CN106846166A - A kind of power marketing customer profile improving method based on the analysis of address big data - Google Patents
A kind of power marketing customer profile improving method based on the analysis of address big data Download PDFInfo
- Publication number
- CN106846166A CN106846166A CN201611123091.3A CN201611123091A CN106846166A CN 106846166 A CN106846166 A CN 106846166A CN 201611123091 A CN201611123091 A CN 201611123091A CN 106846166 A CN106846166 A CN 106846166A
- Authority
- CN
- China
- Prior art keywords
- address
- customer
- electricity consumption
- data
- date
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 64
- 238000004458 analytical method Methods 0.000 title claims abstract description 27
- 230000005611 electricity Effects 0.000 claims abstract description 113
- 230000011218 segmentation Effects 0.000 claims abstract description 32
- 238000012545 processing Methods 0.000 claims abstract description 26
- 238000007405 data analysis Methods 0.000 claims abstract description 11
- 238000010586 diagram Methods 0.000 description 16
- 238000003780 insertion Methods 0.000 description 4
- 230000037431 insertion Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000001514 detection method Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 240000007594 Oryza sativa Species 0.000 description 1
- 235000007164 Oryza sativa Nutrition 0.000 description 1
- 238000004873 anchoring Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000002790 cross-validation Methods 0.000 description 1
- 230000001351 cycling effect Effects 0.000 description 1
- DDVBPZROPPMBLW-IZGXTMSKSA-N latrunculin A Chemical compound C([C@H]1[C@@]2(O)C[C@H]3C[C@H](O2)CC[C@@H](\C=C/C=C/CC\C(C)=C/C(=O)O3)C)SC(=O)N1 DDVBPZROPPMBLW-IZGXTMSKSA-N 0.000 description 1
- NSHPHXHGRHSMIK-IWQSFCKSSA-N latrunculin B Natural products C[C@H]1CC[C@@H]2C[C@@H](C[C@@](O)(O2)[C@@H]3CSC(=O)N3)OC(=O)C=C(C)/CCC=C/1 NSHPHXHGRHSMIK-IWQSFCKSSA-N 0.000 description 1
- DDVBPZROPPMBLW-UHFFFAOYSA-N latrunculin-A Natural products O1C(=O)C=C(C)CCC=CC=CC(C)CCC(O2)CC1CC2(O)C1CSC(=O)N1 DDVBPZROPPMBLW-UHFFFAOYSA-N 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 235000009566 rice Nutrition 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- 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
- G06F16/903—Querying
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- Databases & Information Systems (AREA)
- General Physics & Mathematics (AREA)
- Water Supply & Treatment (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- General Health & Medical Sciences (AREA)
- Computational Linguistics (AREA)
- Public Health (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
This application discloses a kind of power marketing customer profile improving method based on the analysis of address big data, including obtain the customer address data that electricity consumption address date and non-electricity industry are provided；Word segmentation processing is carried out respectively to the electricity consumption address date and the customer address data；Electricity consumption address date and customer address data after word segmentation processing is matched；Judge whether the customer information in the electricity consumption address date and customer address data that the match is successful is different, if it is, updating the customer information in the electricity consumption address date.By the data for introducing other industry, carry out big data analysis, realize the accurate matching of address, on the basis of address date matching, changed according to trade connection mode or different situations that customer premise is changed, the perfect process of power marketing customer profile is respectively completed, real-time, uniformity and the accuracy of customer profile data in power marketing business application system is realized.
Description
Technical field
The invention belongs to Electric Power Marketing Management technical field, more particularly to a kind of electric power based on the analysis of address big data
Marketing customer profile improving method.
Background technology
Current marketing general headquarters of State Grid Corporation of China's (hereinafter referred to as " state's net ") and the electric power of each province and city sales department of Utilities Electric Co.
Marketing customer profile work is primarily present problems with：When the Client handset in power marketing customer profile or phone contact mode
When changing, if customer profile updates not in time, power marketing department can send mistake, and shadow in collection, promotion message
Collection, promotion effect are rung, it could even be possible to causing to complain；When Electricity customers occur change of title, if for same use
User profile in the customer profile of electric address does not upgrade in time, and not only power marketing department can send out in collection, promotion message
Mistake is sent, and influences collection, promotion effect；And when subrogation not in time, customer complaint can be caused, or even credits debt occurs
Business dispute.
Existing mode has the disadvantage that：(1) either Electricity customers contact method changes or customer premise
Situation about changing, is required for client actively to arrive electricity business hall, and when related service is handled, contact staff could passively
Related information is obtained, and manual is entered into power marketing business application system；(2) every time contact staff typing all
It is single, for certain specific Electricity customers, it is impossible to realize that batch improves power marketing customer profile, efficiency is low；(3) when
When Electricity customers are to electricity business hall transacting business, contact method changes or change of title may have been for some time
, or, Electricity customers not remove electricity business hall or by other means with channel actively after these situations occur
These information are changed, the real-time of power marketing customer profile information cannot be ensured, be easy for being sent out in collection, promotion message
Send mistake, influence collection, promotion effect, in some instances it may even be possible to cause the problems such as complaint, credit and debt dispute；(4) electric power contact staff
In the new trade connection mode of manual typing or other new customer profile information, human error, such shadow are easily produced
Ring the accuracy of logging data；(5) the power marketing customer profile perfect cycle is very long, and convergence curve is gentle, and customer profile is complete
Kind coverage rate is low and uneven.
The content of the invention
It is complete the invention provides a kind of power marketing customer profile based on the analysis of address big data to solve the above problems
Kind method, by introducing the data resource of other industry, to electricity consumption address date and other rows in power marketing application system
The customer address data that industry is provided carry out big data analysis, realize the accurate matching of address date, in the base of address date matching
On plinth, changed according to trade connection mode or different situations that customer premise is changed, be respectively completed power marketing
The perfect process of customer profile, realizes real-time, uniformity and the standard of customer profile data in power marketing business application system
True property.
A kind of power marketing customer profile improving method based on the analysis of address big data that the present invention is provided, including：
Obtain the customer address data that electricity consumption address date and non-electricity industry are provided；
Word segmentation processing is carried out respectively to the electricity consumption address date and the customer address data；
Electricity consumption address date and customer address data after word segmentation processing is matched；
Judge whether the customer information in the electricity consumption address date and customer address data that the match is successful is different, if it is,
Then update the customer information in the electricity consumption address date.
Preferably, in the above-mentioned power marketing customer profile improving method based on the analysis of address big data, described right
After electricity consumption address date and customer address data after word segmentation processing are matched, also include：
Obtain the geographical coordinate of the electricity consumption address date and the geographical coordinate of the customer address data and carry out
Match somebody with somebody.
Preferably, in the above-mentioned power marketing customer profile improving method based on the analysis of address big data, the renewal
Customer information in the electricity consumption address date includes：
When the contact method in customer address data changes, replaced using the contact method in the customer address data
Contact method in the electricity consumption address date；
When the property right in customer address data changes, replace described using the property information in the customer address data
Property information in electricity consumption address date.
Preferably, it is described to institute in the above-mentioned power marketing customer profile improving method based on the analysis of address big data
State electricity consumption address date and the customer address data carry out word segmentation processing and are respectively：
Participle is carried out respectively to the electricity consumption address date and the customer address data using maximum forward matching algorithm
Treatment.
Preferably, in the above-mentioned power marketing customer profile improving method based on the analysis of address big data, described pair point
Electricity consumption address date and customer address data after word treatment carry out matching and are：
The electricity consumption address date and customer address data after word segmentation processing are matched using KMP algorithms.
Preferably, in the above-mentioned power marketing customer profile improving method based on the analysis of address big data, the acquisition
The geographical coordinate of the geographical coordinate of the electricity consumption address date and the customer address data simultaneously carries out matching and includes：
Obtain first longitude coordinate and the first latitude coordinate of the electricity consumption address date；
Obtain second longitude coordinate and the second latitude coordinate of the customer address data；
First longitude coordinate, first latitude coordinate, second longitude coordinate after according to pretreatment and
Second latitude coordinate calculate the electricity consumption address date geographical coordinate and the customer address data geographical coordinate it
Between distance；
When the distance being calculated is less than predetermined threshold value, then the electricity consumption address date and the customer address number are judged
According to matching.
By foregoing description, the above-mentioned power marketing customer profile based on the analysis of address big data that the present invention is provided
Improving method, due to including obtaining the customer address data that electricity consumption address date and non-electricity industry are provided；To electricity consumption ground
Location data and the customer address data carry out word segmentation processing respectively；To the electricity consumption address date after word segmentation processing and client ground
Location data are matched；Judge whether the customer information in the electricity consumption address date and customer address data that the match is successful is different,
If it is, updating the customer information in the electricity consumption address date.By introducing the data resource of other industry, electric power is sought
The customer address data that electricity consumption address date and other industry in pin application system are provided carry out big data analysis, realize address
The accurate matching of data, on the basis of address date matching, changes or customer premise hair according to trade connection mode
The different situations for changing more, are respectively completed the perfect process of power marketing customer profile, realize power marketing business application system
The real-time of middle customer profile data, uniformity and accuracy.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this
Inventive embodiment, for those of ordinary skill in the art, on the premise of not paying creative work, can also basis
The accompanying drawing of offer obtains other accompanying drawings.
Fig. 1 is perfect for the first power marketing customer profile based on the analysis of address big data that the embodiment of the present application is provided
The schematic diagram of method；
Fig. 2 is general dictionary schematic diagram；
Fig. 3 is ground thesaurus schematic diagram；
Fig. 4 is cell name dictionary schematic diagram；
Fig. 5 is administrative division set dictionary schematic diagram；
Fig. 6 is the schematic diagram of address segmentation methods；
Fig. 7 is the schematic diagram of electricity consumption address date and customer address Data Matching；
Fig. 8 is address matching algorithm schematic diagram.
Specific embodiment
Core concept of the invention is that a kind of power marketing customer profile based on the analysis of address big data of offer is perfect
Method, by introducing the data resource of other industry, to electricity consumption address date and other industry in power marketing application system
The customer address data of offer carry out big data analysis, realize the accurate matching of address date, on the basis of address date matching
On, changed according to trade connection mode or different situations that customer premise is changed, it is respectively completed power marketing visitor
The process of family file integrity, realizes the real-time of customer profile data in power marketing business application system, uniformity and accurate
Property.
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
The first power marketing customer profile improving method based on the analysis of address big data that the embodiment of the present application is provided
As shown in figure 1, Fig. 1 is complete for the first power marketing customer profile based on the analysis of address big data that the embodiment of the present application is provided
The schematic diagram of kind method, the method comprises the following steps：
S1：Obtain the customer address data that electricity consumption address date and non-electricity industry are provided；
Because power marketing customer profile is the shortcomings of improving process and occasionally there are renewal not in time, therefore it can be introduced
The data resource of his industry improves power marketing customer profile, without the information that manual entry changes, improves operating efficiency.
S2：Word segmentation processing is carried out respectively to the electricity consumption address date and the customer address data；
It should be noted that participle refers to for a Chinese character sequence being cut into single word one by one, participle is exactly
Continuous word sequence is reassembled into the process of word sequence according to certain specification.Chinese is word, sentence and section can be by bright
Aobvious delimiter is simply demarcated, only the formal delimiter of word neither one.In current power marketing business application system
The form of electricity consumption address date by " save (autonomous region, city), city (area, state, alliance), districts under city administration (county-level city), street (small towns),
Neighbourhood committee (village), road, cell, doorplate " etc. is constituted, and the address information storehouse such as " street (small towns), neighbourhood committee (village), road " is by each
Net provincial company is voluntarily safeguarded in power marketing business application system.And other industry provide customer address data form and
The form of the electricity consumption address date of Electricity customers is different in power marketing business application system, such as the client of real estate industry
Address date is generally and is by " city, administrative area, street, neighbourhood committee, cell, Lou Dong, unit, floor, family " nine grades of address formats
Standard.Accordingly, it would be desirable to word segmentation processing is carried out according to different address format standards respectively, while needing by building general term
Storehouse, thesaurus, cell name dictionary, administrative division set dictionary etc., as the reference in address segmentation methods are performed according to
According to and standard, as shown in Fig. 2, Fig. 3, Fig. 4 and Fig. 5, Fig. 2 is general dictionary schematic diagram, and Fig. 3 is ground thesaurus schematic diagram, and Fig. 4 is
Cell name dictionary schematic diagram, Fig. 5 is administrative division set dictionary schematic diagram.
S3：Electricity consumption address date and customer address data after word segmentation processing is matched；
It should be noted that after being operated by participle, it becomes possible to obtain specific electricity consumption address date and customer address
Data, the every single-level address in the two is compared, it becomes possible to learn whether the two is consistent, if unanimously, it becomes possible to according to
Customer address data are updated to some of electricity consumption address date project, improve operating efficiency.
S4：Judge whether the customer information in the electricity consumption address date and customer address data that the match is successful is different, if
It is then to update the customer information in the electricity consumption address date.
In this case, it becomes possible to actively solve the problems, such as that customer information updates, with stronger promptness, be directed to
Property ground solve power marketing business application system in the inconsistent, inaccurate, non real-time etc. of power marketing customer profile information ask
Topic, so as to meet the operating efficiency that Guo Wang sales departments improve power marketing customer profile, lifting power marketing service.
By foregoing description, above-mentioned the first electric power based on the analysis of address big data that the embodiment of the present application is provided
Marketing customer profile improving method, due to including obtaining the customer address data that electricity consumption address date and non-electricity industry are provided；
Word segmentation processing is carried out respectively to the electricity consumption address date and the customer address data；To the electricity consumption address after word segmentation processing
Data and customer address data are matched；Judge the client's letter in the electricity consumption address date and customer address data that the match is successful
Whether breath is different, if it is, updating the customer information in the electricity consumption address date.Provided by the data for introducing other industry
The customer address data that electricity consumption address date in power marketing application system and other industry are provided are carried out big data point by source
Analysis, realize the accurate matching of address date, address date matching on the basis of, changed according to trade connection mode or
The different situations that customer premise is changed, are respectively completed the perfect process of power marketing customer profile, realize power marketing industry
The real-time of customer profile data, uniformity and accuracy in business application system.
Second power marketing customer profile improving method based on the analysis of address big data that the embodiment of the present application is provided,
It is on the basis of above-mentioned the first power marketing customer profile improving method based on the analysis of address big data, also including as follows
Technical characteristic：
It is described to word segmentation processing after electricity consumption address date and customer address data match after, also include：
Obtain the geographical coordinate of the electricity consumption address date and the geographical coordinate of the customer address data and carry out
Match somebody with somebody.
It should be noted that, it is necessary to perform the matching of GPS addresses on the basis of in electricity consumption address and customer address, the match is successful
Algorithm, by marketing, GPS addresses carry out cross validation, can further improve the accuracy of address matching.
The third power marketing customer profile improving method based on the analysis of address big data that the embodiment of the present application is provided,
It is on the basis of the above-mentioned second power marketing customer profile improving method based on the analysis of address big data, also including as follows
Technical characteristic：
The customer information updated in the electricity consumption address date includes：
When the contact method in customer address data changes, replaced using the contact method in the customer address data
Contact method in the electricity consumption address date；
For example：When Electricity customers contact method changes, the verification of Electricity customers contact method and renewal are carried out.
For example, marketing Electricity customers archives are：
Electricity customers：Zhang San
Identification card number：430121198006071234
Contact method：18942512345
Electricity consumption address：No. 199 three phases of the ten thousand state cities present age 10 of Changsha Kaifu District Hong Shan streets Shuan He communities Fu Yuan West Roads
Two units 1706
GPS collects and records with insertion in battalion：112.98674512,28.25572235
Other industry customer data is：
Client：Zhang San
Identification card number：430121198006071234
Contact method：13873912345
Address：The Room of 3 phase of the ten thousand state city of Changsha Kaifu District Fu Yuan West Roads 199 No. 10,17 floor of Unit 2, building 1706
GPS information：112.986615,28.255783
After address matching and Electricity customers contact method are examined and updated, power marketing customer profile is changed to：
Electricity customers：Zhang San
Identification card number：430121198006071234
Contact method：13873912345
Electricity consumption address：No. 199 three phases of the ten thousand state cities present age 10 of Changsha Kaifu District Hong Shan streets Shuan He communities Fu Yuan West Roads
Two units 1706.
When the property right in customer address data changes, replace described using the property information in the customer address data
Property information in electricity consumption address date.
For example：When the customer premise of the electricity consumption address is changed, it is necessary to carry out change verification with Electricity customers, go forward side by side
Capable transfer flow of renaming, realizes upgrading in time for power marketing customer profile.
For example, marketing Electricity customers archives are：
Electricity customers：Zhang San
Identification card number：430121198006071234
Contact method：18942512345
Electricity consumption address：No. 199 three phases of the ten thousand state cities present age 10 of Changsha Kaifu District Hong Shan streets Shuan He communities Fu Yuan West Roads
Two units 1706
GPS collects and records with insertion in battalion：112.98674512,28.25572235
Other industry customer data is：
Client：Li Si
Identification card number：430121198710130725
Contact method：13873912345
Address：The Room of 3 phase of the ten thousand state city of Changsha Kaifu District Fu Yuan West Roads 199 No. 10,17 floor of Unit 2, building 1706
GPS information：112.986615,28.255783
After address matching and Electricity customers change of title are examined and updated, power marketing customer profile is updated to：
Electricity customers：Li Si
Identification card number：430121198710130725
Contact method：13873912345
Electricity consumption address：No. 199 three phases of the ten thousand state cities present age 10 of Changsha Kaifu District Hong Shan streets Shuan He communities Fu Yuan West Roads
Two units 1706.
The 4th kind of power marketing customer profile improving method based on the analysis of address big data that the embodiment of the present application is provided,
It is on the basis of above-mentioned the third is based on the power marketing customer profile improving method of address big data analysis, also including as follows
Technical characteristic：
It is described word segmentation processing is carried out respectively to the electricity consumption address date and the customer address data to be：
Participle is carried out respectively to the electricity consumption address date and the customer address data using maximum forward matching algorithm
Treatment.
Maximum forward matching algorithm is one kind of maximum matching algorithm, and its cardinal principle is all to be syncopated as individual character string, then
Compare with dictionary, if a word is just recorded, otherwise by increasing or reducing an individual character, continue to compare,
An individual character is there remains always then to terminate, if the individual character string cannot cutting, as be not logged in treatment.As shown in fig. 6, Fig. 6
It is the schematic diagram of address segmentation methods, specific algorithm is as follows：
To from left to right treat that the several continuation characters in participle text are matched with vocabulary, if matched, are syncopated as one
Individual word.But there is a problem here：Accomplish maximum matching, be not to match just can such as treat participle with cutting for the first time
Text：
Content []={ " flood ", " mountain ", " street ", " road ", " double ", " river ", " society ", " area " ... ... }
Vocabulary：Dict []={ " Changsha ", " Kaifu District ", " Hong Shan ", " Hong Shan streets " ... }
(1) since content [1], when scanning is to content [2], find " Hong Shan " in vocabulary dict
[] suffers, but can't cut out, because we do not know that word below can constitute longer word (maximum
With)；
(2) content [3] is continued to scan on, it is found that " Hong Shan streets " is not the word in dict [].But we can't be true
Whether fixed " Hong Shan " for above finding has been maximum word, because " Hong Shan streets " is the prefix of dict [2]；
(3) scanning content [4], it is found that " Hong Shan streets " is the word in dict [].Continue to scan on down；
(4) when content [5] are scanned, it is found that " Hong Shan streets are double " are not the word in vocabulary, nor word
Prefix.Therefore above maximum word --- " Hong Shan streets " can be syncopated as.
As can be seen here, the maximum word for matching must assure that next scanning is not that the prefix of word in vocabulary or word just may be used
To terminate.Using maximum forward matching algorithm, continue cycling through, complete remaining participle.Such as " Changsha Kaifu District Hong Shan streets Shuan He
The last word segmentation result of this address of the Unit 2 1706 of three phase of the ten thousand state cities present age 10 of community Fu Yuan West Roads 199 " is as follows：
" Changsha | Kaifu District | Hong Shan streets | Shuan He communities | Fu Yuan West Roads | 199 | number | three phase of contemporary ten thousand state city | 10 |
| two | units | 1706 ".
After word segmentation processing is complete, in addition it is also necessary to using recommending semanteme to carry out treatment and optimization after participle, such as abbreviation, parent-zone
Draw, cell alias, the aspect such as wrong word amendment, eventually form the word segmentation result after optimization, be easy to improve what subsequent address was matched
Accuracy and efficiency.Such as above example will be optimized for following result：
" Changsha | Kaifu District | Hong Shan streets | Shuan He communities | Fu Yuan West Roads | No. 199 | the phase of ten thousand state city three | 10 | Unit 2
| Room 1706 ".
The 5th kind of power marketing customer profile improving method based on the analysis of address big data that the embodiment of the present application is provided,
Be it is above-mentioned the first to the 4th kind based on address big data analysis power marketing customer profile improving method in any one
On the basis of, also including following technical characteristic：
The electricity consumption address date and customer address data to after word segmentation processing carries out matching and is：
The electricity consumption address date and customer address data after word segmentation processing are matched using KMP algorithms.
KMP algorithms are a kind of improved string matching algorithms, same by D.E.Knuth, J.H.Morris and V.R.Pratt
Shi Faxian, therefore people its --- Mo Lisi --- Alexandre Desplat that is called Cnut operation (abbreviation KMP algorithms).The pass of KMP algorithms
Key is, using the information after it fails to match, pattern string and the matching times of main string to be reduced as far as possible to reach the purpose of Rapid matching.
Implement is exactly that with next () function, function contains the local matching information of pattern string, time complexity O in itself
(m+n).With reference to Fig. 7, Fig. 7 is the schematic diagram of electricity consumption address date and customer address Data Matching.For each word segmentation result, lead to
Crossing KMP algorithms carries out participle matching, and is matched one by one according to participle level.For the participle that cannot be matched, such as electricity consumption
The participle such as " Hong Shan streets ", " Shuan He communities " in location data (marketing address), but other industry address (customer address data)
In there is no the participle of " street " and " community ", at this moment need to proceed next stage participle and match, i.e., both sides block participle
Match somebody with somebody, completed until all participles are matched.If the match is successful for all participles, address matching result is " matching ", otherwise for " no
Matching ".It should be noted that traditional matching idea is scanned since the first character of target strings, one by one with pattern string
Correspondence character is matched, if this group of character match, detects next group of character, such as mismatch, then returns to the of target strings
Two characters, repeat the above steps, and until whole pattern finds matching in target strings, or have scanned through whole target strings
Also untill enough could not completing matching.Assuming that pattern string length is m, target string length is n, then more at most need to spend O every time
M the time of (), the complexity of algorithm is O ((n-m+1) * m).This algorithm not using the information for matching, every time from the beginning
Start to compare, efficiency is very low.And KMP matching algorithms are on the basis of traditional algorithm, after it fails to match, and not simply from
Target strings character late starts the detection of a new round, but according to the useful information for obtaining before testing, in other words pattern
The characteristic information of string itself, obtains the position that redirects of next functions, directly skip it is unnecessary from the beginning detect every time, so as to reach one
Individual detection efficiency higher.
The 6th kind of power marketing customer profile improving method based on the analysis of address big data that the embodiment of the present application is provided,
It is on the basis of the above-mentioned second power marketing customer profile improving method based on the analysis of address big data, also including as follows
Technical characteristic：
The geographical coordinate of the geographical coordinate for obtaining the electricity consumption address date and the customer address data is gone forward side by side
Row matching includes：
Obtain first longitude coordinate and the first latitude coordinate of the electricity consumption address date；
Obtain second longitude coordinate and the second latitude coordinate of the customer address data；
First longitude coordinate, first latitude coordinate, second longitude coordinate after according to pretreatment and
Second latitude coordinate calculate the electricity consumption address date geographical coordinate and the customer address data geographical coordinate it
Between distance；
When the distance being calculated is less than predetermined threshold value, then the electricity consumption address date and the customer address number are judged
According to matching.
As shown in figure 8, Fig. 8 is address matching algorithm schematic diagram, obtain battalion according to electricity consumption address date adopts with insertion address
The GPS information (longitude, latitude) and customer address data (other industry address) corresponding GPS information of record, calculate two GPS
The distance of information.The earth is a spheroid for intimate standard, and the longitude and latitude according to earth surface any two points can just be calculated
The surface distance for going out this point-to-point transmission (ignores the error that earth surface landform is brought to calculating, only theoretic estimation here
Value).The longitude and latitude of the GPS information collected and recorded with insertion address of anchoring a tent is (LonA, LatA), other industry address correspondence GPS information
Longitude and latitude be (LonB, LatB), according to 0 degree of benchmark of warp, east longitude degree of learning from else's experience on the occasion of (Longitude), west longitude is learnt from else's experience
Degree negative value (- Longitude), north latitude takes 90- latitude values (90-Latitude), and south latitude takes 90+ latitude values (90+Latitude),
Then it is counted as (MLonA, MLatA) and (MLonB, MLatB) by 2 points after above-mentioned treating.Derived according to triangle, can be with
Obtain calculating the equation below of two point distances：
C=sin (MLatA) * sin (MLatB) * cos (MLonA-MLonB)+cos (MLatA) * cos (MLatB)
D=R*Arccos (C) * Pi/180
Here R and D units are identicals, if using 6371.004 kms as radius R, then D is exactly with thousand
Rice is unit.If two GPS informations are less than certain predetermined threshold value apart from D, then be taken as identical address area, have
The predetermined threshold value definition of body also needs to be processed with reference to the precision of two GPS informations.
The foregoing description of the disclosed embodiments, enables professional and technical personnel in the field to realize or uses the present invention.
Various modifications to these embodiments will be apparent for those skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, the present invention
The embodiments shown herein is not intended to be limited to, and is to fit to and principles disclosed herein and features of novelty phase one
The scope most wide for causing.
Claims (6)
1. it is a kind of based on address big data analysis power marketing customer profile improving method, it is characterised in that including：
Obtain the customer address data that electricity consumption address date and non-electricity industry are provided；
Word segmentation processing is carried out respectively to the electricity consumption address date and the customer address data；
Electricity consumption address date and customer address data after word segmentation processing is matched；
Judge whether the customer information in the electricity consumption address date and customer address data that the match is successful is different, if it is, more
Customer information in the new electricity consumption address date.
2. it is according to claim 1 based on address big data analysis power marketing customer profile improving method, its feature
Be, it is described to word segmentation processing after electricity consumption address date and customer address data match after, also include：
Obtain the geographical coordinate of the electricity consumption address date and the geographical coordinate of the customer address data and matched.
3. it is according to claim 2 based on address big data analysis power marketing customer profile improving method, its feature
It is,
The customer information updated in the electricity consumption address date includes：
When the contact method in customer address data changes, replace described using the contact method in the customer address data
Contact method in electricity consumption address date；
When the property right in customer address data changes, the electricity consumption is replaced using the property information in the customer address data
Property information in address date.
4. it is according to claim 3 based on address big data analysis power marketing customer profile improving method, its feature
It is,
It is described word segmentation processing is carried out respectively to the electricity consumption address date and the customer address data to be：
Word segmentation processing is carried out respectively to the electricity consumption address date and the customer address data using maximum forward matching algorithm.
5. the power marketing customer profile based on the analysis of address big data according to claim any one of 1-4 improves side
Method, it is characterised in that
The electricity consumption address date and customer address data to after word segmentation processing carries out matching and is：
The electricity consumption address date and customer address data after word segmentation processing are matched using KMP algorithms.
6. it is according to claim 2 based on address big data analysis power marketing customer profile improving method, its feature
It is that the geographical coordinate of the geographical coordinate for obtaining the electricity consumption address date and the customer address data is simultaneously carried out
With including：
Obtain first longitude coordinate and the first latitude coordinate of the electricity consumption address date；
Obtain second longitude coordinate and the second latitude coordinate of the customer address data；
First longitude coordinate, first latitude coordinate, second longitude coordinate after according to pretreatment and described
Second latitude coordinate is calculated between the geographical coordinate and the geographical coordinate of the customer address data of the electricity consumption address date
Distance；
When the distance being calculated is less than predetermined threshold value, then the electricity consumption address date and the customer address data phase are judged
Matching.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611123091.3A CN106846166A (en) | 2016-12-08 | 2016-12-08 | A kind of power marketing customer profile improving method based on the analysis of address big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611123091.3A CN106846166A (en) | 2016-12-08 | 2016-12-08 | A kind of power marketing customer profile improving method based on the analysis of address big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106846166A true CN106846166A (en) | 2017-06-13 |
Family
ID=59139250
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611123091.3A Pending CN106846166A (en) | 2016-12-08 | 2016-12-08 | A kind of power marketing customer profile improving method based on the analysis of address big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106846166A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108228825A (en) * | 2018-01-02 | 2018-06-29 | 北京市燃气集团有限责任公司 | A kind of station address data cleaning method based on participle |
| CN108416062A (en) * | 2018-03-26 | 2018-08-17 | 国家电网公司客户服务中心 | A kind of electric network data correlating method based on address matching technology |
| CN108830649A (en) * | 2018-06-05 | 2018-11-16 | 国网浙江省电力有限公司 | Change of title Electricity customers localization method for power marketing |
| CN113672703A (en) * | 2021-08-26 | 2021-11-19 | 国家电网有限公司大数据中心 | User information updating method, device, equipment and storage medium |
| CN113672702A (en) * | 2021-08-26 | 2021-11-19 | 国家电网有限公司大数据中心 | Method, device and equipment for improving user profile information and storage medium |
| CN113672702B (en) * | 2021-08-26 | 2024-07-02 | 国家电网有限公司大数据中心 | User profile information perfecting method, device, equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101882163A (en) * | 2010-06-30 | 2010-11-10 | 中国科学院地理科学与资源研究所 | Fuzzy Chinese address geographic evaluation method based on matching rule |
| CN103886082A (en) * | 2014-03-26 | 2014-06-25 | 百度在线网络技术（北京）有限公司 | Method and device for verifying position information of interest points |
| CN104077322A (en) * | 2013-03-30 | 2014-10-01 | 百度在线网络技术（北京）有限公司 | Method and system for mining geographic information on basis of problems |
| CN104714950A (en) * | 2013-12-13 | 2015-06-17 | 中国银联股份有限公司 | Method and system for correcting and supplementing information in database |
-
2016
- 2016-12-08 CN CN201611123091.3A patent/CN106846166A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101882163A (en) * | 2010-06-30 | 2010-11-10 | 中国科学院地理科学与资源研究所 | Fuzzy Chinese address geographic evaluation method based on matching rule |
| CN104077322A (en) * | 2013-03-30 | 2014-10-01 | 百度在线网络技术（北京）有限公司 | Method and system for mining geographic information on basis of problems |
| CN104714950A (en) * | 2013-12-13 | 2015-06-17 | 中国银联股份有限公司 | Method and system for correcting and supplementing information in database |
| CN103886082A (en) * | 2014-03-26 | 2014-06-25 | 百度在线网络技术（北京）有限公司 | Method and device for verifying position information of interest points |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108228825A (en) * | 2018-01-02 | 2018-06-29 | 北京市燃气集团有限责任公司 | A kind of station address data cleaning method based on participle |
| CN108228825B (en) * | 2018-01-02 | 2019-02-15 | 北京市燃气集团有限责任公司 | A kind of station address data cleaning method based on participle |
| CN108416062A (en) * | 2018-03-26 | 2018-08-17 | 国家电网公司客户服务中心 | A kind of electric network data correlating method based on address matching technology |
| CN108830649A (en) * | 2018-06-05 | 2018-11-16 | 国网浙江省电力有限公司 | Change of title Electricity customers localization method for power marketing |
| CN113672703A (en) * | 2021-08-26 | 2021-11-19 | 国家电网有限公司大数据中心 | User information updating method, device, equipment and storage medium |
| CN113672702A (en) * | 2021-08-26 | 2021-11-19 | 国家电网有限公司大数据中心 | Method, device and equipment for improving user profile information and storage medium |
| CN113672702B (en) * | 2021-08-26 | 2024-07-02 | 国家电网有限公司大数据中心 | User profile information perfecting method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106846166A (en) | A kind of power marketing customer profile improving method based on the analysis of address big data | |
| CN106777275B (en) | Entity attribute and property value extracting method based on more granularity semantic chunks | |
| CN108628811B (en) | Address text matching method and device | |
| CN102955833B (en) | A kind of address identification, standardized method | |
| US20180211350A1 (en) | Urban road network asset valuation method, apparatus and system | |
| CN110472066A (en) | A kind of construction method of urban geography semantic knowledge map | |
| Zhao et al. | Clustering analysis of ridership patterns at subway stations: A case in Nanjing, China | |
| CN111324679B (en) | Method, device and system for processing address information | |
| WO2021259007A1 (en) | Data pushing method and system based on behavior trajectory, and computer device | |
| US20230289807A1 (en) | Method for detecting block chain abnormal behavior based on graph embedding | |
| CN103514235B (en) | A kind of method for building up of incremental code library and device | |
| CN107016042B (en) | Address information verification system based on user position log | |
| CN107463711A (en) | A kind of tag match method and device of data | |
| CN111191817B (en) | Bus network topology division method based on transfer passenger flow | |
| CN108876064A (en) | Urban mass transit network key station recognition methods based on the volume of the flow of passengers | |
| CN108536825A (en) | A method of whether identification source of houses data repeat | |
| Raman et al. | Cultural diversity and spatial structure in the Indian urban context | |
| CN111523433B (en) | Standardized processing method, device and equipment for end address of express mail | |
| CN106155998A (en) | A kind of data processing method and device | |
| CN102117510A (en) | Unknown transportation mean passenger source predictive method in big activities | |
| CN115146635B (en) | Address segmentation method based on domain knowledge enhancement | |
| CN107644101A (en) | Information classification approach and device, information classification equipment and computer-readable medium | |
| Xiao et al. | Multiscale analysis of urban walkability and Pedestrian's destination choice | |
| CN106851565B (en) | A kind of border base station recognition methods and system | |
| Zheng et al. | Discovering urban functional regions with call detail records and points of interest: A case study of Guangzhou city |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170613 |