CN109951859A - Wireless network connection recommended method, device, electronic equipment and readable medium - Google Patents
Wireless network connection recommended method, device, electronic equipment and readable medium Download PDFInfo
- Publication number
- CN109951859A CN109951859A CN201910226151.1A CN201910226151A CN109951859A CN 109951859 A CN109951859 A CN 109951859A CN 201910226151 A CN201910226151 A CN 201910226151A CN 109951859 A CN109951859 A CN 109951859A
- Authority
- CN
- China
- Prior art keywords
- scoring
- network
- wireless network
- connection
- attribute
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Mobile Radio Communication Systems (AREA)
Abstract
This disclosure relates to a kind of wireless network connection recommended method, device, electronic equipment and computer-readable medium.This method comprises: obtaining the network information of multiple wireless networks according to user instructions, the network information includes network identity and signal strength；Multiple attribute ratings of the multiple wireless network are determined based on the network identity；Multiple environment scoring of the multiple wireless network is determined based on the signal strength；Determine that multiple quality of connection of the multiple wireless network score by the multiple attribute ratings and the scoring of the multiple environment；And wireless network connection recommendation is carried out based on the scoring of the multiple quality of connection.This disclosure relates to wireless network connection recommended method, device, electronic equipment and computer-readable medium, the available wireless network resource that success rate is high, online rate is high can be recommended for user.
Description
Technical field
This disclosure relates to computer information processing field, in particular to a kind of wireless network connection recommended method, dress
It sets, electronic equipment and computer-readable medium.
Background technique
Universal with Internet resources is enriched, and demand of the user to network is more and more, and wireless network was due to using
It is not limited by regional context in journey, there is extensive user demand space.At present when user is needed in any place using nothing
When line Internet resources, equipment can detect and simultaneously scan for a large amount of wireless network resource.How to be provided in a large amount of wireless network
An available wireless network resource is rapidly and accurately determined in source, and the network service for obtaining high quality is currently urgently to solve
Certainly the problem of.
Therefore, it is necessary to a kind of new wireless network connection recommended method, device, electronic equipment and computer-readable mediums.
Above- mentioned information are only used for reinforcing the understanding to the background of the disclosure, therefore it disclosed in the background technology part
It may include the information not constituted to the prior art known to persons of ordinary skill in the art.
Summary of the invention
In view of this, the disclosure provides a kind of wireless network connection recommended method, device, electronic equipment and computer-readable
Medium can recommend the available wireless network resource that success rate is high, online rate is high for user.
Other characteristics and advantages of the disclosure will be apparent from by the following detailed description, or partially by the disclosure
Practice and acquistion.
According to the one side of the disclosure, a kind of wireless network connection recommended method is proposed, this method comprises: referring to according to user
The network information for obtaining multiple wireless networks is enabled, the network information includes network identity and signal strength；Based on the network
Mark determines multiple attribute ratings of the multiple wireless network；The multiple wireless network is determined based on the signal strength
Multiple environment scorings；The multiple of the multiple wireless network are determined by the multiple attribute ratings and the scoring of the multiple environment
Quality of connection scoring；And wireless network connection recommendation is carried out based on the scoring of the multiple quality of connection.
In a kind of exemplary embodiment of the disclosure, the multiple wireless network are determined based on the network identity more
A attribute ratings include: to determine that multiple attributes of the multiple wireless network are commented by online data collection based on the network identity
Point；And multiple attribute ratings of the multiple wireless network are determined by off-line data collection based on the network identity.
In a kind of exemplary embodiment of the disclosure, determined based on the network identity by online data collection described more
Multiple attribute ratings of a wireless network further include: the network information and attribute ratings model based on multiple wireless networks obtain institute
State online data collection.
In a kind of exemplary embodiment of the disclosure, further includes: obtain multiple wireless networks essential attribute log and
Connect user behaviors log；The corresponding essential attribute log of the multiple wireless network is assigned to just based on the connection user behaviors log
In sample set and negative sample set；And by the positive sample set and the negative sample set to machine learning model into
Row training is with the determination attribute ratings model.
In a kind of exemplary embodiment of the disclosure, the connection user behaviors log is based on by the multiple wireless network pair
It includes: the company obtained in the connection user behaviors log that the essential attribute log answered, which is assigned in positive sample set and negative sample set,
It is connected into power and online rate；And by power and the online rate of connecting by the corresponding base of the multiple wireless network
This property logs is assigned in positive sample set and negative sample set.
In a kind of exemplary embodiment of the disclosure, by the positive sample set and the negative sample set to machine
Learning model, which is trained, comprises determining that the model structure of Random Forest model and model are deep with the determination attribute ratings model
Degree；Using Gini coefficient as the loss function of the Random Forest model；And the positive sample set and the negative sample collection
It closes and is trained in the input Random Forest model that setting completed with the determination attribute ratings model.
In a kind of exemplary embodiment of the disclosure, the network information and attribute ratings model based on multiple wireless networks
Obtaining the online data collection includes: to extract multi-dimensional feature data by the essential attribute log and connection user behaviors log of wireless network
Set；The corresponding multiple multi-dimensional feature data collection of multiple wireless networks are inputted in the attribute ratings model, are obtained more
A initial score；The multiple initial score and predetermined scoring section are compared to generate multiple attribute ratings；And it is logical
Cross the corresponding attribute ratings generation online data collection of the network identity of multiple wireless networks.
In a kind of exemplary embodiment of the disclosure, the multiple initial score and predetermined scoring section are compared
Before generating multiple attribute ratings further include: the multiple initial score is carried out the processing of broad sense power transformationization, generation is multiple
Target scoring；Calculate the mean value and variance of the multiple target scoring；And by described in the mean value and variance generation
Predetermined scoring section.
In a kind of exemplary embodiment of the disclosure, scored by the multiple attribute ratings and the multiple environment true
Multiple quality of connection scoring of fixed the multiple wireless network includes: to be determined and belonged to based on historical status scoring and history environment scoring
Property scoring weight and environment score weight；And pass through the multiple attribute ratings, the attribute ratings weight and the multiple
Environment scoring, environment scoring weight determine multiple quality of connection scoring of the multiple wireless network.
In a kind of exemplary embodiment of the disclosure, is scored based on historical status scoring and history environment and determine that attribute is commented
Fraction weight and environment scoring weight include: to be scored based on gray scale test mode and historical status scoring, history environment and determined attribute
The weight that scores and environment scoring weight；And logic-based returns mode and historical status scoring, history environment scoring determine and belong to
Property scoring weight and environment score weight.
In a kind of exemplary embodiment of the disclosure, propose that a kind of wireless network connection recommendation apparatus, the device include:
Network information module, for obtaining the network information of multiple wireless networks according to user instructions, the network information includes network
Mark and signal strength；Attribute ratings module, for determining multiple categories of the multiple wireless network based on the network identity
Property scoring；Environment grading module, for determining that multiple environment of the multiple wireless network score based on the signal strength；Matter
Grading module is measured, for determining the more of the multiple wireless network by the multiple attribute ratings and the scoring of the multiple environment
A quality of connection scoring；And connection recommending module, for carrying out wireless network connection based on the scoring of the multiple quality of connection
Recommend.
According to the one side of the disclosure, a kind of electronic equipment is proposed, which includes: one or more processors；
Storage device, for storing one or more programs；When one or more programs are executed by one or more processors, so that one
A or multiple processors realize such as methodology above.
According to the one side of the disclosure, it proposes a kind of computer-readable medium, is stored thereon with computer program, the program
Method as mentioned in the above is realized when being executed by processor.
According to wireless network connection recommended method, device, electronic equipment and the computer-readable medium of the disclosure, pass through nothing
The attribute ratings of gauze network and signal, which score, determines wireless network connection quality score, and based on quality of connection scoring be user into
The mode of row network recommendation can recommend the available wireless network resource that success rate is high, online rate is high for user.
It should be understood that the above general description and the following detailed description are merely exemplary, this can not be limited
It is open.
Detailed description of the invention
Its example embodiment is described in detail by referring to accompanying drawing, above and other target, feature and the advantage of the disclosure will
It becomes more fully apparent.Drawings discussed below is only some embodiments of the present disclosure, for the ordinary skill of this field
For personnel, without creative efforts, it is also possible to obtain other drawings based on these drawings.
Fig. 1 is the system scenarios of a kind of wireless network connection recommended method shown according to an exemplary embodiment and device
Block diagram.
Fig. 2 is the application scenarios of a kind of wireless network connection recommended method shown according to an exemplary embodiment and device
Block diagram.
Fig. 3 is a kind of flow chart of wireless network connection recommended method shown according to an exemplary embodiment.
Fig. 4 is a kind of flow chart of the wireless network connection recommended method shown according to another exemplary embodiment.
Fig. 5 is a kind of schematic diagram of the wireless network connection recommended method shown according to another exemplary embodiment.
Fig. 6 is a kind of flow chart of the wireless network connection recommended method shown according to another exemplary embodiment.
Fig. 7 is a kind of block diagram of wireless network connection recommendation apparatus shown according to an exemplary embodiment.
Fig. 8 is the block diagram of a kind of electronic equipment shown according to an exemplary embodiment.
Fig. 9 is a kind of computer readable storage medium schematic diagram shown according to an exemplary embodiment.
Specific embodiment
Example embodiment is described more fully with reference to the drawings.However, example embodiment can be real in a variety of forms
It applies, and is not understood as limited to embodiment set forth herein；On the contrary, thesing embodiments are provided so that the disclosure will be comprehensively and complete
It is whole, and the design of example embodiment is comprehensively communicated to those skilled in the art.Identical appended drawing reference indicates in figure
Same or similar part, thus repetition thereof will be omitted.
In addition, described feature, structure or characteristic can be incorporated in one or more implementations in any suitable manner
In example.In the following description, many details are provided to provide and fully understand to embodiment of the disclosure.However,
It will be appreciated by persons skilled in the art that can with technical solution of the disclosure without one or more in specific detail,
Or it can be using other methods, constituent element, device, step etc..In other cases, it is not shown in detail or describes known side
Method, device, realization or operation are to avoid fuzzy all aspects of this disclosure.
Block diagram shown in the drawings is only functional entity, not necessarily must be corresponding with physically separate entity.
I.e., it is possible to realize these functional entitys using software form, or realized in one or more hardware modules or integrated circuit
These functional entitys, or these functional entitys are realized in heterogeneous networks and/or processor device and/or microcontroller device.
Flow chart shown in the drawings is merely illustrative, it is not necessary to including all content and operation/step,
It is not required to execute by described sequence.For example, some operation/steps can also decompose, and some operation/steps can close
And or part merge, therefore the sequence actually executed is possible to change according to the actual situation.
It should be understood that although herein various assemblies may be described using term first, second, third, etc., these groups
Part should not be limited by these terms.These terms are to distinguish a component and another component.Therefore, first group be discussed herein below
Part can be described as the second component without departing from the teaching of disclosure concept.As used herein, term " and/or " include associated
All combinations for listing any of project and one or more.
It will be understood by those skilled in the art that attached drawing is the schematic diagram of example embodiment, module or process in attached drawing
Necessary to not necessarily implementing the disclosure, therefore it cannot be used for the protection scope of the limitation disclosure.
Fig. 1 is the system scenarios of a kind of wireless network connection recommended method shown according to an exemplary embodiment and device
Block diagram.
As shown in Figure 1, system architecture 100 may include user equipment 101,102,103, network 104 and server 105,
The network equipment 106,107,108.Network 104 to user equipment 101,102,103 and server 105, the network equipment 106,
107, the medium of communication link is provided between 108.Network 104 may include various connection types, such as wired, wireless communication link
Road or fiber optic cables etc..
User can be used user equipment 101,102,103 and be interacted by network 104 with server 105, to receive or send out
Send message etc..Various telecommunication customer end applications, such as the application of shopping class, net can be installed on user equipment 101,102,103
The application of page browsing device, searching class application, instant messaging tools, mailbox client, social platform software etc..More specifically, at this
In disclosed embodiment, user can be assisted to carry out wireless network connection operation by a scheduled APP application.
User equipment 101,102,103 can be the various electronic equipments with display screen and supported web page browsing, packet
Include but be not limited to smart phone, tablet computer, pocket computer on knee and desktop computer etc..
The network equipment 106,107,108 is can to provide the equipment of wireless network connection, user by user equipment 101,
102,103 connect with the network equipment 106,107,108 after, can pass through the network equipment 106,107,108 carry out network data
Transmission operation.
User equipment 101,102,103 can for example obtain the network information of the network equipment 106,107,108, the network letter
Breath includes network identity and signal strength；User equipment 101,102,103 for example can determine that network is set based on the network identity
Standby 106,107,108 multiple attribute ratings；User equipment 101,102,103 for example can determine network based on the signal strength
Multiple environment of equipment 106,107,108 score；User equipment 101,102,103 can for example by the multiple attribute ratings with
The multiple environment, which scores, determines multiple quality of connection scoring of the network equipment 106,107,108；User equipment 101,102,103
It can for example be scored based on the multiple quality of connection and carry out wireless network connection recommendation.
Server 105 can be to provide the server of various services, such as pass through user equipment 101,102,103 to user
The background server that the connection request submitted is handled.Server 105 can be to the network of the network equipment 106,107,108
Performance carries out the processing such as analyzing, and processing result is fed back to user equipment.
Server 105 can for example obtain the network information of multiple wireless networks, the network information packet according to user instructions
Include network identity and signal strength；Server 105 for example can determine the network equipment 106,107,108 based on the network identity
Multiple attribute ratings；Server 105 can for example determine multiple environment of the network equipment 106,107,108 based on the signal strength
Scoring；Server 105 can for example be scored by the multiple attribute ratings and the multiple environment determine the network equipment 106,
107,108 multiple quality of connection scoring；Server 105 can for example be scored based on the multiple quality of connection and carry out wireless network
Connection is recommended.
Server 105 can be the server of an entity, also may be, for example, multiple server compositions, needs to illustrate
It is that wireless network connection recommended method provided by the embodiment of the present disclosure can be executed by server 105 and/or user equipment
101,102,103 execute, correspondingly, wireless network connection recommendation apparatus can be set in server 105/ or user equipment 101,
102, in 103.
According to the wireless network connection recommended method and device of the disclosure, commented by the attribute ratings and signal of wireless network
Divide and determine wireless network connection quality score, and is the mode that user carries out network recommendation, Neng Gouwei based on quality of connection scoring
User recommends the available wireless network resource that success rate is high, online rate is high.
Fig. 2 is the application scenarios of a kind of wireless network connection recommended method shown according to an exemplary embodiment and device
Block diagram.In embodiment of the disclosure, user can be assisted to carry out wireless network (WiFi) even by a scheduled APP application
Connect operation.As shown in Fig. 2, being attempted when user wants that obtaining wireless network resource carries out wireless network connection by user equipment
Use scheduled APP application auxiliary connection network.User is by the APP application request wireless network connection, and user equipment is to more
A Wireless Communication Equipment is identified.User equipment can be obtained according to the network connection state of current equipment of itself using Different Strategies
The quality of connection scoring of multiple Wireless Communication Equipment is got, and is arranged according to the corresponding quality of connection fraction levels of wireless device
Sequence shows user.
Wherein, in the embodiments of the present disclosure, it is corresponding to may be defined as each wireless device for the corresponding quality of connection of wireless device
By user attempt connection and successful connection ability.
After carrying out wireless network connection recommendation, user can be according to the Wireless Communication Equipment list of scheduled APP offer
Click connection WiFi.The disclosure changes nothing in predetermined APP display interface by scoring Wireless Communication Equipment quality of connection
Line network device list puts in order, thus recommend user it is best connect wireless network, improve user use body
It tests, to increase the retention of user.
Fig. 3 is a kind of flow chart of wireless network connection recommended method shown according to an exemplary embodiment.Wireless network
Network connects recommended method 30 and includes at least step S302 to S310.
As shown in figure 3, obtaining the network information of multiple wireless networks, the network letter according to user instructions in S302
Breath includes network identity and signal strength.As shown in Fig. 2, user for example can send predetermined instruction on scheduled APP, make a reservation for refer to
Wireless network connection can be requested for the Wireless Communication Equipment near user by enabling.
In one embodiment, the network information of multiple wireless networks near user can be obtained according to user instructions.Its
Network identity in the middle network information can be the hardware number of wireless device, and physical address etc. can uniquely determine the wireless device
Mark, the signal strength in the network information is the current wireless signal strength of wireless device.
In S304, multiple attribute ratings of the multiple wireless network are determined based on the network identity.
In one embodiment, multiple attribute ratings packets of the multiple wireless network are determined based on the network identity
It includes: determining multiple attribute ratings of the multiple wireless network by online data collection based on the network identity.Can for example,
When user equipment has network connection state, user equipment initiates to request to background server, passes through the online data of server end
Collection obtains the corresponding attribute ratings of multiple wireless networks.
In one embodiment, the network information and attribute ratings model based on multiple wireless networks obtain described in line number
It include: that multi-dimensional feature data set is extracted by the essential attribute log and connection user behaviors log of wireless network according to collection；By multiple nothings
The corresponding multiple multi-dimensional feature data collection of gauze network input in the attribute ratings model, obtain multiple initial scores；It will
The multiple initial score and predetermined scoring section are compared to generate multiple attribute ratings；And pass through multiple wireless networks
The corresponding attribute ratings of network identity generate the online data collection.Wherein, the acquisition process of online data collection will be
It is described in detail in the corresponding embodiment of Fig. 6.
Wherein, further includes: the network information and attribute ratings model based on multiple wireless networks obtain the online data
Collection.Wherein, the acquisition process of Rating Model will be described in detail in the corresponding embodiment of Fig. 4.
In one embodiment, multiple attribute ratings packets of the multiple wireless network are determined based on the network identity
It includes: determining multiple attribute ratings of the multiple wireless network by off-line data collection based on the network identity.Can for example,
When user equipment is without network connection state, off-line data collection can be used to be identified, current multiple Wireless Communication Equipment with from
Wireless Communication Equipment in line data set is matched, and the attribute ratings provided from the background in offline packet can be used after matching,
Unmatching the wireless device can be arranged default fractional value.
In the embodiments of the present disclosure, online data collection and off-line data integrate can as same process under be calculated it is wireless
Network attribute scoring；Online data collection includes off-line data collection, and off-line data collection may be, for example, that online data is concentrated a small amount of and gone out
The relatively high Wireless Network attributes of existing frequency comment grading information, it is curable in a user device.
More specifically, when user, which is, network connection state, user equipment can arrive online data by network connection
Collection, takes the attribute ratings of wireless network；When user is no net connection status, user equipment connection less than online data collection,
Off-line data collection can only be matched from the storage of itself mobile phone, to obtain the attribute ratings of wireless network.
In S306, determine that multiple environment of the multiple wireless network score based on the signal strength.Wireless network
Equipment JA(junction ambient) is complicated and changeable, and Wireless Communication Equipment quality of connection is mainly influenced by Wireless Communication Equipment current demand signal height
With other transient changes.It is limited to Wireless Communication Equipment prompting message acquisition limitation and client reaction speed in current log table
It is required that etc., Wireless Communication Equipment current signal value is used as Wireless Communication Equipment JA(junction ambient) feature, calculates wireless network
Instantaneous signal score under equipment current environment.May be, for example: by Wireless Communication Equipment instantaneous signal value by 0-100 points uniform 6
Equal part obtains 1-6 points of signal score value, as the environment scoring under Wireless Communication Equipment current environment.
In S308, the multiple wireless network is determined by the multiple attribute ratings and the scoring of the multiple environment
Multiple quality of connection scorings.It can be for example, being scored based on historical status scoring and history environment determines attribute ratings weight and environment
Score weight；And pass through the scoring of the multiple attribute ratings, the attribute ratings weight and the multiple environment, the environment
Scoring weight determines multiple quality of connection scoring of the multiple wireless network.
In one embodiment, it is scored based on historical status scoring and history environment and determines that attribute ratings weight and environment are commented
Fraction includes: to be scored based on gray scale test mode and historical status scoring, history environment and determined attribute ratings weight and environment again
Score weight；And logic-based returns mode and historical status scoring, history environment score and determine attribute ratings weight and ring
Score weight in border.
The quality of wireless device quality of connection can also be by addition to being influenced by the long-term self attributes of the Wireless Communication Equipment
To the influence of current connection context.Therefore, in order to fully consider the factor of these two aspects, in the disclosure by the wireless network on backstage
The scoring of network device attribute and the scoring of Wireless Communication Equipment environment combine, and provide final Wireless Communication Equipment quality of connection etc.
Grade, carries out recommendation connection in predetermined APP.
In one embodiment, the attribute ratings that one group of weighted value respectively corresponds background server rule of thumb can be provided
The current environment scoring of the multiple Wireless Communication Equipment received with user equipment termination, then carries out a large amount of ABtest gray scale and surveys
Examination, to select optimal weighting specific gravity.
In one embodiment, also the selection of weight can be carried out by Logic Regression Models, to provide final wireless
The scoring of network equipment quality of connection.
In one embodiment, in the environment scoring of customer equipment part Wireless Communication Equipment calculates, when other are instantaneous
Environmental characteristic, such as current route requests access information collection after the completion of, can also according on line environmental requirement construct new model into
Row scoring.
In one embodiment, more specifically, the weighted value for being attribute ratings distribution is 0.3-0.5, the power of environment scoring
Weight values are assigned as 0.5-0.7, and then calculate quality of connection scoring.
In S310, wireless network connection recommendation is carried out based on the scoring of the multiple quality of connection.It can be according to multiple wireless
The network equipment corresponding quality of connection point being arranged successively multiple Wireless Communication Equipment from high to low, is recommended with being attached.
It is generated according to the wireless network connection recommended method of the disclosure according to the characteristic of Wireless Communication Equipment quality of connection
Determine that the algorithm of Wireless Communication Equipment quality of connection scoring, the algorithm can be executed by background server and user equipment end, backstage
Server section can be according to the Wireless Communication Equipment attribute ratings model and attribute of Wireless Communication Equipment long-term properties feature construction
Scoring and environment scoring weight calculation model.
At user equipment end, the computation model of a small-sized Wireless Communication Equipment current environment scoring can be constructed.Nothing
Line network connection recommended method comprehensively considered Wireless Communication Equipment it is long-term, static attribute and connection features and currently connect
Momentary surroundings feature under connecing, and most reasonable Wireless Communication Equipment quality of connection score etc. is obtained using optimal weighting specific gravity
Grade, so that it is determined that the display order of user equipment end Wireless Communication Equipment list, connects nothing for the high quality being calculated
The line network equipment is preferentially shown.
It will be clearly understood that the present disclosure describes how to form and use particular example, but the principle of the disclosure is not limited to
These exemplary any details.On the contrary, the introduction based on disclosure disclosure, these principles can be applied to many other
Embodiment.
Fig. 4 is a kind of flow chart of the wireless network connection recommended method shown according to another exemplary embodiment.Fig. 4 institute
The process shown is to the detailed of " network information based on multiple wireless networks obtains the online data collection with attribute ratings model "
Thin description.
As shown in figure 4, obtaining essential attribute log and the connection user behaviors log of multiple wireless networks in S402.Wirelessly
The attribute ratings model of the network equipment can be obtained by following steps.Firstly, training sample building need to meet positive negative sample can
Distinction, sample can train diversity and adequacy of capacity and sample behavioural characteristic etc..In order to realize These characteristics, this public affairs
The essential attribute log for obtaining multiple wireless networks and connection user behaviors log are opened, and to the connection user behaviors log of Wireless Communication Equipment
It is analyzed.
In S404, the corresponding essential attribute log of the multiple wireless network is distributed based on the connection user behaviors log
Into positive sample set and negative sample set.Power and online rate can be connected into for example, obtaining in the connection user behaviors log；
And it connects into power and the online rate by described and is assigned to the corresponding essential attribute log of the multiple wireless network
In positive sample set and negative sample set.
In Wireless Communication Equipment quality of connection scoring problem, the high Wireless Communication Equipment of power can will be connected into as just
Sample connects into the low Wireless Communication Equipment of power as negative sample.In Fig. 5 shown in (a), in order to make the area positive negative sample Geng You
Divide property, more representative, it is negative sample less than 0.2 that can define and connect into power greater than 0.9, which is positive sample,.Simultaneously as
It might not can surf the Internet after Wireless Communication Equipment successful connection, in order to find higher-quality Wireless Communication Equipment, the disclosure
In also introduce online rate, in Fig. 2 shown in (b), the Wireless Communication Equipment by online rate higher than 0.7 is considered high-quality wireless network
Network equipment, online rate are then considered on the one hand low quality Wireless Communication Equipment, this mode increase trained sample lower than 0.1
This, on the other hand also enriches the diversity of sample behavior.
After training sample determines, the feature of Wireless Communication Equipment quality of connection can be fully demonstrated in order to obtain, it can be from nothing
Line network equipment essential attribute log, which is connected with Wireless Communication Equipment in user behaviors log, extracts and is converted to totally 58 dimensional feature.?
In Wireless Communication Equipment essential attribute log, the changeless attributive character of Wireless Communication Equipment can extract, as wireless network is set
Standby type, commercial circle attribute, channel attribute and cryptographic properties etc..
Wherein, wireless network device type is primarily referred to as the Wireless Communication Equipment and whether belongs to authentication-type wireless network setting
It is standby, opening Wireless Communication Equipment, private wireless networks equipment and Wireless Communication Equipment encryption type etc..
Wherein, Wireless Communication Equipment commercial circle attribute mainly includes city, urban life level etc. where Wireless Communication Equipment
Grade, whether be popular city, whether be popular commercial circle etc..Wireless Communication Equipment channel attribute is mainly in terms of signal and routing
Consider, introduces the information such as channel information and routing brand, the route signal of Wireless Communication Equipment.
Wherein, Wireless Communication Equipment cryptographic properties are mainly Wireless Communication Equipment password number, password week interconversion rate, password
Month interconversion rate, password annual transform rate etc..
In Wireless Communication Equipment connection user behaviors log, time-consuming and Wireless Communication Equipment can be connected from Wireless Communication Equipment and connected
Set about in terms of being connected into function failure ratio two.In terms of connecting time-consuming, other than extracting Wireless Communication Equipment connection short time consumption, also
Time-consuming can be connected to Wireless Communication Equipment with Wireless Communication Equipment fundamental property according to the Wireless Communication Equipment Connection Time to beat
Point, as new feature.In terms of Wireless Communication Equipment successful connection fails ratio, power can be connected into from brand respectively, lost
Lose rate；Power, failure rate are connected into Wireless Communication Equipment house keeper；Deep bid connects into power, failure rate；Commercial circle successful connection
Rate, failure rate；Connect into power, failure rate week；The moon connects into power, failure rate；And hour grade connects into power scoring etc..
In one embodiment, user behaviors log and Wireless Communication Equipment essential attribute log sheet are connected from Wireless Communication Equipment
In be extracted sufficiently performance Wireless Communication Equipment quality of connection 58 dimensional features.These long-term properties values sufficiently present wireless network
The fixed attribute information of network equipment, to have a comprehensive evaluation to Wireless Communication Equipment quality of connection.
In S406, machine learning model is trained with true by the positive sample set and the negative sample set
The fixed attribute ratings model.Can include: determine the model structure and model depth of Random Forest model；Using Gini coefficient as
The loss function of the Random Forest model；And the positive sample set and the negative sample set input the institute that setting completed
It states and is trained in Random Forest model with the determination attribute ratings model.
In one embodiment, data training for example can be carried out by the random forest in machine learning model, it is random gloomy
Woods is one of machine learning common method, and precision of prediction is improved under the premise of operand does not increase significantly.Together
When, random forest is insensitive to multiple linear, and it is as a result more steady to missing data and nonequilibrium data, it can be pre- well
The effect for surveying up to thousands of a explanatory variables is known as current best one of algorithm.Therefore, the present invention is made using random forest
For the basic classification model of Wireless Communication Equipment mass fraction model, classified according to the static attribute of Wireless Communication Equipment.
The depth capacity that in experiment, using Gini coefficient as loss function, can be constructed 100 trees, and tree is arranged is 8.Experiment discovery
The model can be very good to distinguish high low quality Wireless Communication Equipment, and accuracy rate is up to 92% or more.Other machines can also be used
Device learning method carries out data training using other parameter settings in random forests algorithm, the application not as
Limit.
Positive negative sample building process according to the wireless network connection recommended method of the disclosure, in machine-learning process
In, Wireless Communication Equipment online rate is introduced, while increasing high-quality Wireless Communication Equipment, expands Wireless Communication Equipment inferior
Definition, to increase training sample and enrich the diversity of sample behavior.
Fig. 6 is a kind of flow chart of the wireless network connection recommended method shown according to another exemplary embodiment.Fig. 6 institute
The process shown is to the detailed of " network information based on multiple wireless networks obtains the online data collection with attribute ratings model "
Thin description.
In S602, multi-dimensional feature data set is extracted by the essential attribute log and connection user behaviors log of wireless network.
Multi-dimensional feature data set may be, for example, the 58 dimensional feature data acquisition systems enumerated in Fig. 4.
In S604, the corresponding multiple multi-dimensional feature data collection of multiple wireless networks are inputted into the attribute ratings mould
In type, multiple initial scores are obtained.
In S606, the multiple initial score and predetermined scoring section are compared to generate multiple attribute ratings.
In S608, the online data is generated by the corresponding attribute ratings of the network identity of multiple wireless networks
Collection.
In order to have one more accurately to score Wireless Communication Equipment quality of connection, the probability that can be exported according to model is carried out
Scoring divides.Normal distribution is the most common distribution in nature, in order to keep scoring more reasonable, points-scoring system can be made to meet just
State distribution.Box-Cox transformation is common a kind of data transformation in statistical modeling, is usually used in continuous response variable and is unsatisfactory for just
The case where state is distributed.Data after converting by Box-Cox can reduce unobservable error and prediction to a certain extent
The correlation of variable.
In one embodiment, can by the continuous probability output of attribute ratings model after Box-Cox is converted discretization,
To the cutting of attribute ratings numerical value be 6 sections after Box-Cox is converted using the mean value (μ) and variance (σ) of normal distribution: (- ∞,
+ 2 σ of μ], (μ+2 σ, μ+σ], (μ+σ, μ], (μ, μ+σ], (+2 σ of μ+σ, μ], (μ+2 σ ,+∞] Wireless Communication Equipment can be respectively corresponded
Mass fraction 1-6 points, to be ranked up to Wireless Communication Equipment.
According to the wireless network connection recommended method of the disclosure, in prediction probability discretization process, introduces Box-Cox and become
It changes, after the two disaggregated models output distribution based on Wireless Communication Equipment self attributes is first converted into normal distribution, then is divided
Number segmentation, to obtain more reasonable mass fraction.
The complicated multiplicity of Wireless Communication Equipment JA(junction ambient) variation, directly combines building mould by Wireless Communication Equipment self attributes
The mode of type is readily incorporated noise, reduces influence of the Wireless Communication Equipment self attributes to Wireless Communication Equipment quality of connection, from
And influence the accuracy of Wireless Communication Equipment quality of connection scoring.
According to the wireless network connection recommended method of the disclosure, for the algorithm of Wireless Communication Equipment quality of connection scoring,
The algorithm separates Wireless Communication Equipment self attributes feature and JA(junction ambient) feature, respectively in background server and user equipment
Model is established at end, and background server can be used to calculate the attribute ratings that Wireless Communication Equipment is long-term, static；User equipment end can
For calculating the scoring of the environment under Wireless Communication Equipment current environment.Finally, this two-part scoring is weighted and averaged, is obtained
To most reasonable Wireless Communication Equipment quality of connection fraction levels, and according to fraction levels in predetermined APP to multiple wireless
The network equipment is recommended.The wireless network connection recommended method of the disclosure not only avoids the noise that JA(junction ambient) may introduce
Problem, and comprehensively considered all factors for influencing Wireless Communication Equipment quality of connection, obtain a reasonable wireless network
Network equipment quality of connection score.
It will be appreciated by those skilled in the art that realizing that all or part of the steps of above-described embodiment is implemented as being executed by CPU
Computer program.When the computer program is executed by CPU, above-mentioned function defined by the above method that the disclosure provides is executed
Energy.The program can store in a kind of computer readable storage medium, which can be read-only memory, magnetic
Disk or CD etc..
Further, it should be noted that above-mentioned attached drawing is only the place according to included by the method for disclosure exemplary embodiment
Reason schematically illustrates, rather than limits purpose.It can be readily appreciated that above-mentioned processing shown in the drawings is not indicated or is limited at these
The time sequencing of reason.In addition, be also easy to understand, these processing, which can be, for example either synchronously or asynchronously to be executed in multiple modules.
Following is embodiment of the present disclosure, can be used for executing embodiments of the present disclosure.It is real for disclosure device
Undisclosed details in example is applied, embodiments of the present disclosure is please referred to.
Fig. 7 is a kind of block diagram of wireless network connection recommendation apparatus shown according to an exemplary embodiment.Wireless network
Connecting recommendation apparatus 70 includes: network information module 702, attribute ratings module 704, environment grading module 706, quality score mould
Block 708, and connection recommending module 710.
Network information module 702 is used to obtain the network information of multiple wireless networks, the network letter according to user instructions
Breath includes network identity and signal strength；User can for example send predetermined instruction on scheduled APP, predetermined instruction can for
Wireless Communication Equipment near family requests wireless network connection.
Attribute ratings module 704 is used to determine that multiple attributes of the multiple wireless network are commented based on the network identity
Point；It include: the multiple attribute ratings for determining the multiple wireless network by online data collection based on the network identity；It is based on
The network identity determines multiple attribute ratings of the multiple wireless network by off-line data collection.
Environment grading module 706 is used to determine that multiple environment of the multiple wireless network are commented based on the signal strength
Point；Wireless Communication Equipment JA(junction ambient) is complicated and changeable, and Wireless Communication Equipment quality of connection is mainly current by Wireless Communication Equipment
Signal height influences and other transient changes.It is limited to Wireless Communication Equipment prompting message acquisition limitation and visitor in current log table
Family end reaction speed requirement etc., it is special as Wireless Communication Equipment JA(junction ambient) to have can be used Wireless Communication Equipment current signal value
Sign calculates the instantaneous signal score under Wireless Communication Equipment current environment.May be, for example: by Wireless Communication Equipment instantaneous signal value
By 0-100 points of uniform 6 equal parts, 1-6 points of signal score value is obtained, as the environment scoring under Wireless Communication Equipment current environment.
Quality score module 708 is used for the multiple by the multiple attribute ratings and the scoring determination of the multiple environment
Multiple quality of connection of wireless network score；It can be for example, being scored based on historical status scoring and history environment determines attribute ratings
Weight and environment scoring weight；And it is commented by the multiple attribute ratings, the attribute ratings weight and the multiple environment
Divide, environment scoring weight determines that multiple quality of connection of the multiple wireless network score.
Recommending module 710 is connected to be used to carry out wireless network connection recommendation based on the scoring of the multiple quality of connection.It can press
According to the corresponding quality of connection point of multiple Wireless Communication Equipment being arranged successively multiple Wireless Communication Equipment from high to low, to carry out
Connection is recommended.
It is generated according to the wireless network connection recommendation apparatus of the disclosure according to the characteristic of Wireless Communication Equipment quality of connection
Determine that the algorithm of Wireless Communication Equipment quality of connection scoring, the algorithm can be executed by background server and user equipment end, backstage
Server section can be according to the Wireless Communication Equipment attribute ratings model and attribute of Wireless Communication Equipment long-term properties feature construction
Scoring and environment scoring weight calculation model.
At user equipment end, the computation model of a small-sized Wireless Communication Equipment current environment scoring can be constructed.Nothing
Line network connection recommendation apparatus comprehensively considered Wireless Communication Equipment it is long-term, static attribute and connection features and currently connect
Momentary surroundings feature under connecing, and most reasonable Wireless Communication Equipment quality of connection score etc. is obtained using optimal weighting specific gravity
Grade, so that it is determined that the display order of user equipment end Wireless Communication Equipment list, connects nothing for the high quality being calculated
The line network equipment is preferentially shown.
Fig. 8 is the block diagram of a kind of electronic equipment shown according to an exemplary embodiment.
The electronic equipment 800 of this embodiment according to the disclosure is described referring to Fig. 8.The electronics that Fig. 8 is shown
Equipment 800 is only an example, should not function to the embodiment of the present disclosure and use scope bring any restrictions.
As shown in figure 8, electronic equipment 800 is showed in the form of universal computing device.The component of electronic equipment 800 can wrap
It includes but is not limited to: at least one processing unit 810, at least one storage unit 820, (including the storage of the different system components of connection
Unit 820 and processing unit 810) bus 830, display unit 840 etc..
Wherein, the storage unit is stored with program code, and said program code can be held by the processing unit 810
Row, so that the processing unit 810 executes described in this specification above-mentioned electronic prescription circulation processing method part according to this
The step of disclosing various illustrative embodiments.For example, the processing unit 810 can be executed such as Fig. 3, Fig. 4, shown in Fig. 6
The step of.
The storage unit 820 may include the readable medium of volatile memory cell form, such as random access memory
Unit (RAM) 8201 and/or cache memory unit 8202 can further include read-only memory unit (ROM) 8203.
The storage unit 820 can also include program/practical work with one group of (at least one) program module 8205
Tool 8204, such program module 8205 includes but is not limited to: operating system, one or more application program, other programs
It may include the realization of network environment in module and program data, each of these examples or certain combination.
Bus 830 can be to indicate one of a few class bus structures or a variety of, including storage unit bus or storage
Cell controller, peripheral bus, graphics acceleration port, processing unit use any bus structures in a variety of bus structures
Local bus.
Electronic equipment 800 can also be with one or more external equipments 800 ' (such as keyboard, sensing equipment, bluetooth equipment
Deng) communication, can also be enabled a user to one or more equipment interact with the electronic equipment 200 communicate, and/or with make
Any equipment (such as the router, modulation /demodulation that the electronic equipment 800 can be communicated with one or more of the other calculating equipment
Device etc.) communication.This communication can be carried out by input/output (I/O) interface 850.Also, electronic equipment 800 can be with
By network adapter 860 and one or more network (such as local area network (LAN), wide area network (WAN) and/or public network,
Such as internet) communication.Network adapter 860 can be communicated by bus 830 with other modules of electronic equipment 800.It should
Understand, although not shown in the drawings, other hardware and/or software module can be used in conjunction with electronic equipment 800, including but unlimited
In: microcode, device driver, redundant processing unit, external disk drive array, RAID system, tape drive and number
According to backup storage system etc..
Through the above description of the embodiments, those skilled in the art is it can be readily appreciated that example described herein is implemented
Mode can also be realized by software realization in such a way that software is in conjunction with necessary hardware.Therefore, according to the disclosure
The technical solution of embodiment can be embodied in the form of software products, which can store non-volatile at one
Property storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in or network on, including some instructions are so that a calculating
Equipment (can be personal computer, server or network equipment etc.) executes the above method according to disclosure embodiment.
Fig. 9 schematically shows a kind of computer readable storage medium schematic diagram in disclosure exemplary embodiment.
Refering to what is shown in Fig. 9, describing the program product for realizing the above method according to embodiment of the present disclosure
900, can using portable compact disc read only memory (CD-ROM) and including program code, and can in terminal device,
Such as it is run on PC.However, the program product of the disclosure is without being limited thereto, in this document, readable storage medium storing program for executing can be with
To be any include or the tangible medium of storage program, the program can be commanded execution system, device or device use or
It is in connection.
Described program product can be using any combination of one or more readable mediums.Readable medium can be readable letter
Number medium or readable storage medium storing program for executing.Readable storage medium storing program for executing for example can be but be not limited to electricity, magnetic, optical, electromagnetic, infrared ray or
System, device or the device of semiconductor, or any above combination.The more specific example of readable storage medium storing program for executing is (non exhaustive
List) include: electrical connection with one or more conducting wires, portable disc, hard disk, random access memory (RAM), read-only
Memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read only memory
(CD-ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.
The computer readable storage medium may include in a base band or the data as the propagation of carrier wave a part are believed
Number, wherein carrying readable program code.The data-signal of this propagation can take various forms, including but not limited to electromagnetism
Signal, optical signal or above-mentioned any appropriate combination.Readable storage medium storing program for executing can also be any other than readable storage medium storing program for executing
Readable medium, the readable medium can send, propagate or transmit for by instruction execution system, device or device use or
Person's program in connection.The program code for including on readable storage medium storing program for executing can transmit with any suitable medium, packet
Include but be not limited to wireless, wired, optical cable, RF etc. or above-mentioned any appropriate combination.
Can with any combination of one or more programming languages come write for execute the disclosure operation program
Code, described program design language include object oriented program language-Java, C++ etc., further include conventional
Procedural programming language-such as " C " language or similar programming language.Program code can be fully in user
It calculates and executes in equipment, partly executes on a user device, being executed as an independent software package, partially in user's calculating
Upper side point is executed on a remote computing or is executed in remote computing device or server completely.It is being related to far
Journey calculates in the situation of equipment, and remote computing device can pass through the network of any kind, including local area network (LAN) or wide area network
(WAN), it is connected to user calculating equipment, or, it may be connected to external computing device (such as utilize ISP
To be connected by internet).
Above-mentioned computer-readable medium carries one or more program, when said one or multiple programs are by one
When the equipment executes, so that the computer-readable medium implements function such as: obtaining multiple wireless networks according to user instructions
The network information, the network information include network identity and signal strength；It is determined based on the network identity the multiple wireless
Multiple attribute ratings of network；Multiple environment scoring of the multiple wireless network is determined based on the signal strength；Pass through institute
It states multiple attribute ratings and the scoring of the multiple environment determines that multiple quality of connection of the multiple wireless network score；And base
It scores in the multiple quality of connection and carries out wireless network connection recommendation.
It will be appreciated by those skilled in the art that above-mentioned each module can be distributed in device according to the description of embodiment, it can also
Uniquely it is different from one or more devices of the present embodiment with carrying out corresponding change.The module of above-described embodiment can be merged into
One module, can also be further split into multiple submodule.
By the description of above embodiment, those skilled in the art is it can be readily appreciated that example embodiment described herein
It can also be realized in such a way that software is in conjunction with necessary hardware by software realization.Therefore, implemented according to the disclosure
The technical solution of example can be embodied in the form of software products, which can store in a non-volatile memories
In medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) or on network, including some instructions are so that a calculating equipment (can
To be personal computer, server, mobile terminal or network equipment etc.) it executes according to the method for the embodiment of the present disclosure.
In addition, structure shown by this specification Figure of description, ratio, size etc., only to cooperate specification institute
Disclosure, for skilled in the art realises that be not limited to the enforceable qualifications of the disclosure with reading, therefore
Do not have technical essential meaning, the modification of any structure, the change of proportionate relationship or the adjustment of size are not influencing the disclosure
Under the technical effect and achieved purpose that can be generated, it should all still fall in technology contents disclosed in the disclosure and obtain and can cover
In the range of.Meanwhile cited such as "upper" in this specification, " first ", " second " and " one " term, be also only and be convenient for
Narration is illustrated, rather than to limit the enforceable range of the disclosure, relativeness is altered or modified, without substantive change
Under technology contents, when being also considered as the enforceable scope of the disclosure.
Claims (13)
1. a kind of wireless network connection recommended method characterized by comprising
The network information of multiple wireless networks is obtained according to user instructions, and the network information includes that network identity and signal are strong
Degree；
Multiple attribute ratings of the multiple wireless network are determined based on the network identity；
Multiple environment scoring of the multiple wireless network is determined based on the signal strength；
Multiple quality of connection of the multiple wireless network are determined by the multiple attribute ratings and the scoring of the multiple environment
Scoring；And
It is scored based on the multiple quality of connection and carries out wireless network connection recommendation.
2. the method as described in claim 1, which is characterized in that determine the multiple wireless network based on the network identity
Multiple attribute ratings include:
Multiple attribute ratings of the multiple wireless network are determined by online data collection based on the network identity；And
Multiple attribute ratings of the multiple wireless network are determined by off-line data collection based on the network identity.
3. method according to claim 2, which is characterized in that passed through described in the determination of online data collection based on the network identity
Multiple attribute ratings of multiple wireless networks further include:
The network information and attribute ratings model based on multiple wireless networks obtain the online data collection.
4. method as claimed in claim 3, which is characterized in that further include:
Obtain essential attribute log and the connection user behaviors log of multiple wireless networks；
The corresponding essential attribute log of the multiple wireless network is assigned to positive sample set based on the connection user behaviors log
In negative sample set；And
Machine learning model is trained by the positive sample set and the negative sample set and is commented with the determination attribute
Sub-model.
5. method as claimed in claim 4, which is characterized in that be based on the connection user behaviors log for the multiple wireless network
Corresponding essential attribute log is assigned in positive sample set and negative sample set
It obtains in the connection user behaviors log and connects into power and online rate；And
It connects into power and the online rate by described and is assigned to the corresponding essential attribute log of the multiple wireless network
In positive sample set and negative sample set.
6. method as claimed in claim 4, which is characterized in that by the positive sample set and the negative sample set to machine
Device learning model is trained includes: with the determination attribute ratings model
Determine the model structure and model depth of Random Forest model；
Using Gini coefficient as the loss function of the Random Forest model；And
Be trained in the positive sample set and negative sample set input the Random Forest model that setting completed with
Determine the attribute ratings model.
7. method as claimed in claim 3, which is characterized in that the network information and attribute ratings mould based on multiple wireless networks
Type obtains the online data collection
Multi-dimensional feature data set is extracted by the essential attribute log and connection user behaviors log of wireless network；
The corresponding multiple multi-dimensional feature data collection of multiple wireless networks are inputted in the attribute ratings model, are obtained multiple
Initial score；
The multiple initial score and predetermined scoring section are compared to generate multiple attribute ratings；And
The online data collection is generated by the corresponding attribute ratings of the network identity of multiple wireless networks.
8. the method for claim 7, which is characterized in that carry out pair the multiple initial score and predetermined scoring section
Before to generate multiple attribute ratings further include:
The multiple initial score is subjected to the processing of broad sense power transformationization, generates multiple target scorings；
Calculate the mean value and variance of the multiple target scoring；And
The predetermined scoring section is generated by the mean value and the variance.
9. the method as described in claim 1, which is characterized in that scored by the multiple attribute ratings and the multiple environment
Determining that multiple quality of connection of the multiple wireless network score includes:
It is scored based on historical status scoring and history environment and determines attribute ratings weight and environment scoring weight；And
Pass through the scoring of the multiple attribute ratings, the attribute ratings weight and the multiple environment, environment scoring weight
Determine multiple quality of connection scoring of the multiple wireless network.
10. method as claimed in claim 9, which is characterized in that determine and belong to based on historical status scoring and history environment scoring
Property scoring weight and environment scoring weight include:
It is scored based on gray scale test mode and historical status scoring, history environment and determines attribute ratings weight and environment scoring power
Weight；And
Logic-based returns mode and historical status scoring, history environment score and determine attribute ratings weight and environment scoring power
Weight.
11. a kind of wireless network connection recommendation apparatus characterized by comprising
Network information module, for obtaining the network information of multiple wireless networks according to user instructions, the network information includes
Network identity and signal strength；
Attribute ratings module, for determining multiple attribute ratings of the multiple wireless network based on the network identity；
Environment grading module, for determining that multiple environment of the multiple wireless network score based on the signal strength；
Quality score module, for determining the multiple wireless network by the multiple attribute ratings and the scoring of the multiple environment
Multiple quality of connection of network score；And
Recommending module is connected, for carrying out wireless network connection recommendation based on the scoring of the multiple quality of connection.
12. a kind of electronic equipment characterized by comprising
One or more processors；
Storage device, for storing one or more programs；
When one or more of programs are executed by one or more of processors, so that one or more of processors are real
The now method as described in any in claim 1-10.
13. a kind of computer-readable medium, is stored thereon with computer program, which is characterized in that described program is held by processor
The method as described in any in claim 1-10 is realized when row.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910226151.1A CN109951859B (en) | 2019-03-25 | 2019-03-25 | Wireless network connection recommendation method and device, electronic equipment and readable medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910226151.1A CN109951859B (en) | 2019-03-25 | 2019-03-25 | Wireless network connection recommendation method and device, electronic equipment and readable medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109951859A true CN109951859A (en) | 2019-06-28 |
| CN109951859B CN109951859B (en) | 2021-08-20 |
Family
ID=67011470
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910226151.1A Active CN109951859B (en) | 2019-03-25 | 2019-03-25 | Wireless network connection recommendation method and device, electronic equipment and readable medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109951859B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112260862A (en) * | 2020-10-13 | 2021-01-22 | 北京锐安科技有限公司 | Network data quality determination method and device, electronic equipment and storage medium |
| CN114584607A (en) * | 2022-05-05 | 2022-06-03 | 施维智能计量系统服务(长沙)有限公司 | Communication connection establishing method and device, electronic equipment and readable storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2005062658A1 (en) * | 2003-12-15 | 2005-07-07 | Intel Corporation (A Corporation Of Delaware) | Handoff apparatus, systems, and methods |
| CN103262632A (en) * | 2010-06-04 | 2013-08-21 | 得克萨斯系统大学评议会 | Wireless communication methods, systems, and computer program products |
| CN103874132A (en) * | 2014-03-25 | 2014-06-18 | 北京工业大学 | Heterogeneous wireless network access selection method based on users |
| CN104301925A (en) * | 2014-10-22 | 2015-01-21 | 福建富士通信息软件有限公司 | Wireless WIFI network quality analysis evaluation method |
| CN106488539A (en) * | 2015-09-02 | 2017-03-08 | 腾讯科技（深圳）有限公司 | The processing method of WiFi resource and system in terminal |
| CN107563645A (en) * | 2017-09-04 | 2018-01-09 | 杭州云算信达数据技术有限公司 | A kind of Financial Risk Analysis method based on big data |
-
2019
- 2019-03-25 CN CN201910226151.1A patent/CN109951859B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2005062658A1 (en) * | 2003-12-15 | 2005-07-07 | Intel Corporation (A Corporation Of Delaware) | Handoff apparatus, systems, and methods |
| CN103262632A (en) * | 2010-06-04 | 2013-08-21 | 得克萨斯系统大学评议会 | Wireless communication methods, systems, and computer program products |
| CN103874132A (en) * | 2014-03-25 | 2014-06-18 | 北京工业大学 | Heterogeneous wireless network access selection method based on users |
| CN104301925A (en) * | 2014-10-22 | 2015-01-21 | 福建富士通信息软件有限公司 | Wireless WIFI network quality analysis evaluation method |
| CN106488539A (en) * | 2015-09-02 | 2017-03-08 | 腾讯科技（深圳）有限公司 | The processing method of WiFi resource and system in terminal |
| CN107563645A (en) * | 2017-09-04 | 2018-01-09 | 杭州云算信达数据技术有限公司 | A kind of Financial Risk Analysis method based on big data |
Non-Patent Citations (1)
| Title |
|---|
| 吴世江: "城市客运出行非线性效用离散选择模型研究", 《武汉理工大学学报》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112260862A (en) * | 2020-10-13 | 2021-01-22 | 北京锐安科技有限公司 | Network data quality determination method and device, electronic equipment and storage medium |
| WO2022078194A1 (en) * | 2020-10-13 | 2022-04-21 | 北京锐安科技有限公司 | Network data quality determining method and apparatus, electronic device, and storage medium |
| CN114584607A (en) * | 2022-05-05 | 2022-06-03 | 施维智能计量系统服务(长沙)有限公司 | Communication connection establishing method and device, electronic equipment and readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109951859B (en) | 2021-08-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Kazak et al. | Artificial intelligence in the tourism sphere | |
| CN107846350A (en) | A kind of method, computer-readable medium and the system of context-aware Internet chat | |
| CN110111139B (en) | Behavior prediction model generation method and device, electronic equipment and readable medium | |
| CN110569377A (en) | Media file processing method and device | |
| US20150206102A1 (en) | Human Resource Analytics Engine with Multiple Data Sources | |
| CN114787814A (en) | Reference resolution | |
| CN109344906A (en) | Consumer's risk classification method, device, medium and equipment based on machine learning | |
| CN111813910B (en) | Customer service problem updating method, customer service problem updating system, terminal equipment and computer storage medium | |
| CN112035549B (en) | Data mining method, device, computer equipment and storage medium | |
| CN113643103A (en) | Product recommendation method, device, equipment and storage medium based on user similarity | |
| US11074043B2 (en) | Automated script review utilizing crowdsourced inputs | |
| KR102250131B1 (en) | Method and apparatus for recommending supply companies to demand companies for inter-company transactions | |
| CN109690581A (en) | User guided system and method | |
| CN110009229A (en) | Supply chain management method, device, storage medium and equipment based on block chain | |
| CN110348897A (en) | Financial service product marketing method, apparatus and electronic equipment | |
| CN110443236A (en) | Text will put information extracting method and device after loan | |
| US20210110415A1 (en) | Enhanced survey information synthesis | |
| CN114036398A (en) | Content recommendation and ranking model training method, device, equipment and storage medium | |
| CN107896510A (en) | The quality business content mixed in social networks with the model of friend | |
| CN112861662A (en) | Target object behavior prediction method based on human face and interactive text and related equipment | |
| CN113420212A (en) | Deep feature learning-based recommendation method, device, equipment and storage medium | |
| CN109951859A (en) | Wireless network connection recommended method, device, electronic equipment and readable medium | |
| US10387566B2 (en) | Assisting with written communication style based on recipient dress style | |
| CN116843483A (en) | Vehicle insurance claim settlement method, device, computer equipment and storage medium | |
| KR20210048818A (en) | Apparatus and method for trade based on artificial intelligence using fintech |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |