CN110287406A - Channel user recommended method, server and computer readable storage medium - Google Patents
Channel user recommended method, server and computer readable storage medium Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
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Abstract
The present invention relates to a kind of data analysis techniques, disclose a kind of channel user recommended method, this method comprises: in each channel information of front-end configuration and user information；All channel informations and user information are saved to backstage and are cached；The duplicate customer in cached user information is filtered by Bloom filter；The user information for meeting channel preset condition is assembled, is put into MongoDB database；According to the user information in the MongoDB database, corresponding user is recommended to different channels.The present invention also provides a kind of server and computer readable storage mediums.Channel user recommended method, server and computer readable storage medium provided by the invention accurately can recommend qualified user information for different channels, and avoid repeating to recommend to influence the channel treatment effeciency and user experience.
Description
Technical field
The present invention relates to data analysis technique field more particularly to a kind of channel user recommended methods, server and calculating
Machine readable storage medium storing program for executing.
Background technique
For the outer paging system of intelligence, generally there are a multiple and different operators, i.e. services channels, and each channel has pair
The rule limitation answered, system need to be recommended different users according to the restrictive condition and user information of each channel different
Channel.And the existing way of recommendation, accuracy and repeatability on do it is incomplete, recommend channel user may not enough
Accurately, or one user of appearance repeats to recommend multiple situation, leads to customer complaint, influences brand effect.In addition, accessing
When new channel, need to remodify code, test, hair version, service availability and stability reduce, manpower maintenance cost is high.
Summary of the invention
In view of this, the present invention proposes a kind of channel user recommended method, server and computer readable storage medium, with
Solve at least one above-mentioned technical problem.
Firstly, to achieve the above object, the present invention proposes a kind of channel user recommended method, and the method comprising the steps of:
In each channel information of front-end configuration and user information；
All channel informations and user information are saved to backstage and are cached；
The duplicate customer in cached user information is filtered by Bloom filter；
The user information for meeting channel preset condition is assembled, is put into MongoDB database；And
According to the user information in the MongoDB database, corresponding user is recommended to different channels.
Optionally, this method further comprises the steps of:
After recommending corresponding user information to the channel, recommend whether successfully to feed back from the channel reception user
Information, and the feedback information is synchronized in the user information.
Optionally, this method further comprises the steps of:
For successful user is recommended, setting no longer recommends the user to the channel within a predetermined period of time.
Optionally, the user information includes at least address name, phone number and passport NO..
Optionally, the duplicate customer filtered in cached user information by Bloom filter includes:
Using in the user information phone number of each user as the Bloom filter keyword, described in retrieval
Whether phone number is in the user information in the phone number set of other all users, to judge duplicate mobile phone
Number then filters out corresponding duplicate customer.
Optionally, described to assemble the user information for meeting channel preset condition, it is put into MongoDB database
Step includes:
From the preset condition needed for the channel dynamic acquisition and carry out intelligently parsing；
User information in caching described in repeating query, is matched with the preset condition；
The information for the user for meeting all preset conditions of the channel is grouped by the matched channel of institute, is put into described
In MongoDB database.
Optionally, the preset condition includes user information classification and limiting factor.
Optionally, the user information according in the MongoDB database, corresponding user is recommended different
The step of channel includes:
According to the corresponding user information set for being directed to the storage of each channel in the MongoDB database, described in acquisition
Then the user information is recommended corresponding channel by predetermined manner by the corresponding user information of channel.
In addition, to achieve the above object, the present invention also provides a kind of server, including memory, processor, the storages
The channel user's recommender system that can be run on the processor is stored on device, the channel user recommender system is by the place
It manages when device executes and realizes such as the step of above-mentioned channel user's recommended method.
Further, to achieve the above object, the present invention also provides a kind of computer readable storage medium, the computers
Readable storage medium storing program for executing is stored with channel user's recommender system, and the channel user recommender system can be held by least one processor
Row, so that at least one described processor is executed such as the step of above-mentioned channel user's recommended method.
Compared to the prior art, channel user recommended method, server and computer-readable storage proposed by the invention
Medium with preset condition needed for each channel of dynamic acquisition and can carry out intelligently parsing, will meet the use of channel preset condition
Family information is assembled, and is put into MongoDB, to be accurately that different channels is recommended according to the user information in MongoDB
Qualified user information improves and recommends success rate.Can also by Bloom filter filter duplicate customer, and to recommend at
The user of function is not repeated to recommend within a predetermined period of time, to avoid repeating to recommend to influence the channel treatment effeciency and user's body
It tests.In addition, can be handled using identical process when accessing new channel, not need to remodify code, test, hair
Version, improves service availability and stability, reduces manpower maintenance cost.
Detailed description of the invention
Fig. 1 is the schematic diagram of the optional hardware structure of server one of the present invention；
Fig. 2 is the program module schematic diagram of channel user recommender system first embodiment of the present invention；
Fig. 3 is the program module schematic diagram of channel user recommender system second embodiment of the present invention；
Fig. 4 is the flow diagram of channel user recommended method first embodiment of the present invention；
Fig. 5 is the flow diagram of channel user recommended method second embodiment of the present invention；
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.Based on the embodiments of the present invention, those of ordinary skill in the art are not before making creative work
Every other embodiment obtained is put, shall fall within the protection scope of the present invention.
It should be noted that the description for being related to " first ", " second " etc. in the present invention is used for description purposes only, and cannot
It is interpreted as its relative importance of indication or suggestion or implicitly indicates the quantity of indicated technical characteristic.Define as a result, " the
One ", the feature of " second " can explicitly or implicitly include at least one of the features.In addition, the skill between each embodiment
Art scheme can be combined with each other, but must be based on can be realized by those of ordinary skill in the art, when technical solution
Will be understood that the combination of this technical solution is not present in conjunction with there is conflicting or cannot achieve when, also not the present invention claims
Protection scope within.
As shown in fig.1, being the schematic diagram of the optional hardware structure of server 2 one of the present invention.
In the present embodiment, the server 2 may include, but be not limited only to, and can be in communication with each other connection by system bus and deposit
Reservoir 11, processor 12, network interface 13.It should be pointed out that Fig. 1 illustrates only the server 2 with component 11-13, but
Be it should be understood that, it is not required that implement all components shown, the implementation that can be substituted is more or less component.
Wherein, the server 2 can be rack-mount server, blade server, tower server or cabinet-type clothes
Business device etc. calculates equipment, which can be independent server, be also possible to server set composed by multiple servers
Group.
The memory 11 include at least a type of readable storage medium storing program for executing, the readable storage medium storing program for executing include flash memory,
Hard disk, multimedia card, card-type memory (for example, SD or DX memory etc.), random access storage device (RAM), static random are visited
It asks memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), may be programmed read-only deposit
Reservoir (PROM), magnetic storage, disk, CD etc..In some embodiments, the memory 11 can be the server
2 internal storage unit, such as the hard disk or memory of the server 2.In further embodiments, the memory 11 can also be with
It is the plug-in type hard disk being equipped on the External memory equipment of the server 2, such as the server 2, intelligent memory card (Smart
Media Card, SMC), secure digital (Secure Digital, SD) card, flash card (Flash Card) etc..Certainly, described
Memory 11 can also both including the server 2 internal storage unit and also including its External memory equipment.In the present embodiment,
The memory 11 is installed on the operating system and types of applications software of the server 2 commonly used in storage, such as channel is used
The program code etc. of family recommender system 200.It has exported or has incited somebody to action in addition, the memory 11 can be also used for temporarily storing
The Various types of data to be exported.
The processor 12 can be in some embodiments central processing unit (Central Processing Unit,
CPU), controller, microcontroller, microprocessor or other data processing chips.The processor 12 is commonly used in the control clothes
The overall operation of business device 2.In the present embodiment, the processor 12 for run the program code stored in the memory 11 or
Person handles data, such as runs the channel user recommender system 200 etc..
The network interface 13 may include radio network interface or wired network interface, which is commonly used in
Communication connection is established between the server 2 and other electronic equipments.
So far, oneself is through describing the hardware configuration and function of relevant device of the present invention in detail.In the following, above-mentioned introduction will be based on
It is proposed each embodiment of the invention.
Firstly, the present invention proposes a kind of channel user recommender system 200.
As shown in fig.2, being the Program modual graph of 200 first embodiment of channel user recommender system of the present invention.
In the present embodiment, the channel user recommender system 200 includes a series of calculating being stored on memory 11
Machine program instruction, when the computer program instructions are executed by processor 12, the channel that various embodiments of the present invention may be implemented is used
Recommend operation in family.In some embodiments, the specific operation realized based on the computer program instructions each section, channel are used
Family recommender system 200 can be divided into one or more modules.For example, in Fig. 2, the channel user recommender system 200
Configuration module 201, preserving module 202, filtering module 203, assembling module 204, recommending module 205 can be divided into.Wherein:
The configuration module 201, in each channel information of front-end configuration and user information.
Specifically, channel information corresponding to different channels is different, for example, the channel having need to obtain objective label and
List source, some need obtains objective channel and media source launches code, can be respectively channel letter needed for each channel configuration
Breath.User information needed for each channel is also different, contains address name, phone number and passport NO. substantially.Namely
It says, the user information includes at least address name, phone number and passport NO., according further to specifically wanting for each channel
It asks, the other information of corresponding user can also be configured.
The preserving module 202 is cached for saving all channel informations and user information to backstage.
Specifically, after the good all channel informations of front-end configuration and user information, all information is stored to backstage and are cached
In, it is further processed in case subsequent.
The filtering module 203, for filtering duplicate customer by Bloom filter.
Specifically, the duplicate customer is judged by repeated number code value (i.e. subscriber phone number).
Bloom filter (Bloom Filter) is actually a series of to reflect by a very long binary vector and at random
Function composition is penetrated, algorithm can be used for retrieving an element whether in a set similar to a hash set.It excellent
Point is space efficiency and query time all considerably beyond general algorithm, the disadvantage is that there is certain false recognition rate (false positive example False
Positives, i.e. Bloom Filter report a certain element there are in Mr. Yu's set, but actually the element is not being gathered
In) and delete difficulty, but without the situation of identification mistake (i.e. false counter-example False negatives, if some element is certain
Not in the set, then Bloom Filter will not report that the element is present in set, so will not fail to report).
The algorithm is not necessarily to store the value of key (keyword), for each key, it is only necessary to k bit, each storage one
A mark, for judging key whether in set.Specific algorithm includes:
1. each function, which can hash key, becomes 1 integer firstly the need of k hash function；
2. when initialization, needing a length is the array of n-bit, each bit is initialized as 0；
3. calculating k hashed value with k hash function, and ratio corresponding in array when some key, which is added, to be gathered
Special position is 1；
4. judge some key whether set when, calculate k hashed value with k hash function, and inquire it is right in array
The bit answered, if all bits are all 1, then it is assumed that key is in set.
Specifically, each subscriber phone number should as the key, judgement using in the user information in the present embodiment
Whether phone number is in set (phone numbers of other all users), to judge duplicate phone number, then mistake
Filter corresponding duplicate customer.
The assembling module 204 is put into MongoDB for assembling the user information for meeting channel preset condition
In database.
Specifically, the preset condition includes required user information classification, limiting factor (such as region limitation) etc..Often
A channel has corresponding rule limitation, needs from the preset condition needed for each channel dynamic acquisition and carries out intelligent solution
Analysis, is then matched with user information again.The user information in repeating query caching is required according to channel, it is all to the channel is met
The information of the user of preset condition assembles.For example, the user information that some channel needs has certain ten, and there are also regions to limit
System, the user only met with these conditions just can allow the channel to provide service for the user, by qualified user information
It is matched with the channel.The assembling, which refers to, is grouped all user informations by the matched channel of institute, then according to existing
User information is put into MongoDB database by some interfaces.
MongoDB is the database based on distributed document storage, is write by C Plus Plus, it is intended to mention for WEB application
For expansible high-performance data storage solution.The data structure that MongoDB is supported is very loose, is similar json
Bson format, therefore can store more complicated data type.The feature of MongoDB maximum is that the query language that it is supported is non-
Chang Qiang great, grammer are somewhat similarly to the query language of object-oriented, and the inquiry of similarity relation database list table almost may be implemented
Most functions, but also support to data establish index.MongoDB includes following characteristics:
Towards set (Collection-Oriented), i.e., data, which are grouped, is stored in data set, referred to as one collection
It closes (Collection).Each set has a unique identification name in the database, and may include unlimited number of
Document.The inner table (table) of the concept similarity relation type database (RDBMS) of set, unlike it does not need to define it is any
Mode (schema).Flash cache algorithm in Nytro MegaRAID technology can count greatly in quick identification database
According to the dsc data of concentration, consistent performance improvement is provided.
Mode is freely (schema-free), it is meant that for the document being stored in MongoDB database, does not need to know
Its any structure definition of road.If necessary, the document of different structure can be stored in the same lane database.Storage
Document in set is stored as the form of key-value pair.Key is used for one document of unique identification, is character string type, and is worth
It then can be the file type of various complexity.
The recommending module 205, for according to the user information in MongoDB database, corresponding user to be recommended
Different channels.
Specifically, it is stored with corresponding user information set for each channel in MongoDB database, from MongoDB
It is middle to obtain the corresponding user information of each channel, these users are then recommended into corresponding channel by predetermined manner.
Channel user recommender system provided in this embodiment can be gone forward side by side with preset condition needed for each channel of dynamic acquisition
The user information for meeting channel preset condition is assembled, is put into MongoDB, according in MongoDB by row intelligently parsing
User information be accurately that different channel recommends qualified user information, improve and recommend success rate.It can also pass through
Bloom filter filters duplicate customer, to avoid repeating to recommend to influence the channel treatment effeciency and user experience.
As shown in fig.3, being the Program modual graph of 200 second embodiment of channel user recommender system of the present invention.This implementation
In example, the channel user recommender system 200 is in addition to including the configuration module 201, the preserving module in first embodiment
It 202, further include synchronization module 206, setup module 207 except filtering module 203, assembling module 204, recommending module 205.
Feedback information is synchronized in user information by the synchronization module 206 for receiving feedback information.
Specifically, after recommending corresponding user information to channel, it is also necessary to from each channel reception feedback information, i.e., should
User recommends whether succeed, and then feedback information is synchronized in the user information, in case subsequent accurately manual service.
The setup module 207, for for successful user is recommended, the use no longer to be recommended in setting within a predetermined period of time
Family is to the channel.
Specifically, it can start above-mentioned process to timing or trigger-type, carry out the matching between user and channel, be every
A channel recommends corresponding user information.Recommend time and channel for recommending successful user will record, and is arranged predetermined
The user will not be recommended to the channel in period, again to avoid repeating to recommend to influence the channel treatment effeciency and user's body
It tests.
In addition, when having new channel access or user information change (newly-increased, delete, modification), it is only necessary to use with
Upper identical process is handled the matching relationship between i.e. renewable user and channel, recommends corresponding user's letter for new channel
Breath, or new user is recommended into corresponding channel.
Channel user recommender system provided in this embodiment can be gone forward side by side with preset condition needed for each channel of dynamic acquisition
The user information for meeting channel preset condition is assembled, is put into MongoDB, according in MongoDB by row intelligently parsing
User information be accurately that different channel recommends qualified user information, improve and recommend success rate.It can also pass through
Bloom filter filters duplicate customer, and to recommending successful user to be not repeated to recommend within a predetermined period of time, to avoid weight
It is multiple to recommend to influence the channel treatment effeciency and user experience.In addition, the present embodiment when accessing new channel, can use identical
Process is handled, and is not needed to remodify code, test, hair version, is improved service availability and stability, reduce manpower
Maintenance cost.
In addition, the present invention also proposes a kind of channel user recommended method.
As shown in fig.4, being the flow diagram of channel user recommended method first embodiment of the present invention.In the present embodiment
In, the execution sequence of the step in flow chart shown in Fig. 4 can change according to different requirements, and certain steps can be omitted.
Method includes the following steps:
Step S400, in each channel information of front-end configuration and user information.
Specifically, channel information corresponding to different channels is different, for example, the channel having need to obtain objective label and
List source, some need obtains objective channel and media source launches code, can be respectively channel letter needed for each channel configuration
Breath.User information needed for each channel is also different, contains address name, phone number and passport NO. substantially.Namely
It says, the user information includes at least address name, phone number and passport NO., according further to specifically wanting for each channel
It asks, the other information of corresponding user can also be configured.
All channel informations and user information are saved to backstage and are cached by step S402.
Specifically, after the good all channel informations of front-end configuration and user information, all information is stored to backstage and are cached
In, it is further processed in case subsequent.
Step S404 filters duplicate customer by Bloom filter.
Specifically, the duplicate customer is judged by repeated number code value (i.e. subscriber phone number).
Bloom filter is actually to be made of a very long binary vector and a series of random mapping functions, is calculated
Method can be used for retrieving an element whether in a set similar to a hash set.Its advantages be space efficiency and
Query time is all considerably beyond general algorithm, the disadvantage is that have certain false recognition rate and delete difficulty, but it is wrong without identification
Situation accidentally.
The algorithm is not necessarily to store the value of key, for each key, it is only necessary to which k bit, one mark of each storage are used
To judge key whether in set.Specific algorithm includes:
1. each function, which can hash key, becomes 1 integer firstly the need of k hash function；
2. when initialization, needing a length is the array of n-bit, each bit is initialized as 0；
3. calculating k hashed value with k hash function, and ratio corresponding in array when some key, which is added, to be gathered
Special position is 1；
4. judge some key whether set when, calculate k hashed value with k hash function, and inquire it is right in array
The bit answered, if all bits are all 1, then it is assumed that key is in set.
Specifically, each subscriber phone number should as the key, judgement using in the user information in the present embodiment
Whether phone number is in set (phone numbers of other all users), to judge duplicate phone number, then mistake
Filter corresponding duplicate customer.
Step S406 assembles the user information for meeting channel preset condition, is put into MongoDB database.
Specifically, the preset condition includes required user information classification, limiting factor (such as region limitation) etc..Often
A channel has corresponding rule limitation, needs from the preset condition needed for each channel dynamic acquisition and carries out intelligent solution
Analysis, is then matched with user information again.The user information in repeating query caching is required according to channel, it is all to the channel is met
The information of the user of preset condition assembles.For example, the user information that some channel needs has certain ten, and there are also regions to limit
System, the user only met with these conditions just can allow the channel to provide service for the user, by qualified user information
It is matched with the channel.The assembling, which refers to, is grouped all user informations by the matched channel of institute, then according to existing
User information is put into MongoDB database by some interfaces.
MongoDB is the database based on distributed document storage, is write by C Plus Plus, it is intended to mention for WEB application
For expansible high-performance data storage solution.The data structure that MongoDB is supported is very loose, is similar json
Bson format, therefore can store more complicated data type.The feature of MongoDB maximum is that the query language that it is supported is non-
Chang Qiang great, grammer are somewhat similarly to the query language of object-oriented, and the inquiry of similarity relation database list table almost may be implemented
Most functions, but also support to data establish index.
Corresponding user is recommended different channels according to the user information in MongoDB database by step S408.
Specifically, it is stored with corresponding user information set for each channel in MongoDB database, from MongoDB
It is middle to obtain the corresponding user information of each channel, these users are then recommended into corresponding channel by predetermined manner.
Channel user recommended method provided in this embodiment can be gone forward side by side with preset condition needed for each channel of dynamic acquisition
The user information for meeting channel preset condition is assembled, is put into MongoDB, according in MongoDB by row intelligently parsing
User information be accurately that different channel recommends qualified user information, improve and recommend success rate.It can also pass through
Bloom filter filters duplicate customer, to avoid repeating to recommend to influence the channel treatment effeciency and user experience.
As shown in figure 5, being the flow diagram of the second embodiment of channel user recommended method of the present invention.The present embodiment
In, the step S500-S508 of the channel user recommended method and the step S400-S408 of first embodiment are similar, difference
It is that this method further includes step S510-S512.
Method includes the following steps:
Step S500, in each channel information of front-end configuration and user information.
Specifically, channel information corresponding to different channels is different, for example, the channel having need to obtain objective label and
List source, some need obtains objective channel and media source launches code, can be respectively channel letter needed for each channel configuration
Breath.User information needed for each channel is also different, contains address name, phone number and passport NO. substantially.Namely
It says, the user information includes at least address name, phone number and passport NO., according further to specifically wanting for each channel
It asks, the other information of corresponding user can also be configured.
All channel informations and user information are saved to backstage and are cached by step S502.
Specifically, after the good all channel informations of front-end configuration and user information, all information is stored to backstage and are cached
In, it is further processed in case subsequent.
Step S504 filters duplicate customer by Bloom filter.
Specifically, the duplicate customer is judged by repeated number code value (i.e. subscriber phone number).
Bloom filter is actually to be made of a very long binary vector and a series of random mapping functions, is calculated
Method can be used for retrieving an element whether in a set similar to a hash set.Its advantages be space efficiency and
Query time is all considerably beyond general algorithm, the disadvantage is that have certain false recognition rate and delete difficulty, but it is wrong without identification
Situation accidentally.
The algorithm is not necessarily to store the value of key, for each key, it is only necessary to which k bit, one mark of each storage are used
To judge key whether in set.Specific algorithm includes:
1. each function, which can hash key, becomes 1 integer firstly the need of k hash function；
2. when initialization, needing a length is the array of n-bit, each bit is initialized as 0；
3. calculating k hashed value with k hash function, and ratio corresponding in array when some key, which is added, to be gathered
Special position is 1；
4. judge some key whether set when, calculate k hashed value with k hash function, and inquire it is right in array
The bit answered, if all bits are all 1, then it is assumed that key is in set.
Specifically, each subscriber phone number should as the key, judgement using in the user information in the present embodiment
Whether phone number is in set (phone numbers of other all users), to judge duplicate phone number, then mistake
Filter corresponding duplicate customer.
Step S506 assembles the user information for meeting channel preset condition, is put into MongoDB database.
Specifically, the preset condition includes required user information classification, limiting factor (such as region limitation) etc..Often
A channel has corresponding rule limitation, needs from the preset condition needed for each channel dynamic acquisition and carries out intelligent solution
Analysis, is then matched with user information again.The user information in repeating query caching is required according to channel, it is all to the channel is met
The information of the user of preset condition assembles.For example, the user information that some channel needs has certain ten, and there are also regions to limit
System, the user only met with these conditions just can allow the channel to provide service for the user, by qualified user information
It is matched with the channel.The assembling, which refers to, is grouped all user informations by the matched channel of institute, then according to existing
User information is put into MongoDB database by some interfaces.
MongoDB is the database based on distributed document storage, is write by C Plus Plus, it is intended to mention for WEB application
For expansible high-performance data storage solution.The data structure that MongoDB is supported is very loose, is similar json
Bson format, therefore can store more complicated data type.The feature of MongoDB maximum is that the query language that it is supported is non-
Chang Qiang great, grammer are somewhat similarly to the query language of object-oriented, and the inquiry of similarity relation database list table almost may be implemented
Most functions, but also support to data establish index.
Corresponding user is recommended different channels according to the user information in MongoDB database by step S508.
Specifically, it is stored with corresponding user information set for each channel in MongoDB database, from MongoDB
It is middle to obtain the corresponding user information of each channel, these users are then recommended into corresponding channel by predetermined manner.
Step S510 receives feedback information, feedback information is synchronized in user information.
Specifically, after recommending corresponding user information to channel, it is also necessary to from each channel reception feedback information, i.e., should
User recommends whether succeed, and then feedback information is synchronized in the user information, in case subsequent accurately manual service.
Step S512, for successful user is recommended, setting no longer recommends the user to the channel within a predetermined period of time.
Specifically, it can start above-mentioned process to timing or trigger-type, carry out the matching between user and channel, be every
A channel recommends corresponding user information.Recommend time and channel for recommending successful user will record, and is arranged predetermined
The user will not be recommended to the channel in period, again to avoid repeating to recommend to influence the channel treatment effeciency and user's body
It tests.
In addition, when having new channel access or user information change (newly-increased, delete, modification), it is only necessary to use with
Upper identical process is handled the matching relationship between i.e. renewable user and channel, recommends corresponding user's letter for new channel
Breath, or new user is recommended into corresponding channel.
Channel user recommended method provided in this embodiment can be gone forward side by side with preset condition needed for each channel of dynamic acquisition
The user information for meeting channel preset condition is assembled, is put into MongoDB, according in MongoDB by row intelligently parsing
User information be accurately that different channel recommends qualified user information, improve and recommend success rate.It can also pass through
Bloom filter filters duplicate customer, and to recommending successful user to be not repeated to recommend within a predetermined period of time, to avoid weight
It is multiple to recommend to influence the channel treatment effeciency and user experience.In addition, the present embodiment when accessing new channel, can use identical
Process is handled, and is not needed to remodify code, test, hair version, is improved service availability and stability, reduce manpower
Maintenance cost.
The present invention also provides another embodiments, that is, provide a kind of computer readable storage medium, the computer
Readable storage medium storing program for executing is stored with channel user's recommended program, and the channel user recommended program can be held by least one processor
Row, so that at least one described processor is executed such as the step of above-mentioned channel user's recommended method.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in a storage medium
In (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that a terminal device (can be mobile phone, computer, clothes
Business device, air conditioner or the network equipment etc.) execute method described in each embodiment of the present invention.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of channel user recommended method, which is characterized in that the method includes the steps:
In each channel information of front-end configuration and user information；
All channel informations and user information are saved to backstage and are cached；
The duplicate customer in cached user information is filtered by Bloom filter；
The user information for meeting channel preset condition is assembled, is put into MongoDB database；And
According to the user information in the MongoDB database, corresponding user is recommended to different channels.
2. channel user's recommended method as described in claim 1, which is characterized in that this method further comprises the steps of:
When to the channel recommend corresponding user information after, from the channel reception user recommend whether successful feedback letter
Breath, and the feedback information is synchronized in the user information.
3. channel user recommended method as claimed in claim 2, which is characterized in that this method further comprises the steps of:
For successful user is recommended, setting no longer recommends the user to the channel within a predetermined period of time.
4. channel user recommended method as described in any one of claims 1-3, which is characterized in that the user information is at least wrapped
Include address name, phone number and passport NO..
5. channel user recommended method as claimed in claim 4, which is characterized in that described to be delayed by Bloom filter filtering
The duplicate customer in user information deposited includes:
The phone number of each user retrieves the mobile phone as the keyword of the Bloom filter using in the user information
Whether number is in the user information in the phone number set of other all users, to judge duplicate cell-phone number
Code, then filters out corresponding duplicate customer.
6. channel user recommended method as described in any one of claims 1-3, which is characterized in that the channel that will meet is preset
The user information of condition is assembled, and the step being put into MongoDB database includes:
From the preset condition needed for the channel dynamic acquisition and carry out intelligently parsing；
User information in caching described in repeating query, is matched with the preset condition；
The information for the user for meeting all preset conditions of the channel is grouped by the matched channel of institute, is put into described
In MongoDB database.
7. channel user recommended method as claimed in claim 6, which is characterized in that the preset condition includes user information class
Other and limiting factor.
8. channel user recommended method as claimed in claim 6, which is characterized in that described according to the MongoDB database
In user information, the step of corresponding user is recommended different channels includes:
According to the corresponding user information set for being directed to the storage of each channel in the MongoDB database, the channel is obtained
Then the user information is recommended corresponding channel by predetermined manner by corresponding user information.
9. a kind of server, which is characterized in that the server includes memory, processor, and being stored on the memory can
The channel user's recommender system run on the processor, it is real when the channel user recommender system is executed by the processor
Now such as the step of channel user recommended method of any of claims 1-8.
10. a kind of computer readable storage medium, which is characterized in that the computer-readable recording medium storage has channel user
Recommender system, the channel user recommender system can be executed by least one processor, so that at least one described processor is held
Row is such as the step of channel user recommended method of any of claims 1-8.
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