CN105871707A - Resource recommendation method and system based on cloud computing - Google Patents
Resource recommendation method and system based on cloud computing Download PDFInfo
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- CN105871707A CN105871707A CN201610438614.7A CN201610438614A CN105871707A CN 105871707 A CN105871707 A CN 105871707A CN 201610438614 A CN201610438614 A CN 201610438614A CN 105871707 A CN105871707 A CN 105871707A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/52—Network services specially adapted for the location of the user terminal
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/21—Monitoring or handling of messages
- H04L51/214—Monitoring or handling of messages using selective forwarding
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
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Abstract
The invention provides a resource recommendation method and system based on cloud computing, and belongs to the technical field of communication. The resource recommendation method based on cloud computing comprises the following steps: receiving resource distribution request information sent by a user, wherein the resource distribution request information comprises user location information and a website type; according to a preset algorithm, computing heat weight of each website under the website type sent by a user, and sequencing the heat weights; according to tthe user location information, computing distance weight from the position of each website under the website type sent by the user to a user location, and sequencing the distance weights; according to the sequences of the heat weights and the distance weights, sending recommended website information to the user. The resource recommendation method can be used for bank recommendation, restaurant recommendation and the like.
Description
Technical field
The invention belongs to communication technical field, be specifically related to a kind of resource based on cloud computing
Recommend method and system.
Background technology
At present, the acquisition that needs to rank of the public place such as bank, restaurant and hospital is available
Resource, in order to improve queuing efficiency, provides a kind of system of queuing up in the prior art for this
System.
But existing queuing system, process user send resource allocation request time
Wait, send the time order and function order sequence of request according to user.General along with mobile terminal
And, the when that user applying for resource, the probability using mobile terminal is more and more higher, original
Only consider the algorithm of time, namely existing queuing system is only to apply for money according to user
User is ranked up by the sequencing in source, and not in view of user with asked
The information such as the distance between resource.Concrete, if some of which user initiates request money
The time in source is earlier, and now it puts in order the most earlier, but once
Close together followed by between user and this resource of resource request, the most very possible
Occur that user below first arrives resource location, but owing to sequence is rear, it is impossible to do
Reason business, now will cause subsequent user to need to wait that the long period just can handle relevant
Business, the most irrational arrangement resource is a kind of waste to resource equally, and etc.
Treat temporal waste.
Summary of the invention
The technical problem to be solved includes, exists for existing queuing system
The problems referred to above, it is provided that a kind of provide resource distribute rational resource based on cloud computing
Recommend method and system.
Solve the technology of the present invention problem and be employed technical scheme comprise that a kind of based on cloud computing
Resource recommendation method, including:
Receive the resource allocation request information that user is sent；Wherein, described resource distribution
Solicited message includes: customer position information, site classification；
According to preset algorithm, calculate each site under the site classification that user is sent
Temperature weight, and be ranked up；
According to customer position information, calculate each net under the site classification that user is sent
The position of point is to the distance weighting between customer location, and is ranked up；
According to temperature weight and the sequence of distance weighting, send the site recommended to user
Information.
Preferably, described according to preset algorithm, calculate the site class that user is sent
Not Xia the temperature weight of each site, and the step being ranked up includes:
According to formula:Calculate under the site classification that user is sent
Temperature weight p [i] of each site；Wherein, i represents number node；N is more than or equal to 1
Integer；Xi represents each site under the site classification that the user of real time record is sent
Clicked number of times；
The size of the temperature weighted value according to each site calculated is ranked up.
Preferably, described according to customer position information, calculate the net that user is sent
Under some classification, the position of each site is to the distance weighting between customer location, and arranges
The step of sequence specifically includes:
Described according to customer position information, calculate customer location respectively and sent to user
On-line shop's classification under each site between distance；
According to formula:Calculate under the site classification that user is sent
The position of each site is to the distance weighting d [i] between customer location；Wherein, i represents net
Point numbering；N is the integer more than or equal to 1；yiRepresent what customer location was sent to user
The distance between each site under on-line shop's classification；
Distance weighting value size according to each site calculated is ranked up.
Preferably, described according to temperature weight with the sequence of distance weighting, send out to user
The step sending recommended site information specifically includes:
According to formula: s [i]=p [i] * A1[i]+d[i]*A2[i], calculates the net that user is sent
Each site composite score s [i] under some classification；Wherein, number node is represented；N is for being more than
Integer equal to 1；P [i] represents the temperature of each site under the site classification that user is sent
Weight；D [i] represents under the site classification that user is sent the position of each site to user position
Distance weighting between putting；A1[i] represents the regulation weight of temperature weight；A2[i] represent away from
Regulation weight from weight；
According to each site composite score under the site classification that the user calculated is sent
Height carries out the sequence of site, and carries out the recommendation of site to user.
It may further be preferable that described A1[i] and described A2[i] is and manually regulates or be
It is automatically adjusted.
Solve the technology of the present invention problem and be employed technical scheme comprise that a kind of based on cloud computing
Resource recommendation system, including: receiving unit, the resource sent for receiving user is divided
Join solicited message；Wherein, described resource allocation request information includes: customer position information,
Site classification；
Temperature weight calculation unit, for according to preset algorithm, calculates user and is sent
Site classification under the temperature weight of each site, and be ranked up；
Distance weighting computing unit, for according to customer position information, calculates user institute
Under the site classification sent, the position of each site is to the distance weighting between customer location,
And be ranked up；
Resource supplying unit, for according to temperature weight and the sequence of distance weighting, Xiang Yong
Family sends the site information recommended.
Preferably, described temperature weight calculation unit specifically for,
According to formula:Calculate under the site classification that user is sent
Temperature weight p [i] of each site；Wherein, i represents number node；N is more than or equal to 1
Integer；Xi represents each site under the site classification that the user of real time record is sent
Clicked number of times；
The size of the temperature weighted value according to each site calculated is ranked up.
Preferably, described distance weighting computing unit specifically for,
Described according to customer position information, calculate customer location respectively and sent to user
On-line shop's classification under each site between distance；
According to formula:Calculate under the site classification that user is sent
The position of each site is to the distance weighting d [i] between customer location；Wherein, i represents net
Point numbering；N is the integer more than or equal to 1；yiRepresent what customer location was sent to user
The distance between each site under on-line shop's classification；
Distance weighting value size according to each site calculated is ranked up.
Preferably, described resource supplying unit specifically for,
According to formula: s [i]=p [i] * A1[i]+d[i]*A2[i], calculates the net that user is sent
Each site composite score s [i] under some classification；Wherein, number node is represented；N is for being more than
Integer equal to 1；P [i] represents the temperature of each site under the site classification that user is sent
Weight；D [i] represents under the site classification that user is sent the position of each site to user position
Distance weighting between putting；A1[i] represents the regulation weight of temperature weight；A2[i] represent away from
Regulation weight from weight；
According to each site composite score under the site classification that the user calculated is sent
Height carries out the sequence of site, and carries out the recommendation of site to user.
It may further be preferable that described A1[i] and described A2[i] is and manually regulates or be
It is automatically adjusted.
There is advantages that
The resource recommendation method based on cloud computing provided and system, sent out according to user
The resource allocation request information sent, calculates the distance weighting between user and site and net
Two factors of temperature weight of point, it is achieved Reasonable needs, rationally recommend corresponding for user
Site, thus improve the reasonability of resource distribution.
Accompanying drawing explanation
Fig. 1 is the stream of the resource recommendation method based on cloud computing of embodiments of the invention 1
Cheng Tu；
Fig. 2 is the knot of the resource recommendation system based on cloud computing of embodiments of the invention 2
Structure schematic diagram.
Detailed description of the invention
For making those skilled in the art be more fully understood that technical scheme, knot below
Close the drawings and specific embodiments the present invention is described in further detail.
Embodiment 1:
Shown in Fig. 1, the present embodiment provides a kind of resource recommendation side based on cloud computing
Method, the realization of this resource recommendation method is based on resource recommendation system, namely cloud management is put down
Information can be realized by wireless network mutual between platform, and customer mobile terminal.This reality
Execute the resource recommendation method of example, specifically include following steps:
The resource allocation request information that step one, reception user are sent；Wherein, described
Resource allocation request information includes: customer position information, site classification.
This step specifically includes: the data receipt unit in cloud management platform receives user and leads to
Cross the resource allocation request information that mobile terminal is sent；Wherein, resource allocation request letter
Breath includes customer position information, site classification, certainly can also include the transmission time.
Simultaneously, it should be appreciated that in the memory module of cloud management platform, be previously stored with net
The position of point, the affiliated site classification of each site, the clicked number of times in site.
Citing, user current location is Chongwenmen, it is desirable to going to site is industrial and commercial bank's (work
Site classification industrial and commercial bank class described in business bank), now user will pass through mobile terminal
Cloud management platform is given, accordingly by oneself current location information and site classification
The information that cloud management platform receives is then site classification: industrial and commercial bank's class；Customer location
Information: Chongwenmen.At this it should be noted that customer position information can be user's hands
Dynamic input is uploaded to cloud management platform, it is also possible to be that mobile terminal self poisoning goes out present bit
Confidence breath is automatically transmitted to cloud management platform.
Step 2, according to preset algorithm, calculate under the site classification that user is sent each
The temperature weight of individual site, and be ranked up.
This step specifically includes: first, and cloud management platform can be to cloud management when initializing
In the memory module of platform, each site under each site classification is numbered (in other words
It is to label), numbering i represents, 1≤i≤n；N is the integer more than or equal to 1.With
Time, cloud management platform also can real time record to update each site in memory module clicked
Number of times.Afterwards, formula is utilizedCalculate the site that user is sent
Temperature weight p [i] of each site under classification；Wherein, i represents number node；N is big
In the integer equal to 1；xiRepresent under the site classification that the user of real time record is sent
The number of times that each site is clicked.Temperature finally according to each site calculated
The size of weighted value is ranked up.
Step 3, according to customer position information, calculate the site classification that user is sent
The position of each site lower is to the distance weighting between customer location, and is ranked up.
This step specifically includes: first, cloud management platform according in its memory module in advance
The positional information of each site of storage, and the customer location that the user received sends
Information calculates between each site under customer location and its site classification sent
Distance.Afterwards, according to formula:Calculate the net that user is sent
Under some classification, the position of each site is to the distance weighting d [i] between customer location；Wherein,
I represents number node；N is the integer more than or equal to 1；yiRepresent customer location to user
The distance between each site under the on-line shop's classification sent.Finally according to being calculated
The size of distance weighting value of each site be ranked up.
Wherein, distance coefficient yiAccording to the size of actual range, become ladder distribution, specifically
Information is as follows:
disi≤500m,yi=1
500m<disi≤1000m,yi=-a × disi+b,a&b>0
Wherein, disiFor sending between the mobile terminal of resource allocation request and request site
Actual range.According to investigation, the distance between mobile terminal and request site is at 500 meters
Within, distance will not become reference factor for a user, say, that request site
Distance users 300 meters and distance users 400 meters do not interfere with the selection of user, so away from
It is 1 from factor.The ratio that distance factor declines between 500 meters to 1000 meters is 1000
Rice is above decline fast, this is because between 500 meters to 1000 meters, user along with away from
From increase can reduce the selection to site tendency.More than 1000 meters, although user is also
Can increasing to reduce the selection of site be inclined to along with distance, but will not arrive as 500 meters
As reducing between 1000 meters soon.Distance factor presents the trend successively decreased on the whole, i.e.
yi(0,500m]>yi(500m,1000m]>yi(1000m,+∞]。
At this it should be noted that the order of above-mentioned steps two and step 3 can be exchanged,
The most the order of step 2 and step 3 is not defined.
Step 4, sequence according to temperature weight and distance weighting, send to user and pushed away
The site information recommended.
This step specifically includes: cloud management platform is calculated according in step 2 and step 3
The temperature weight of each site and distance weighting under the site classification that the user gone out is sent
Sequence is comprehensively given a mark, to recommend corresponding site to user.Concrete, according to public affairs
Formula: s [i]=p [i] * A1[i]+d[i]*A2[i], calculates under the site classification that user is sent each
Individual site composite score s [i]；Wherein, number node is represented；N is whole more than or equal to 1
Number；P [i] represents the temperature weight of each site under the site classification that user is sent；d[i]
Represent under the site classification that user is sent the position of each site between customer location
Distance weighting；A1[i] represents the regulation weight of temperature weight；A2[i] represents distance weighting
Regulation weight；Each net under the site classification sent according to the user calculated afterwards
Point composite score height carries out the sequence of site, and carries out the recommendation of site to user.
Wherein, above-mentioned A1[i] and A2[i] is manually regulation or for being automatically adjusted, example
As said, if what user valued is site distance, want to select the site close to oneself, this
Time then can be by A2It is larger that [i] regulates, if the welcome journey of site that user values
Degree, then can be by A1It is larger that [i] regulates, and specifically can limit according to demands of individuals.
In sum, the resource recommendation method based on cloud computing provided in the present embodiment,
The resource allocation request information sent according to user, calculates between user and site
Two factors of the temperature weight of distance weighting and site, it is achieved Reasonable needs, close for user
Reason recommends corresponding site, thus improves the reasonability of resource distribution.
Embodiment 2:
As in figure 2 it is shown, the present embodiment provides a kind of resource recommendation system based on cloud computing,
It can use the resource recommendation method in embodiment 1 to recommend corresponding resource information to user.
The resource recommendation system of the present embodiment includes: receive unit, temperature weight calculation unit,
Distance weighting computing unit, resource supplying unit.
Wherein, unit is received for receiving the resource allocation request information that user is sent；
Wherein, described resource allocation request information includes: customer position information, site classification.
Concrete, the data receipt unit in cloud management platform receives user by mobile whole
The resource allocation request information that end is sent；Wherein, resource allocation request information comprises
There are customer position information, site classification, certainly can also include the transmission time.Meanwhile,
It should be appreciated that be previously stored with the position of site in the memory module of cloud management platform
Put, the affiliated site classification of each site, the clicked number of times in site.
Wherein, temperature weight calculation unit, for according to preset algorithm, calculates user institute
The temperature weight of each site under the site classification sent, and be ranked up.
Concrete, temperature weight calculation unit is specifically for can be to cloud management when initializing
In the memory module of platform, each site under each site classification is numbered (in other words
It is to label), numbering i represents, 1≤i≤n；N is the integer more than or equal to 1.With
Time, cloud management platform also can real time record to update each site in memory module clicked
Number of times.Afterwards, formula is utilizedCalculate the site that user is sent
Temperature weight p [i] of each site under classification；Wherein, i represents number node；N is big
In the integer equal to 1；xiRepresent under the site classification that the user of real time record is sent
The number of times that each site is clicked.Temperature finally according to each site calculated is weighed
The size of weight values is ranked up.
Wherein, distance weighting computing unit, for according to customer position information, calculates use
Under the site classification that family is sent, the position of each site is weighed to the distance between customer location
Weight, and be ranked up.
Concrete, distance weighting computing unit, first deposit in advance according in its memory module
The positional information of each site of storage, and the customer location letter that the user received sends
Breath calculate between each site under customer location and its site classification sent away from
From.Afterwards, according to formula:Calculate the site that user is sent
Under classification, the position of each site is to the distance weighting d [i] between customer location；Wherein, i
Represent number node；N is the integer more than or equal to 1；yiRepresent customer location to user institute
The distance between each site under the on-line shop's classification sent.Finally according to calculated
The size of the distance weighting value of each site is ranked up.
Wherein, distance coefficient yiAccording to the size of actual range, become ladder distribution, specifically
Information is as follows:
disi≤500m,yi=1
500m<disi≤1000m,yi=-a × disi+b,a&b>0
Wherein, disiFor sending between the mobile terminal of resource allocation request and request site
Actual range.According to investigation, the distance between mobile terminal and request site is at 500 meters
Within, distance will not become reference factor for a user, say, that request site
Distance users 300 meters and distance users 400 meters do not interfere with the selection of user, so away from
It is 1 from factor.The ratio that distance factor declines between 500 meters to 1000 meters is 1000
Rice is above decline fast, this is because between 500 meters to 1000 meters, user along with away from
From increase can reduce the selection to site tendency.More than 1000 meters, although user is also
Can increasing to reduce the selection of site be inclined to along with distance, but will not arrive as 500 meters
As reducing between 1000 meters soon.Distance factor presents the trend successively decreased on the whole, i.e.
yi(0,500m]>yi(500m,1000m]>yi(1000m,+∞]。
Wherein, resource supplying unit, for being calculated according to temperature weight calculation unit
Temperature weight and the sequence of distance weighting that calculated of distance weighting computing unit, to
User sends the site information recommended.
Concrete, that resource supplying unit is sent according to the user calculated site class
Xia the temperature weight of each site and the sequence of distance weighting comprehensively not give a mark, with to
User recommends corresponding site.Concrete, according to formula: s [i]=p [i] * A1[i]+d[i]*A2[i],
Calculate each site composite score s [i] under the site classification that user is sent；Wherein, generation
Table number node；N is the integer more than or equal to 1；P [i] represents the site that user is sent
The temperature weight of each site under classification；D [i] represents under the site classification that user is sent each
The position of individual site is to the distance weighting between customer location；A1[i] represents temperature weight
Regulation weight；A2[i] represents the regulation weight of distance weighting；Afterwards according to being calculated
Under the site classification that user is sent, each site composite score height carries out the row of site
Sequence, and the recommendation of site is carried out to user.
Wherein, above-mentioned A1[i] and A2[i] is manually regulation or for being automatically adjusted, example
As said, if what user valued is site distance, want to select the site close to oneself, this
Time then can be by A2It is larger that [i] regulates, if the welcome journey of site that user values
Degree, then can be by A1It is larger that [i] regulates, and specifically can limit according to demands of individuals.
In sum, the resource recommendation system based on cloud computing provided in the present embodiment,
The resource allocation request information sent according to user, calculates between user and site
Two factors of the temperature weight of distance weighting and site, it is achieved Reasonable needs, close for user
Reason recommends corresponding site, thus improves the reasonability of resource distribution.
It is understood that the principle that embodiment of above is intended to be merely illustrative of the present
And the illustrative embodiments used, but the invention is not limited in this.For ability
For those of ordinary skill in territory, in the situation without departing from spirit and substance of the present invention
Under, various modification and improvement can be made, these modification and improvement are also considered as the present invention's
Protection domain.
Claims (10)
1. a resource recommendation method based on cloud computing, it is characterised in that including:
Receive the resource allocation request information that user is sent；Wherein, described resource distribution
Solicited message includes: customer position information, site classification；
According to preset algorithm, calculate each site under the site classification that user is sent
Temperature weight, and be ranked up；
According to customer position information, calculate each net under the site classification that user is sent
The position of point is to the distance weighting between customer location, and is ranked up；
According to temperature weight and the sequence of distance weighting, send the site recommended to user
Information.
Resource recommendation method based on cloud computing the most according to claim 1, it is special
Levy and be, described according to preset algorithm, calculate under the site classification that user is sent each
The temperature weight of individual site, and the step being ranked up includes:
According to formula:Calculate under the site classification that user is sent
Temperature weight p [i] of each site；Wherein, i represents number node；N is more than or equal to 1
Integer；xiRepresent each site under the site classification that the user of real time record is sent
Clicked number of times；
The size of the temperature weighted value according to each site calculated is ranked up.
Resource recommendation method based on cloud computing the most according to claim 1, it is special
Levy and be, described according to customer position information, calculate the site classification that user is sent
The position of each site lower is to the distance weighting between customer location, and the step being ranked up
Suddenly specifically include:
Described according to customer position information, calculate customer location respectively and sent to user
On-line shop's classification under each site between distance；
According to formula:Calculate under the site classification that user is sent
The position of each site is to the distance weighting d [i] between customer location；Wherein, i represents net
Point numbering；N is the integer more than or equal to 1；yiRepresent what customer location was sent to user
The distance between each site under on-line shop's classification；
Distance weighting value size according to each site calculated is ranked up.
Resource recommendation method based on cloud computing the most according to claim 1, it is special
Levy and be, described according to temperature weight with the sequence of distance weighting, send to user and pushed away
The step of the site information recommended specifically includes:
According to formula: s [i]=p [i] * A1[i]+d[i]*A2[i], calculates the net that user is sent
Each site composite score s [i] under some classification；Wherein, number node is represented；N is for being more than
Integer equal to 1；P [i] represents the temperature of each site under the site classification that user is sent
Weight；D [i] represents under the site classification that user is sent the position of each site to user position
Distance weighting between putting；A1[i] represents the regulation weight of temperature weight；A2[i] represent away from
Regulation weight from weight；
According to each site composite score under the site classification that the user calculated is sent
Height carries out the sequence of site, and carries out the recommendation of site to user.
Resource recommendation method based on cloud computing the most according to claim 4, it is special
Levy and be, described A1[i] and described A2[i] is manually regulation or for being automatically adjusted.
6. a resource recommendation system based on cloud computing, it is characterised in that including:
Receive unit, for receiving the resource allocation request information that user is sent；Wherein,
Described resource allocation request information includes: customer position information, site classification；
Temperature weight calculation unit, for according to preset algorithm, calculates user and is sent
Site classification under the temperature weight of each site, and be ranked up；
Distance weighting computing unit, for according to customer position information, calculates user institute
Under the site classification sent, the position of each site is to the distance weighting between customer location,
And be ranked up；
Resource supplying unit, for according to temperature weight and the sequence of distance weighting, Xiang Yong
Family sends the site information recommended.
Resource recommendation system based on cloud computing the most according to claim 6, it is special
Levy and be, described temperature weight calculation unit specifically for,
According to formula:Calculate under the site classification that user is sent
Temperature weight p [i] of each site；Wherein, i represents number node；N is more than or equal to 1
Integer；xiRepresent each site under the site classification that the user of real time record is sent
Clicked number of times；
The size of the temperature weighted value according to each site calculated is ranked up.
Resource recommendation system based on cloud computing the most according to claim 6, it is special
Levy and be, described distance weighting computing unit specifically for,
Described according to customer position information, calculate customer location respectively and sent to user
On-line shop's classification under each site between distance；
According to formula:Calculate under the site classification that user is sent
The position of each site is to the distance weighting d [i] between customer location；Wherein, i represents net
Point numbering；N is the integer more than or equal to 1；yiRepresent what customer location was sent to user
The distance between each site under on-line shop's classification；
Distance weighting value size according to each site calculated is ranked up.
Resource recommendation system based on cloud computing the most according to claim 6, it is special
Levy and be, described resource supplying unit specifically for,
According to formula: s [i]=p [i] * A1[i]+d[i]*A2[i], calculates the net that user is sent
Each site composite score s [i] under some classification；Wherein, number node is represented；N is for being more than
Integer equal to 1；P [i] represents the temperature of each site under the site classification that user is sent
Weight；D [i] represents under the site classification that user is sent the position of each site to user position
Distance weighting between putting；A1[i] represents the regulation weight of temperature weight；A2[i] represent away from
Regulation weight from weight；
According to each site composite score under the site classification that the user calculated is sent
Height carries out the sequence of site, and carries out the recommendation of site to user.
Resource recommendation system based on cloud computing the most according to claim 9, its
It is characterised by, described A1[i] and described A2[i] is manually regulation or for being automatically adjusted.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106779181A (en) * | 2016-11-29 | 2017-05-31 | 深圳北航新兴产业技术研究院 | Method is recommended by a kind of medical institutions based on linear regression factor Non-negative Matrix Factorization model |
| CN108550046A (en) * | 2018-03-07 | 2018-09-18 | 阿里巴巴集团控股有限公司 | A kind of resource and market recommendation method, apparatus and electronic equipment |
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