CN101951623B - User behavior statistical method and device based on user events - Google Patents
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Abstract
The invention discloses a user behavior statistical method based on user events, comprising: after receiving a user event message, obtaining the dimensionality information of the current state of a user from basic user information; and according the dimensionality information of the current state of the user and the event type, adding 1 to the attribute value of the event correlation index in a corresponding statistical object embodiment. The invention also discloses a user behavior statistical device based on user events. The method and the device of the invention can compress the user behaviour according to the dimensionality space and save system resources. On the basis of the user events according to the dimensionality statistical result, the flexible analysis and statics of user behaviour in any dimensionality or dimensionality combination can be realized, and the ineffective dimensionality space event can be automatically rejected.
Description
Technical Field
The present invention relates to statistical techniques in the field of communications, and in particular, to a user behavior statistical method and apparatus based on user events.
Background
With the development of mobile networks, the interest of operators has been shifted from a load profit model to a content service profit model, so that the traditional performance statistics object has not been able to meet the requirement of operators for fine operation of mobile services, and the analysis of user behavior in due course becomes the basis of the interest goal and the profit improvement capability of operators. The user behavior analysis can be realized by counting the call records and the media message contents of the users, the contents contained in the call records and the media messages far exceed the traditional performance counting objects, counting and analyzing are carried out on the basis of the call records and the media messages, a series of indexes such as system performance, user behavior and the like can be deeply analyzed, and more valuable information can be obtained.
For a mobile user, his business behavior has a number of attributes, such as: the user location must belong to a certain location area, routing area, service area, etc., and the Access mode must belong to a certain Access mode, such as a second Generation mobile communication technology (2G), a third Generation mobile communication technology (3G, 3rd-Generation), or a fourth Generation mobile communication technology (4G), and the Access Point must belong to a certain Access Point Name (APN). In the following description, attributes such as a user location, an access method, and a home APN related to an event are referred to as a dimension, a service behavior type of the user is referred to as an event, and a statistical result of a specific service process is referred to as an index.
In the application of analyzing user behaviors, an operator needs to be able to analyze the user behaviors from multiple dimensions or combined dimensions and multiple indexes, for example, for a serving general packet radio Service technology Service support node (SGSN), the dimension concerned by the operator may be a specific or combined dimension in a series of dimensions such as a routing area, a location area, a Service area, a tracking area, an access point, an access mode, a Service type, a user category, and a terminal type, and the concerned index includes a series of statistical results such as the number of attached users, the number of activated users, the attachment success rate, the activation success rate, the paging success rate, the delay, the Quality of Service (QoS, Quality of Service), and the terminal type distribution.
For the statistical analysis requirement of the multi-dimensional and multi-index flexible operation, a common processing method is as follows: establishing a Cartesian model of an attention index in a statistical system, specifically, assuming that M dimensions exist in user information, and the operator attention index relates to N dimensions, wherein N is less than or equal to M, and D is used1、D2、......、DnRepresenting N dimensions, the number of corresponding elements of each dimension being N1、N2、......、NnThen the total number of records for the cartesian model can be expressed as:
N＝N1×N2×......×Nn
however, for the mobile communication field, the number of user-related dimensions is usually large, such as: SGSN dimensions include routing areas, location areas, access points, service areas, etc., if the above calculation formula is used, the total number of corresponding records will be very large, and the memory allocation and operation according to this method are difficult to meet the requirements of resources and performance of the existing system, so the above method needs to be improved, and the prior art has the following two solutions:
firstly, for the model, the dimension space is compressed according to the incidence relation of the dimension. For example, a fixed location area in the network model must be attributed to a particular routing area, and for other non-associated routing areas, the location area and other non-associated routing areas cannot be combined. By the method, certain dimension combinations which are unlikely to occur can be eliminated, so that the dimension space is compressed. Although this processing method can save part of the memory resources, the dimension compression method is too complex, and if the networking model of the network element changes, it is difficult to implement automatic processing.
Secondly, according to a predefined model, a fixed statistical model is established for the concerned dimensionality and index of an operator, and data statistical analysis is respectively carried out. The statistical method is suitable for real-time monitoring, and can obtain a higher compression ratio, but because the method is based on a fixed model and fixed indexes, the statistical function is single, and the flexible combination requirement of dimensionality is difficult to meet.
In summary, the conventional user behavior statistical method cannot realize multi-dimensional statistics and combined multi-dimensional statistics of user behaviors based on events.
Disclosure of Invention
In view of this, the main objective of the present invention is to provide a user behavior statistical method and device based on user events, which can implement multidimensional statistics and combined multidimensional statistics of user behaviors based on events.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
the invention provides a user behavior statistical method based on user events, which comprises the following steps:
after receiving a user event message, acquiring dimension information of the current state of a user from the currently stored user basic information;
and adding 1 to the count value of the event related index in the corresponding statistical object instance according to the dimension information and the event type of the current state of the user.
In the above solution, before obtaining the dimension information of the current state of the user from the currently stored user basic information, the method further includes:
and when the user event message carries the dimension of the event which changes, updating the stored user basic information according to the user dimension carried in the user event message.
In the above scheme, the adding 1 to the count value of the event related index in the corresponding statistical object instance according to the dimension information of the current state of the user and the event type specifically includes:
and searching a corresponding statistical object instance according to the dimension information of the currently stored user state, if the corresponding statistical object instance is found, adding 1 to the count value of the event related index in the statistical object instance according to the event type, if the corresponding statistical object instance is not found, creating a new statistical object instance, and adding 1 to the count value of the event related index in the statistical object instance according to the event type.
In the above scheme, the searching for the corresponding statistical object instance according to the currently stored dimension information of the user state specifically includes:
calculating an index corresponding to the dimension information according to the dimension information of the user state stored currently;
and searching a statistical object example corresponding to the index according to the index corresponding to the dimension information.
In the above scheme, the method further comprises:
and after the timer is overtime, the statistical result is stored, all the statistical object examples are cleared, and the statistics is restarted.
In the above scheme, the method further comprises:
and after the original statistics is finished, further analyzing and calculating the statistical result according to the user requirements, and outputting the calculation result.
The invention also provides a user behavior statistical device based on the user event, which comprises: a message analysis module and a statistic module; wherein,
the message analysis module is used for acquiring the dimension information of the current state of the user from the currently stored user basic information after receiving a user event message, and sending the acquired current dimension information of the user to the statistical module;
and the counting module is used for adding 1 to the counting value of the event related index in the corresponding counting object example according to the dimension information of the current state of the user and the event type after receiving the dimension information of the current state of the user sent by the message analysis module.
In the above scheme, the apparatus further includes a storage module, configured to store user basic information and a statistical object instance, where the user basic information includes dimension information of a current state of a user.
In the above scheme, the device further includes an acquisition module, configured to receive the user event message, and update the user basic information stored in the storage module according to the dimensionality carried in the user event message when the user event message carries the dimensionality of the event that changes this time.
In the above scheme, the apparatus further comprises: a timer and a clearing module; wherein,
the timer is used for triggering the clearing module after the timeout;
and the clearing module is used for storing the statistical result and then clearing all the statistical object instances.
In the above scheme, the device further comprises a calculation module, which is used for further analyzing and calculating the statistical result according to the user requirement after the statistics is completed, and outputting the calculation result.
According to the user behavior statistical method and device based on the user event, after the user event message is received, the count value of the event related index in the corresponding statistical object example is added with 1 according to the dimension information and the event type of the current state of the user, so that the user behavior can be classified and compressed according to the dimension attribute and the event type of the user, namely: the statistics of the multiple dimensions and the combined dimensions of the user behavior can be realized, and the system resources can be further saved; in addition, for example, in a mobile communication system, a specific location area is necessarily belonged to a specific routing area, and a user event is not necessarily generated due to the combination of two location areas without membership and the routing area, so that the scheme of the invention can also automatically eliminate an invalid dimension space event.
Calculating an index corresponding to the dimension information according to the dimension information of the current user state; according to the index corresponding to the dimension information, the statistical object instance corresponding to the index is searched, and therefore the statistical object instance corresponding to the dimension information can be found quickly.
In addition, after the original statistics is finished, according to the user requirements, the statistical results are further analyzed and calculated aiming at the user attention objects, and the calculation results are output for the user, so that secondary calculation can be realized on the basis of the original statistical results, and the user requirements are further met.
Drawings
FIG. 1 is a schematic flow chart of a user behavior statistical method based on user events according to the present invention;
FIG. 2 is a diagram illustrating the original statistical results of the first embodiment;
FIG. 3 is a diagram illustrating a dimension combination query result according to the first embodiment;
FIG. 4 is a diagram illustrating the output of a statistical activation success rate according to an embodiment;
FIG. 5 is a schematic diagram of a user behavior statistics apparatus based on user events according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
The event statistical method based on user behavior of the invention, as shown in fig. 1, comprises the following steps:
step 101: after receiving a user event message, acquiring dimension information of the current state of a user from the currently stored user basic information;
here, the user event message includes a user identifier, an event type, and an execution result, and the user basic information currently stored can be found according to the user identifier, that is: the user identification is index information of the currently stored user basic information; the currently stored user basic information comprises dimension information of the current state of the user; the dimension information of the current state of the user refers to specific information of all dimensions of the current state of the user; after receiving the user event message, searching the currently stored user basic information according to the user identification in the user event message, if not, indicating that the user event message of the user is received for the first time, storing the user basic information, and after receiving the user event message again, updating the user basic information on the basis of the first storage;
before obtaining the dimension information of the current state of the user from the currently saved user basic information, the method may further include:
when the dimensionality of the event is changed in the user event message, updating the stored user basic information according to the dimensionality in the user event message;
when the dimension information of the user changes, the user basic information carried in the user event message contains the dimension of the user which changes currently, for the dimension which does not change, the user basic information carried in the user event message can not be contained in the user basic information carried in the user event message, and if all the dimensions of the user change, the user basic information carried in the user event message contains all the current dimensions of the user; if the user basic information carried by the user event message contains the dimension of the user which changes currently, only the dimension of the user which changes in the stored user basic information is updated, and the dimension which does not change is not modified;
if the dimensionality of the user does not change, the user basic information carried in the user event message does not contain the dimensionality of the user, correspondingly, after the user event message is received, the dimensionality information in the stored user basic information is not updated, and the dimensionality information of the current state of the user is directly obtained from the currently stored user information.
Step 102: adding 1 to the count value of the event related index in the corresponding statistical object instance according to the dimension information and the event type of the current state of the user;
specifically, according to the dimension information of the user state stored currently, a corresponding statistical object instance is searched, if the corresponding statistical object instance is found, the count value of the event related index in the statistical object instance is added by 1 according to the event type, if the corresponding statistical object instance is not found, a new statistical object instance is created, and the count value of the event related index in the statistical object instance is added by 1 according to the event type;
the searching for the corresponding statistical object instance according to the currently stored dimension information of the user state specifically includes:
calculating an index corresponding to the dimension information according to the dimension information of the user state stored currently;
searching a statistical object example corresponding to the index according to the index corresponding to the dimension information;
because the dimension information of the user state contains specific information of multiple dimensions, in order to quickly find the statistical object instance corresponding to the dimension information, the index corresponding to the dimension information can be calculated by adopting a hash algorithm, a fifth edition (MD5) of a message digest algorithm, or other algorithms for digital signature, and then the corresponding statistical object instance is found by utilizing the index; the index may be a feature value;
one dimension information corresponds to one statistic object example, and the statistic object example comprises dimension specific information and a count value of an event correlation index; wherein, the counting of the event related index can be realized by a counter; for the counting values of the event related indexes, each event type corresponds to a set of counting values of the related indexes, and one statistical object instance can contain the counting values of the related indexes of various event types; in the practical application process, event types needing to be counted can be selected according to needs, and counters of relevant indexes are distributed according to the event types;
for step 102, for example, the event types to be counted are activation and paging, and accordingly, there are two counters for counting the activation related indicators in the object instance, that is: the counter for counting the successful times of activation and the counter for counting the failed times of activation, the number of the counters for paging related indexes is two, namely: and when the event type in the received user event message is activation and the execution result is activation success, adding 1 to the value of the counter for counting the activation success times in the corresponding counting object example.
According to the attributes of user services, setting a dimension information, wherein the attributes of the user services include a location area, a routing area, a service area, an access mode, an access point and the like of a user, the dimension information corresponds to a dimension space, and through steps 101 and 102, a plurality of events occurring in the same dimension space can be aggregated into a statistical record. For example, for a network element, assuming that the number of events per second is 10000 in a statistical period, for example, 15 minutes, the total number of events occurring in 15 minutes is 10000 × 60 × 15 — 9000000, if the average number of events occurring in each dimension space is 100, the corresponding statistical object instance will be: 9000000/100 is 90000 and the compression ratio is 1/100.
Of course, in the limit case, such as the statistical period is very short, when the average occurrence number of events in each dimension space is 1, that is: all events that occur are not repeated, then the number of statistical object instances equals the number of event occurrences. For a network element, the number of events occurring in a unit of time is generally fixed, so that the total number of events can be controlled within a predictable range by setting a statistical period.
The process of the step 101-102 can be called as an original counting process, after the original counting is completed, according to the user requirement, aiming at the user concerned object, the counting result is further analyzed and calculated, and the calculation result is output; the output mode can adopt a graphical mode, so that a user can visually see the operation result; the user needs may be a certain event statistic result in a certain dimension of interest, a certain event statistic result in a combination of dimensions, and the like.
In the practical application process, a statistical period may be set, such as: setting the statistical period to be 15 minutes, storing the statistical result of the period of time to a disk after the timer is overtime every 15 minutes, then clearing all statistical examples, and restarting to count the newly reported user event messages so that the user can further analyze and calculate the statistical result, thereby better meeting the user requirements.
Example one
The application scenario of this embodiment is: and (4) counting the activation success rate of the SGSN.
The dimension information of the user in this embodiment includes: location Area Identity (LAI), Routing Area Identity (RAI), Service Area Identity (SAI), APN, Radio Access Type (RAT), and Radio Network Controller (RNC) name, etc.; the events to be counted are attachment, activation, deactivation, paging, and the like, and correspondingly, counters for counting attachment success times, attachment failure times, activation success times, activation failure times, deactivation success times, deactivation failure times, paging success times, paging failure times, and the like are respectively configured, and a method for calculating an index corresponding to the dimensional information is set, for example: and (4) carrying out a Hash algorithm, and setting a statistical period to be 15 minutes.
After receiving the user event message, the SGSN finds out the stored user basic information according to the user identification carried in the user event message, and if the user event message carries the dimension of the event change, the stored user basic information is updated according to the dimension carried in the user event message; if the dimension information is not carried, the dimension information in the stored user basic information is not updated; in this embodiment, the user event message may be a message of an event such as attach, activation, deactivation, paging, and the like; when the geographic location, and/or the access mode, and/or the access point, etc. where the user is located are changed, the dimension information of the user is changed, in this embodiment, specifically, when one or more of LAI, RAI, SAI, APN, RAT, and RNC name is changed, the dimension information of the user is considered to be changed;
then, according to the dimension information of the user state stored currently, calculating an index corresponding to the dimension information, then, according to the index corresponding to the dimension information, searching a statistical object example corresponding to the index, if the corresponding statistical object example is found, adding 1 to the count value of the event related index in the statistical object example according to the event type, if the corresponding statistical object example is not found, creating a new statistical object example, and according to the event type, adding 1 to the count value of the event related index in the statistical object example, storing the statistical result every 15 minutes, then, clearing all the statistical examples, and restarting to count the newly reported user event message, thereby obtaining the original statistical result schematic diagram shown in fig. 2, wherein only the count value of the activation related index is listed in fig. 2, that is: the activation success number and the activation failure number, ACTIVE _ success in fig. 2 represents a statistical result of a counter of the activation success number, and ACTIVE _ FAIL represents a statistical result of a counter of the activation failure number.
Selecting a dimension or combination of dimensions of interest, such as: the selected combination of dimensions is (LAI 32432, RAI 3256, SAI 3247, APN xcom. 16:00:00 to 18:15:00, according to the original statistical result, the dimension combination query result shown in fig. 3 can be obtained, and then according to the query result, the activation success rate is counted to obtain the output result shown in fig. 4; in practical application, a dimension or a combination of dimensions concerned can be selected by using a Structured Query Language (SQL), and then the activation success rate is calculated. The calculation formula of the statistical activation success rate is as follows:
activation success rate is activation success times/(activation success times + activation failure times) 100;
here, the activation success number and the activation failure number are respectively the activation success number and the activation failure number of the concerned dimension or the dimension combination query result in the period of time.
As can be seen from the above description, index analysis and comparison of any dimension or combination of dimensions of the SGSN can be achieved.
Example two
The application scenario of this embodiment is: and (3) counting the bearing updating success rate of a Gateway general packet radio service technology Support Node (GGSN).
The dimension information of the user in this embodiment includes: LAI, RAI, SAI, APN, RAT, and RNC names, etc.; the events to be counted are activation, deactivation, bearer update, and the like, and correspondingly, counters for counting activation success times, activation failure times, deactivation success times, deactivation failure times, bearer update success times, bearer update failure times, and the like are respectively configured, and a method for calculating an index corresponding to the dimensional information is set, for example: and (4) carrying out a Hash algorithm, and setting a statistical period to be 15 minutes.
After receiving the user event message, the GGSN finds out the stored user basic information according to the user identification carried in the user event message, and if the user event message carries the dimension of the event change, updates the stored user basic information according to the dimension carried in the user event message; if the dimension is not carried, the dimension information in the stored user basic information is not updated; in this embodiment, the user event message may be a message of an event such as activation, deactivation, and bearer update; when the geographic location, and/or the access mode, and/or the access point, etc. where the user is located are changed, the dimension information of the user is changed, in this embodiment, specifically, when one or more of LAI, RAI, SAI, APN, RAT, and RNC name is changed, the dimension information of the user is considered to be changed;
then, according to the dimension information of the user state stored currently, calculating an index corresponding to the dimension information, then, according to the index corresponding to the dimension information, searching a statistical object example corresponding to the index, if the corresponding statistical object example is found, adding 1 to the count value of the event related index in the statistical object example according to the event type, if the corresponding statistical object example is not found, creating a new statistical object example, and according to the event type, adding 1 to the count value of the event related index in the statistical object example, storing the statistical result every 15 minutes, then, clearing all the statistical examples, restarting to perform statistics on the newly reported user event message, wherein the obtained original statistical result is similar to the original statistical result shown in fig. 2.
Selecting concerned dimensionality or dimensionality combination, obtaining concerned dimensionality or dimensionality combination query result according to original statistical result, then counting bearing update success rate according to the query result, and in practical application, selecting concerned dimensionality or dimensionality combination by using SQL, and then calculating the bearing update success rate. Wherein, the calculation formula of the success rate of the bearing update activation is as follows:
the bearer update success rate is the bearer update success times/(bearer update success times + bearer update failure times) 100;
here, the bearer update success number and the bearer update failure number are respectively the bearer update success number and the bearer update failure number of the concerned dimension or the dimension combination query result in the period of time.
As can be seen from the above description, index analysis and comparison of any dimension or combination of dimensions of the GGSN can be achieved.
In order to implement the above method, the present invention further provides a user behavior statistics apparatus based on user events, as shown in fig. 5, the apparatus includes: a message analysis module 51 and a statistic module 52; wherein,
the message analysis module 51 is configured to, after receiving a user event message, obtain the dimension information of the current state of the user from the currently stored user basic information, and send the obtained current dimension information of the user to the statistics module 52;
the counting module 52 is configured to, after receiving the dimension information of the current state of the user sent by the message analysis module 51, add 1 to the count value of the event related index in the corresponding statistical object instance according to the dimension information of the current state of the user and the event type.
The device may further include a storage module 53, configured to store user basic information and a statistical object instance, where the user basic information includes dimension information of a current state of a user;
the device may further include an acquisition module 54, configured to receive the user event message, and update the user basic information stored in the storage module 53 according to the dimension carried in the user event message when the user event message carries the dimension that changes in the event.
The statistical module 52 is specifically configured to: and searching a corresponding statistical object instance according to the dimension information of the currently stored user state, if the corresponding statistical object instance is found, adding 1 to the count value of the event related index in the statistical object instance according to the event type, if the corresponding statistical object instance is not found, creating a new statistical object instance, and adding 1 to the count value of the event related index in the statistical object instance according to the event type.
The apparatus may further comprise: a timer and a clearing module; wherein,
the timer is used for triggering the clearing module after the timeout;
and the clearing module is used for storing the statistical result and then clearing all the statistical object instances.
The storage module 53 is further configured to store the statistical result.
The apparatus may further comprise: and the calculation module is used for further analyzing and calculating the statistical result according to the user requirement after the statistics is finished, and outputting the calculation result.
The above description is only exemplary of the present invention and should not be taken as limiting the scope of the present invention, and any modifications, equivalents, improvements, etc. that are within the spirit and principle of the present invention should be included in the present invention.
Claims (9)
1. A user behavior statistical method based on user events is characterized by comprising the following steps:
after receiving a user event message, when the user event message carries a dimension of the event, updating the stored user basic information according to the changed dimension, wherein the user basic information comprises: dimension information of the current state of the user;
acquiring dimension information of the current state of the user from the updated basic user information;
searching a corresponding statistical object example according to the dimension information;
and adding 1 to the count value of the event correlation index in the corresponding statistical object instance according to the event type.
2. The method of claim 1, further comprising:
and if the corresponding statistical object instance is not found according to the dimension information of the currently stored user state, creating a new statistical object instance, and adding 1 to the count value of the event related index in the statistical object instance according to the event type.
3. The method according to claim 1, wherein the searching for the corresponding statistical object instance according to the dimension information of the currently stored user state specifically includes:
calculating an index corresponding to the dimension information according to the dimension information of the user state stored currently;
and searching a statistical object example corresponding to the index according to the index corresponding to the dimension information.
4. The method of claim 1, further comprising:
and after the timer is overtime, the statistical result is stored, all the statistical object examples are cleared, and the statistics is restarted.
5. The method of claim 1 or 4, further comprising:
and after the original statistics is finished, further analyzing and calculating the statistical result according to the user requirements, and outputting the calculation result.
6. A user behavior statistics apparatus based on user events, the apparatus comprising: the device comprises an acquisition module, a message analysis module and a statistic module; wherein,
the acquisition module is used for receiving the user event message, and when the user event message carries the dimension of the event change, updating the user basic information stored in the storage module according to the dimension carried in the user event message, wherein the user basic information comprises: dimension information of the current state of the user;
the message analysis module is used for acquiring the dimension information of the current state of the user from the updated user basic information and sending the acquired current dimension information of the user to the statistical module;
and the counting module is used for searching a corresponding counting object example according to the dimension information after receiving the dimension information of the current state of the user, which is sent by the message analysis module, and adding 1 to the counting value of the event related index in the corresponding counting object example according to the event type.
7. The apparatus of claim 6, further comprising a storage module for storing user basic information and the statistical object instance, wherein the user basic information includes dimension information of a current state of the user.
8. The apparatus of claim 6, further comprising: a timer and a clearing module; wherein,
the timer is used for triggering the clearing module after the timeout;
and the clearing module is used for storing the statistical result and then clearing all the statistical object instances.
9. The device of claim 6 or 8, further comprising a calculation module for performing further analysis and calculation on the statistical result according to the user requirement after the statistics is completed, and outputting the calculation result.
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| PCT/CN2011/071904 WO2012034388A1 (en) | 2010-09-13 | 2011-03-17 | Method and apparatus for user behaviors statistics based on user events |
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| CN101951623A (en) | 2011-01-19 |
| WO2012034388A1 (en) | 2012-03-22 |
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