CN107169801A - Shop incidence relation acquisition methods, system, storage medium and mobile terminal - Google Patents
Shop incidence relation acquisition methods, system, storage medium and mobile terminal Download PDFInfo
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- CN107169801A CN107169801A CN201710363753.2A CN201710363753A CN107169801A CN 107169801 A CN107169801 A CN 107169801A CN 201710363753 A CN201710363753 A CN 201710363753A CN 107169801 A CN107169801 A CN 107169801A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F16/00 and subgroups
- G06F2216/03—Data mining
Abstract
The present invention provides a kind of shop incidence relation acquisition methods, system, storage medium and mobile terminal, and applied to commercial operation place, the shop incidence relation acquisition methods comprise the following steps：The parameter of strolling about of the customer in collection visiting commercial operation place Nei Ge shops in preset time period；Based on the parameter of strolling about, it is determined that the weight of the parameter of strolling about and according to the scoring of strolling about in each shop of Weight Acquisition customer correspondence；The similarity between shop is obtained according to the scoring of strolling about in each shop of customer's correspondence；Visualize the similarity between shop.The present invention can be arranged in pairs or groups for the industry situation in shopping center, association marketing program provides foundation, and decision recommendation is provided for the operation in market.
Description
Technical field
The invention belongs to commercial operation analysis technical field, more particularly to a kind of shop incidence relation acquisition methods, it is
System, storage medium and mobile terminal.
Background technology
Correlation rule (Association Rule) was proposed by Rakesh Agrawal et al. in 1993, was mainly used in hair
Association or contact in existing data set between item collection.Wherein Apriori algorithm is a kind of most influential Mining Boolean Association Rules
The algorithm of frequent item set, is used for the shopping basket of supermarket, through being generalized to many fields earliest.
In relation between brand shop under application Apriori algorithm excavates line, the relation between customer and brand is 0-1 numbers
According to (whether visiting), more accurately incidence relation depends on the judgement of more various dimensions, such as amount of consumption, trip actually between brand shop
Stroll time, visiting frequency etc..
Therefore, a kind of shop incidence relation acquisition methods, system, storage medium and mobile terminal how to be provided how
Various dimensions, more accurately judge to excavate the relation under line between brand shop, it is real with urgently to be resolved hurrily as those skilled in the art
Technical problem.
The content of the invention
The shortcoming of prior art in view of the above, it is an object of the invention to provide a kind of shop incidence relation acquisition side
Method, system, storage medium and mobile terminal, for solving accurately judge in the prior art asking for the relation between shop
Topic.
In order to achieve the above objects and other related objects, one aspect of the present invention provides a kind of shop incidence relation acquisition side
Method, applied to commercial operation place, the shop incidence relation acquisition methods comprise the following steps：Adopted in preset time period
The parameter of strolling about of the customer in collection visiting commercial operation place Nei Ge shops；Based on the parameter of strolling about, it is determined that the parameter of strolling about
Weight and according to the scoring of strolling about in each shop of Weight Acquisition customer correspondence；According to the scoring of strolling about in each shop of customer's correspondence
Obtain the similarity between shop；Visualize the similarity between shop.
In one embodiment of the invention, the parameter of strolling about is included in customer in predetermined amount of time and transported into the business
Seek the frequency in place Nei Ge shops, customer passes by the frequency in the commercial operation place Nei Ge shops and customer transports in the business
Seek the duration of strolling about that is averaged in place Nei Ge shops.
In one embodiment of the invention, shop is obtained according to the cosine similarity of the scoring of strolling about in each shop of customer's correspondence
Between similarity.
In one embodiment of the invention, the similarity between the shop is：
X=(x1,x2,...,xn)T；
Y=(y1,y2,...,yn)T；
Wherein：D (X, Y) is the similarity between shop X and shop Y, and X is score value vector of the customer to shop X, and Y is
Customer is vectorial to shop Y score value, | | X | | it is score value absolute value of a vector of the customer to shop X, | | Y | | it is customer couple
Shop Y score value absolute value of a vector, x1,x2,...,xnRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop
Spread X score value, y1,y2,...,ynRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop Y score value, T
For transposition symbol.
In one embodiment of the invention, the similarity between shop is visualized by network associate diagram form.
Another aspect of the present invention provides a kind of shop incidence relation and obtains system, applied to commercial operation place, the shop
Paving incidence relation, which obtains system, to be included：Stroll about parameter collection module, for the collection visiting commercial operation in preset time period
The parameter of strolling about of the customer in place Nei Ge shops；Weight grading module, for based on the parameter of strolling about, it is determined that the ginseng of strolling about
Several weight and according to the scoring of strolling about in each shop of Weight Acquisition customer correspondence；Similarity acquisition module, for according to Gu
The scoring of strolling about in each shop of visitor's correspondence obtains the similarity between shop；Similarity visualization model, for visualizing between shop
Similarity.
In one embodiment of the invention, the parameter of strolling about is included in customer in predetermined amount of time and transported into the business
Seek the frequency in place Nei Ge shops, customer passes by the frequency in the commercial operation place Nei Ge shops and customer transports in the business
Seek the duration of strolling about that is averaged in place Nei Ge shops.
In one embodiment of the invention, the similarity acquisition module is according to the scoring of strolling about in each shop of customer's correspondence
Cosine similarity obtains the similarity between shop.
In one embodiment of the invention, the similarity between the shop is：
X=(x1,x2,...,xn)T；
Y=(y1,y2,...,yn)T；
Wherein：D (X, Y) is the similarity between shop X and shop Y, and X is score value vector of the customer to shop X, and Y is
Customer is vectorial to shop Y score value, | | X | | it is score value absolute value of a vector of the customer to shop X, | | Y | | it is customer couple
Shop Y score value absolute value of a vector, x1,x2,...,xnRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop
Spread X score value, y1,y2,...,ynRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop Y score value, T
For transposition symbol.
In one embodiment of the invention, the similarity visualization model visualizes shop by network associate diagram form
Between similarity.
Another aspect of the invention provides a kind of computer-readable recording medium, is stored thereon with computer program, the program
The step in method as described above is realized when being executed by processor.
Another aspect of the invention provides a kind of mobile terminal, including processor and memory, and the memory storage has journey
Sequence is instructed, it is characterised in that：The step in method as described above is realized in the processor operation program instruction.
As described above, shop incidence relation acquisition methods, system, storage medium and the mobile terminal of the present invention, have
Following beneficial effect：
The data of behavior of the invention of being strolled about based on the consumer collected, to the brand for the customer that visited in the cycle of shopping center
Shop preference carries out the incidence relation between data mining analysis, research shop, can effectively be lifted and weigh the degree of association between shop
The degree of accuracy, provides foundation for the industry situation collocation in shopping center, association marketing program, decision recommendation is provided for the operation in market.
Brief description of the drawings
Fig. 1 is shown as schematic flow sheet of the shop incidence relation acquisition methods of the present invention in an embodiment.
Fig. 2 is shown as implementation procedure schematic diagram of the shop incidence relation acquisition methods of the present invention in an embodiment.
Fig. 3 is shown as the related network figure in the shop incidence relation acquisition methods of the present invention.
The shop incidence relation that Fig. 4 is shown as the present invention obtains theory structure schematic diagram of the system in an embodiment.
Component label instructions
100 shop incidence relations obtain system
101 stroll about parameter collection module
102 weight grading modules
103 similarity acquisition modules
104 similarity visualization models
S101~S104 steps
Embodiment
Illustrate embodiments of the present invention below by way of specific instantiation, those skilled in the art can be by this specification
Disclosed content understands other advantages and effect of the present invention easily.The present invention can also pass through specific realities different in addition
The mode of applying is embodied or practiced, the various details in this specification can also based on different viewpoints with application, without departing from
Various modifications or alterations are carried out under the spirit of the present invention.It should be noted that, in the case where not conflicting, following examples and implementation
Feature in example can be mutually combined.
It should be noted that the diagram provided in following examples only illustrates the basic structure of the present invention in a schematic way
Think, then in schema only display with relevant component in the present invention rather than according to component count, shape and the size during actual implement
Draw, it is actual when implementing, and kenel, quantity and the ratio of each component can be a kind of random change, and its assembly layout kenel
It is likely more complexity.
The purpose of the present embodiment is to provide a kind of shop incidence relation acquisition methods, system, storage medium and movement
Terminal, the problem of can not accurately judging the relation between shop in the prior art for solution.It is described in detail below of the invention
Shop incidence relation acquisition methods, system, the principle and embodiment of storage medium and mobile terminal, make people in the art
Member does not need creative work to be shop incidence relation acquisition methods, system, storage medium and the movement for being appreciated that the present invention
Terminal.
The present embodiment weighted association rules algorithm new by studying, the number for behavior of being strolled about based on the consumer collected
According to the brand shop preference to the customer that visited in the cycle of shopping center carries out data mining analysis, and the association studied between shop is closed
System, provides foundation for the industry situation collocation in shopping center, association marketing program, decision recommendation is provided for the operation in market.New calculation
Method improves Apriori algorithm, and whether the relation between customer and market is directed not only to visit, can also be in time of strolling about, visiting
Comprehensive assessment is carried out in the dimensions such as the frequency, based on the data basis of more various dimensions, is conducive to being lifted the accurate of the degree of association between shop
Degree.
The present embodiment is specifically described below.
Embodiment one
The present embodiment provides a kind of shop incidence relation acquisition methods, applied to commercial operation place, as shown in figure 1, institute
Shop incidence relation acquisition methods are stated to comprise the following steps：
S101, the parameter of strolling about of the customer in collection visiting commercial operation place Nei Ge shops in preset time period.
S102, based on the parameter of strolling about, it is determined that the weight of the parameter of strolling about and according to the Weight Acquisition customer couple
Answer the scoring of strolling about in each shop.
S103, the similarity between shop is obtained according to the scoring of strolling about in each shop of customer's correspondence.
Similarity between S104, visualization shop.
It is described in detail below with reference to the shop incidence relation acquisition methods that Fig. 2 is provided the present embodiment.
Shop incidence relation acquisition methods described in the present embodiment are applied to commercial operation place, for example, market, bar,
Supermarket etc..Department stores are used in the present embodiment selection.
S101, the parameter of strolling about of the customer in collection visiting commercial operation place Nei Ge shops in preset time period.
In the present embodiment, the parameter of strolling about be included in predetermined amount of time (in the present embodiment, the predetermined amount of time
T is half a year) interior customer enters the frequency (Frequency/ times) in the commercial operation place Nei Ge shops, customer and passes by the business
Industry operation place Nei Ge shops the frequency and customer the commercial operation place Nei Ge shops the duration of strolling about that is averaged
(Length/ hours).The present invention's strolls about parameter on the basis of original whether visit, and has increased duration of strolling about, visiting frequency newly
The degree of accuracy of the degree of association between shop is weighed in two dimensions of rate, lifting.
S102, based on the parameter of strolling about, it is determined that the weight of the parameter of strolling about and according to the Weight Acquisition customer couple
Answer the scoring of strolling about in each shop.
In the present embodiment, the code of points of parameter it is determined that each dimension is strolled about, it is determined that customer enters within a predetermined period of time
Enter the frequency and customer that the frequency in the commercial operation place Nei Ge shops, customer pass by the commercial operation place Nei Ge shops
The duration of strolling about that is averaged in the commercial operation place Nei Ge shops.For example, the score that customer enters shop with crossing shop 1 time is respectively 2
Point, 0.5 point.
In the present embodiment, the frequency that the customer calculated using Information Entropy enters the commercial operation place Nei Ge shops is weighed
Pass through H againF1Represent, the frequency weight that the customer calculated using Information Entropy passes by the commercial operation place Nei Ge shops passes through
HF2Represent, be averaged stroll about duration weight H of the customer calculated using Information Entropy in the commercial operation place Nei Ge shopsLTable
Show.In the present embodiment, the weight of some parameter in parameter of strolling about is bigger, illustrates that influence of the parameter to overall merit is got over
Greatly.
Wherein, HF1=∑ P (F) logP (F), P (F) enter each in the commercial operation place by customer in predetermined amount of time
The frequency composition in shop.
HF2=∑ P (R) logP (R), P (R) pass by the commercial operation place Nei Ge shops by customer within a predetermined period of time
The frequency composition of paving.
HL=∑ P (L) logP (L), P (L) are by customer within a predetermined period of time in the commercial operation place Nei Ge shops
Be averaged stroll about duration composition.
The H obtained by the calculating of lot of experimental data, the present embodimentF1=0.4, HF2=0.3, HL=0.3.
S103, the similarity between shop is obtained according to the scoring of strolling about in each shop of customer's correspondence.
The core of shop incidence relation acquisition methods is to seek the similarity between brand shop in the present embodiment, according to classics
Similarity between the principle of collaborative filtering, brand shop is weighed using cosine similarity.
Similarity between brand shop is maintained by the customer base to shop, based on the recommendation based on article in collaborative filtering
Algorithmic rule, the similarity between brand shop is weighed by cosine similarity.
In the present embodiment, specifically, shop is obtained according to the cosine similarity of the scoring of strolling about in each shop of customer's correspondence
Between similarity.
Wherein, the similarity between the shop is：
X=(x1,x2,...,xn)T；
Y=(y1,y2,...,yn)T；
Wherein：D (X, Y) is the similarity between shop X and shop Y, and X is score value vector of the customer to shop X, and Y is
Customer is vectorial to shop Y score value, | | X | | it is score value absolute value of a vector of the customer to shop X, | | Y | | it is customer couple
Shop Y score value absolute value of a vector, x1,x2,...,xnRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop
Spread X score value, y1,y2,...,ynRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop Y score value, T
For transposition symbol.
Similarity between S104, visualization shop.
Specifically, as shown in figure 3, in the present embodiment, the similarity between shop is visualized by network associate diagram form.
The present embodiment also provides a kind of computer-readable recording medium, is stored thereon with computer program, and the program is located
Reason device realizes the step in method as described above when performing.
The present embodiment also provides a kind of mobile terminal, including processor and memory, and the memory storage has program to refer to
Order, it is characterised in that：The step in method as described above is realized in the processor operation program instruction.
Embodiment two
The present embodiment provides a kind of shop incidence relation and obtains system, applied to commercial operation place, for example, market, wine
, supermarket etc..Referring to Fig. 4, being shown as shop incidence relation obtains theory structure signal of the system 100 in an embodiment
Figure.Include as shown in figure 4, the shop incidence relation obtains system 100：Stroll about parameter collection module 101, weight grading module
102, similarity acquisition module 103 and similarity visualization model 104.
In the present embodiment, the parameter collection module 101 of strolling about is used for the collection visiting business in preset time period
Run the parameter of strolling about of the customer in place Nei Ge shops.
In the present embodiment, the parameter of strolling about be included in predetermined amount of time (in the present embodiment, the predetermined amount of time
T is half a year) interior customer enters the frequency (Frequency/ times) in the commercial operation place Nei Ge shops, customer and passes by the business
Industry operation place Nei Ge shops the frequency and customer the commercial operation place Nei Ge shops the duration of strolling about that is averaged
(Length/ hours).The present invention's strolls about parameter on the basis of original whether visit, and has increased duration of strolling about, visiting frequency newly
The degree of accuracy of the degree of association between shop is weighed in two dimensions of rate, lifting.
In the present embodiment, the weight grading module 102 is used for based on the parameter of strolling about, it is determined that the parameter of strolling about
Weight and according to the scoring of strolling about in each shop of Weight Acquisition customer correspondence.
In the present embodiment, the code of points of parameter it is determined that each dimension is strolled about, it is determined that customer enters within a predetermined period of time
Enter the frequency and customer that the frequency in the commercial operation place Nei Ge shops, customer pass by the commercial operation place Nei Ge shops
The duration of strolling about that is averaged in the commercial operation place Nei Ge shops.For example, the score that customer enters shop with crossing shop 1 time is respectively 2
Point, 0.5 point.
In the present embodiment, the frequency that the customer calculated using Information Entropy enters the commercial operation place Nei Ge shops is weighed
Pass through H againF1Represent, the frequency weight that the customer calculated using Information Entropy passes by the commercial operation place Nei Ge shops passes through
HF2Represent, be averaged stroll about duration weight H of the customer calculated using Information Entropy in the commercial operation place Nei Ge shopsLTable
Show.In the present embodiment, the weight of some parameter in parameter of strolling about is bigger, illustrates that influence of the parameter to overall merit is got over
Greatly.
Wherein, HF1=∑ P (F) logP (F), P (F) enter each in the commercial operation place by customer in predetermined amount of time
The frequency composition in shop.
HF2=∑ P (R) logP (R), P (R) pass by the commercial operation place Nei Ge shops by customer within a predetermined period of time
The frequency composition of paving.
HL=∑ P (L) logP (L), P (L) are by customer within a predetermined period of time in the commercial operation place Nei Ge shops
Be averaged stroll about duration composition.
The H obtained by the calculating of lot of experimental data, the present embodimentF1=0.4, HF2=0.3, HL=0.3.
In the present embodiment, the similarity acquisition module 103 is used to be obtained according to the scoring of strolling about in each shop of customer's correspondence
Take the similarity between shop.
The core of shop incidence relation acquisition methods is to seek the similarity between brand shop in the present embodiment, according to classics
Similarity between the principle of collaborative filtering, brand shop is weighed using cosine similarity.
Similarity between brand shop is maintained by the customer base to shop, based on the recommendation based on article in collaborative filtering
Algorithmic rule, the similarity between brand shop is weighed by cosine similarity.
In the present embodiment, specifically, the similarity acquisition module 103 corresponds to the scoring of strolling about in each shop according to customer
Cosine similarity obtain shop between similarity.
Wherein, the similarity between the shop is：
X=(x1,x2,...,xn)T；
Y=(y1,y2,...,yn)T；
Wherein：D (X, Y) is the similarity between shop X and shop Y, and X is score value vector of the customer to shop X, and Y is
Customer is vectorial to shop Y score value, | | X | | it is score value absolute value of a vector of the customer to shop X, | | Y | | it is customer couple
Shop Y score value absolute value of a vector, x1,x2,...,xnRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop
Spread X score value, y1,y2,...,ynRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop Y score value, T
For transposition symbol.
In the present embodiment, the similarity visualization model 104 is used to visualize the similarity between shop.
Specifically, as shown in figure 3, in the present embodiment, the similarity acquisition module 103 is according to each shop of customer's correspondence
Scoring of strolling about cosine similarity obtain shop between similarity.
In summary, the data of behavior of the invention of being strolled about based on the consumer collected, to being visited in the cycle of shopping center
The brand shop preference of customer carries out the incidence relation between data mining analysis, research shop, can effectively lift measurement shop
Between the degree of association the degree of accuracy, provide foundation for the industry situation collocation in shopping center, association marketing program, provide and determine for the operation in market
Plan is advised.So, the present invention effectively overcomes various shortcoming of the prior art and has high industrial utilization.
The above-described embodiments merely illustrate the principles and effects of the present invention, not for the limitation present invention.It is any ripe
Know the personage of this technology all can carry out modifications and changes under the spirit and scope without prejudice to the present invention to above-described embodiment.Cause
This, those of ordinary skill in the art is complete without departing from disclosed spirit and institute under technological thought such as
Into all equivalent modifications or change, should by the present invention claim be covered.
Claims (12)
1. a kind of shop incidence relation acquisition methods, it is characterised in that：Applied to commercial operation place, the shop incidence relation
Acquisition methods comprise the following steps：
The parameter of strolling about of the customer in collection visiting commercial operation place Nei Ge shops in preset time period；
Based on the parameter of strolling about, it is determined that the weight of the parameter of strolling about and according to each shop of Weight Acquisition customer correspondence
Stroll about scoring；
The similarity between shop is obtained according to the scoring of strolling about in each shop of customer's correspondence；
Visualize the similarity between shop.
2. incidence relation acquisition methods in shop according to claim 1, it is characterised in that：The parameter of strolling about is included in pre-
Customer enters the frequency in the commercial operation place Nei Ge shops, customer and passed by the commercial operation place respectively in section of fixing time
The duration of strolling about that is averaged of the frequency in shop and customer in the commercial operation place Nei Ge shops.
3. incidence relation acquisition methods in shop according to claim 1, it is characterised in that：According to each shop of customer's correspondence
Stroll about scoring cosine similarity obtain shop between similarity.
4. incidence relation acquisition methods in shop according to claim 3, it is characterised in that：Similarity between the shop
For：
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<mi>X</mi>
<mo>&times;</mo>
<mi>Y</mi>
</mrow>
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<mo>|</mo>
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<mi>X</mi>
<mo>|</mo>
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<mo>&times;</mo>
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<mi>Y</mi>
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</mrow>
</mfrac>
<mo>;</mo>
</mrow>
X=(x1,x2,...,xn)T；
Y=(y1,y2,...,yn)T；
Wherein：D (X, Y) is the similarity between shop X and shop Y, and X is score value vector of the customer to shop X, and Y is customer
To shop Y score value vector, | | X | | for score value absolute value of a vector of the customer to shop X, | | Y | | it is customer to shop Y
Score value absolute value of a vector, x1,x2,...,xnRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop X's
Score value, y1,y2,...,ynRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop Y score value, and T is transposition
Symbol.
5. incidence relation acquisition methods in shop according to claim 1, it is characterised in that：Can by network associate diagram form
Depending on changing the similarity between shop.
6. a kind of shop incidence relation obtains system, it is characterised in that：Applied to commercial operation place, the shop incidence relation
Acquisition system includes：
Stroll about parameter collection module, for the customer in collection visiting commercial operation place Nei Ge shops in preset time period
Stroll about parameter；
Weight grading module, for based on the parameter of strolling about, it is determined that the weight of the parameter of strolling about and being obtained according to the weight
Take the scoring of strolling about in each shop of customer's correspondence；
Similarity acquisition module, for obtaining the similarity between shop according to the scoring of strolling about in each shop of customer's correspondence；
Similarity visualization model, for visualizing the similarity between shop.
7. shop incidence relation according to claim 6 obtains system, it is characterised in that：The parameter of strolling about is included in pre-
Customer enters the frequency in the commercial operation place Nei Ge shops, customer and passed by the commercial operation place respectively in section of fixing time
The duration of strolling about that is averaged of the frequency in shop and customer in the commercial operation place Nei Ge shops.
8. shop incidence relation according to claim 6 obtains system, it is characterised in that：The similarity acquisition module root
The similarity between shop is obtained according to the cosine similarity of the scoring of strolling about in each shop of customer's correspondence.
9. shop incidence relation according to claim 8 obtains system, it is characterised in that：Similarity between the shop
For：
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<mi>d</mi>
<mrow>
<mo>(</mo>
<mi>X</mi>
<mo>,</mo>
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<mo>)</mo>
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<mo>&times;</mo>
<mi>Y</mi>
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<mo>&times;</mo>
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<mo>|</mo>
<mi>Y</mi>
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</mrow>
</mfrac>
<mo>;</mo>
</mrow>
X=(x1,x2,...,xn)T；
Y=(y1,y2,...,yn)T；
Wherein：D (X, Y) is the similarity between shop X and shop Y, and X is score value vector of the customer to shop X, and Y is customer
To shop Y score value vector, | | X | | for score value absolute value of a vector of the customer to shop X, | | Y | | it is customer to shop Y
Score value absolute value of a vector, x1,x2,...,xnRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop X's
Score value, y1,y2,...,ynRespectively the 1st customer, n-th of customer of the 2nd customer ... is to shop Y score value, and T is transposition
Symbol.
10. shop incidence relation according to claim 6 obtains system, it is characterised in that：The similarity visualizes mould
Block visualizes the similarity between shop by network associate diagram form.
11. a kind of computer-readable recording medium, is stored thereon with computer program, it is characterised in that：The program is by processor
The step in any one of Claims 1 to 5 methods described is realized during execution.
12. a kind of mobile terminal, including processor and memory, the memory storage have programmed instruction, it is characterised in that：Institute
The instruction of processor operation program is stated to realize such as the step in any one of 1~5 methods described.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710363753.2A CN107169801A (en) | 2017-05-22 | 2017-05-22 | Shop incidence relation acquisition methods, system, storage medium and mobile terminal |
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| CN108009847A (en) * | 2017-11-30 | 2018-05-08 | 西安电子科技大学 | The method for taking out shop embedding feature extractions under scene |
| CN110473043A (en) * | 2018-05-11 | 2019-11-19 | 北京京东尚科信息技术有限公司 | A kind of item recommendation method and device based on user behavior |
| CN110570238A (en) * | 2019-08-26 | 2019-12-13 | 上海汇纳数据科技有限公司 | Method, system, medium, and electronic device for evaluating time value of customer |
| CN112580397A (en) * | 2019-09-29 | 2021-03-30 | 北京市商汤科技开发有限公司 | Data processing method, device and storage medium |
| CN113496432A (en) * | 2021-07-06 | 2021-10-12 | 北京爱笔科技有限公司 | Mining method, device and equipment of entity to be recommended and storage medium |
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| CN108009847A (en) * | 2017-11-30 | 2018-05-08 | 西安电子科技大学 | The method for taking out shop embedding feature extractions under scene |
| CN108009847B (en) * | 2017-11-30 | 2021-06-15 | 西安电子科技大学 | Method for extracting imbedding characteristics of shop under takeaway scene |
| CN110473043A (en) * | 2018-05-11 | 2019-11-19 | 北京京东尚科信息技术有限公司 | A kind of item recommendation method and device based on user behavior |
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| CN113496432A (en) * | 2021-07-06 | 2021-10-12 | 北京爱笔科技有限公司 | Mining method, device and equipment of entity to be recommended and storage medium |
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