mobile phone signaling data again.
It should be noted that, the feature values in the corresponding remote mobile phone signaling data are divided into a main feature value and a secondary feature value, where if the main feature value can determine the gender of the corresponding user of the remote mobile phone signaling data, the secondary feature value does not need to be sent to the preset population gender identification model to save the calculation time.
According to an embodiment of the present invention, after the main feature value is preferentially sent to the preset population sex identification model, the method specifically includes:
Preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
comparing and calculating the difference value between the first male index and the first female index to obtain a first sex index difference value;
if the absolute value of the first sex index difference value is larger than a preset sex index difference threshold value, the sex with the large sex index is set as the sex corresponding to the user of the remote mobile phone signaling data;
if the absolute value of the first sex index difference value is not greater than the preset sex index difference threshold value, the sex of the user corresponding to the remote mobile phone signaling data is not determined.
It should be noted that, the gender of the user corresponding to the remote mobile phone signaling data is judged by the absolute value of the first gender index difference value, for example, the first gender index difference value is equal to the first male index minus the first female index, when the first gender index difference value is greater than the preset gender index difference threshold value, the gender of the user corresponding to the remote mobile phone signaling data is male, when the first gender difference value is negative and the absolute value of the corresponding first gender difference value is greater than the preset gender index difference threshold value, the gender of the user corresponding to the remote mobile phone signaling data is female, otherwise, the remote mobile phone signaling data needs to be judged by the secondary features.
According to an embodiment of the present invention, the step of sending the secondary feature value to a preset population gender identification model to determine the gender of the user corresponding to the signaling data of the remote mobile phone again specifically includes:
preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
transmitting the secondary characteristic value to a preset population sex identification model to obtain a second male index and a second female index;
accumulating the first male index and the second male index to obtain male index;
accumulating the first female index and the second female index to obtain female indexes;
comparing and analyzing the male index and the female index, and setting the gender of the user corresponding to the remote mobile phone signaling data as male if the male index is larger than the female index;
if the male index is smaller than the female index, the gender of the user corresponding to the remote mobile phone signaling data is set as female;
and if the male index is equal to the female index, judging through the maximum characteristic value in the signaling data of the remote mobile phone.
When the gender index corresponding to the main characteristic cannot judge the gender of the user corresponding to the remote mobile phone signaling data, the secondary characteristic is sent to a preset population gender identification model to obtain a second male index and a second female index, and if the male index is larger than the female index, the gender of the user corresponding to the remote mobile phone signaling data is set as a male; if the male index is smaller than the female index, the sex of the user corresponding to the remote mobile phone signaling data is set as female, otherwise, the judgment is carried out again according to the maximum characteristic value in the remote mobile phone signaling data.
According to the embodiment of the invention, if the male index is equal to the female index, the step of determining by the maximum eigenvalue in the signaling data of the mobile phone in different places specifically includes:
arranging the characteristic values in the signaling data of the remote mobile phone in order from small to large to obtain a first large characteristic value in the signaling data of the remote mobile phone;
transmitting a first large characteristic value in the signaling data of the remote mobile phone to a preset population sex identification model to obtain a third male index and a third female index;
comparing and analyzing the third male index and the third female index, and setting the gender with the large gender index as the gender of the user corresponding to the remote mobile phone signaling data;
and if the third male index and the third female index are equal, extracting a second large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and if the gender index corresponding to the second large characteristic value in the remote mobile phone signaling data is the same, continuously extracting a third large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and the like until the gender of the user corresponding to the remote mobile phone signaling data is distinguished.
When the male index is equal to the female sex index, the characteristic values in the remote mobile phone signaling data are arranged in the order from small to large, the first large characteristic value is firstly sent to a preset population sex identification model to obtain a third male index and a third female index, if the third male index is the same as the third female index, the second large characteristic value is continuously extracted for judgment, if the male index and the female index corresponding to the second large characteristic value are the same, the third large characteristic value is extracted for judgment, and the like, and if the male index and the female index are different, the sex with the large sex index is set as the sex of the user corresponding to the remote mobile phone signaling data.
The invention discloses a regional population sex identification method and a system based on signaling data, wherein the method comprises the following steps: acquiring mobile phone signaling data information of a preset area based on a preset first time period; dividing the mobile phone signaling data to obtain local mobile phone signaling data and remote mobile phone signaling data; inquiring in a preset local database according to the local mobile phone signaling data to obtain the gender of the user corresponding to the local mobile phone signaling data; extracting characteristic values in the signaling data of the mobile phones in different places, and sending the characteristic values to a preset population gender identification model to obtain the gender of the user corresponding to the signaling data of the mobile phones in different places; and combining and counting the local mobile phone signaling data corresponding user and the remote mobile phone signaling data corresponding user according to the same gender. According to the invention, the supervised learning algorithm is used for identifying and counting the gender of the population in the region based on the signaling data, so that the method is more accurate than the estimation according to the population equal proportion of the known gender, and the signaling data is convenient to acquire.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
Claims (6)
1. A method for regional population gender identification based on signaling data, comprising:
acquiring mobile phone signaling data information of a preset area based on a preset first time period;
dividing the mobile phone signaling data to obtain local mobile phone signaling data and remote mobile phone signaling data;
inquiring in a preset local database according to the local mobile phone signaling data to obtain the gender of the user corresponding to the local mobile phone signaling data;
extracting characteristic values in the signaling data of the mobile phones in different places, and sending the characteristic values to a preset population gender identification model to obtain the gender of the user corresponding to the signaling data of the mobile phones in different places;
combining and counting the local mobile phone signaling data corresponding user and the remote mobile phone signaling data corresponding user according to the same gender;
further comprises:
obtaining mobile track information of a user corresponding to the mobile phone signaling data according to the mobile phone signaling data;
extracting resident point information in the movement track information of the corresponding user;
obtaining a characteristic value in corresponding mobile phone signaling data according to resident point information in the movement track information of the corresponding user;
the characteristic values in the mobile phone signaling data comprise characteristic values in local mobile phone signaling data and characteristic values in remote mobile phone signaling data;
Further comprises:
extracting a characteristic value in local mobile phone signaling data;
performing feature processing on the feature values in the local mobile phone signaling data to obtain a space-time behavior feature rule of a user corresponding to the local mobile phone signaling data;
the method comprises the steps of sorting space-time behavior characteristic rules of users corresponding to local mobile phone signaling data and sexes of users corresponding to the local mobile phone signaling data, and dividing the space-time behavior characteristic rules and sexes into training samples and verification samples;
the training samples are sent to a preset initialization model for training, and the preset initialization model after training is obtained;
transmitting the verification sample to a preset initialization model after training to obtain gender prediction accuracy;
and when the gender prediction accuracy is greater than a preset accuracy threshold, stopping training by the preset initialization model to obtain a preset population gender identification model.
2. The method for identifying regional population gender based on signaling data according to claim 1, wherein the step of extracting the characteristic value in the signaling data of the mobile phone in different places and sending the characteristic value to a preset population gender identification model to obtain the gender of the user corresponding to the signaling data of the mobile phone in different places specifically comprises the following steps:
Comparing and analyzing the characteristic value in the signaling data of the remote mobile phone with a corresponding preset characteristic threshold value, judging whether the characteristic value in the signaling data of the remote mobile phone is larger than the corresponding preset characteristic threshold value, and if so, setting the characteristic value in the signaling data of the remote mobile phone as a main characteristic value; if not, setting the characteristic value in the corresponding remote mobile phone signaling data as a secondary characteristic value;
the main characteristic value is preferentially sent to a preset population gender identification model, and if the gender of the user corresponding to the signaling data of the mobile phone in different places is determined, the secondary characteristic value does not need to be sent to the preset population gender identification model; if the gender of the user corresponding to the remote mobile phone signaling data is not determined, the secondary characteristic value is sent to a preset population gender identification model to judge the gender of the user corresponding to the remote mobile phone signaling data again.
3. The method for regional population sex identification based on signaling data according to claim 2, wherein after the primary characteristic value is preferentially sent to the preset population sex identification model, the method specifically comprises:
preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
Comparing and calculating the difference value between the first male index and the first female index to obtain a first sex index difference value;
if the absolute value of the first sex index difference value is larger than a preset sex index difference threshold value, the sex with the large sex index is set as the sex corresponding to the user of the remote mobile phone signaling data;
if the absolute value of the first sex index difference value is not greater than the preset sex index difference threshold value, the sex of the user corresponding to the remote mobile phone signaling data is not determined.
4. The method for identifying regional population gender based on signaling data as set forth in claim 2, wherein the step of sending the secondary eigenvalue to a preset population gender identification model to re-determine the gender of the user corresponding to the signaling data of the cell phone in the different place specifically comprises:
preferentially sending the main characteristic values to a preset population sex identification model to obtain a first male index and a first female index;
transmitting the secondary characteristic value to a preset population sex identification model to obtain a second male index and a second female index;
accumulating the first male index and the second male index to obtain male index;
accumulating the first female index and the second female index to obtain female indexes;
Comparing and analyzing the male index and the female index, and setting the gender of the user corresponding to the remote mobile phone signaling data as male if the male index is larger than the female index;
if the male index is smaller than the female index, the gender of the user corresponding to the remote mobile phone signaling data is set as female;
and if the male index is equal to the female index, judging through the maximum characteristic value in the signaling data of the remote mobile phone.
5. The method for regional population sex identification based on signaling data as claimed in claim 4, wherein the step of determining by the maximum eigenvalue in the signaling data of the cell phone in different places if the male index is equal to the female index specifically comprises:
arranging the characteristic values in the signaling data of the remote mobile phone in order from small to large to obtain a first large characteristic value in the signaling data of the remote mobile phone;
transmitting a first large characteristic value in the signaling data of the remote mobile phone to a preset population sex identification model to obtain a third male index and a third female index;
comparing and analyzing the third male index and the third female index, and setting the gender with the large gender index as the gender of the user corresponding to the remote mobile phone signaling data;
And if the third male index and the third female index are equal, extracting a second large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and if the gender index corresponding to the second large characteristic value in the remote mobile phone signaling data is the same, continuously extracting a third large characteristic value in the remote mobile phone signaling data to judge the gender of the user corresponding to the remote mobile phone signaling data, and the like until the gender of the user corresponding to the remote mobile phone signaling data is distinguished.
6. A regional population sex identification system based on signaling data, comprising a memory and a processor, wherein the memory stores a regional population sex identification method program based on signaling data, and the regional population sex identification method program based on signaling data realizes the following steps when executed by the processor:
acquiring mobile phone signaling data information of a preset area based on a preset first time period;
dividing the mobile phone signaling data to obtain local mobile phone signaling data and remote mobile phone signaling data;
inquiring in a preset local database according to the local mobile phone signaling data to obtain the gender of the user corresponding to the local mobile phone signaling data;
Extracting characteristic values in the signaling data of the mobile phones in different places, and sending the characteristic values to a preset population gender identification model to obtain the gender of the user corresponding to the signaling data of the mobile phones in different places;
combining and counting the local mobile phone signaling data corresponding user and the remote mobile phone signaling data corresponding user according to the same gender;
further comprises:
obtaining mobile track information of a user corresponding to the mobile phone signaling data according to the mobile phone signaling data;
extracting resident point information in the movement track information of the corresponding user;
obtaining a characteristic value in corresponding mobile phone signaling data according to resident point information in the movement track information of the corresponding user;
the characteristic values in the mobile phone signaling data comprise characteristic values in local mobile phone signaling data and characteristic values in remote mobile phone signaling data;
further comprises:
extracting a characteristic value in local mobile phone signaling data;
performing feature processing on the feature values in the local mobile phone signaling data to obtain a space-time behavior feature rule of a user corresponding to the local mobile phone signaling data;
the method comprises the steps of sorting space-time behavior characteristic rules of users corresponding to local mobile phone signaling data and sexes of users corresponding to the local mobile phone signaling data, and dividing the space-time behavior characteristic rules and sexes into training samples and verification samples;
The training samples are sent to a preset initialization model for training, and the preset initialization model after training is obtained;
transmitting the verification sample to a preset initialization model after training to obtain gender prediction accuracy;
and when the gender prediction accuracy is greater than a preset accuracy threshold, stopping training by the preset initialization model to obtain a preset population gender identification model.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105095401A (en) * | 2015-07-07 | 2015-11-25 | 北京嘀嘀无限科技发展有限公司 | Method and apparatus for identifying gender |
| CN107886366A (en) * | 2017-11-22 | 2018-04-06 | 深圳市金立通信设备有限公司 | Generation method, sex fill method, terminal and the storage medium of Gender Classification model |
| CN109495856A (en) * | 2018-12-18 | 2019-03-19 | 成都方未科技有限公司 | A kind of mobile phone user's type mark method based on big data |
| CN110245981A (en) * | 2019-05-31 | 2019-09-17 | 南京瑞栖智能交通技术产业研究院有限公司 | A kind of crowd's kind identification method based on mobile phone signaling data |
| CN110990443A (en) * | 2019-10-28 | 2020-04-10 | 上海城市交通设计院有限公司 | Mobile phone signaling-based professional and living population characteristic estimation method |
| CN111615054A (en) * | 2020-05-25 | 2020-09-01 | 和智信(山东)大数据科技有限公司 | Population analysis method and device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11582336B1 (en) * | 2021-08-04 | 2023-02-14 | Nice Ltd. | System and method for gender based authentication of a caller |
-
2023
- 2023-09-28 CN CN202311272274.1A patent/CN116992267B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105095401A (en) * | 2015-07-07 | 2015-11-25 | 北京嘀嘀无限科技发展有限公司 | Method and apparatus for identifying gender |
| CN107886366A (en) * | 2017-11-22 | 2018-04-06 | 深圳市金立通信设备有限公司 | Generation method, sex fill method, terminal and the storage medium of Gender Classification model |
| CN109495856A (en) * | 2018-12-18 | 2019-03-19 | 成都方未科技有限公司 | A kind of mobile phone user's type mark method based on big data |
| CN110245981A (en) * | 2019-05-31 | 2019-09-17 | 南京瑞栖智能交通技术产业研究院有限公司 | A kind of crowd's kind identification method based on mobile phone signaling data |
| CN110990443A (en) * | 2019-10-28 | 2020-04-10 | 上海城市交通设计院有限公司 | Mobile phone signaling-based professional and living population characteristic estimation method |
| CN111615054A (en) * | 2020-05-25 | 2020-09-01 | 和智信(山东)大数据科技有限公司 | Population analysis method and device |
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