CN109447753B - Address matching method and system based on big data - Google Patents
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Abstract
The invention discloses an address matching method and system based on big data, which comprises the steps of obtaining a takeaway address set by a user, and dividing the content included in the takeaway address into a first-level address, a second-level address and a third-level address according to a region range; acquiring first position information of a user and importing the first position information into an electronic map preset by a system; judging whether the takeaway address is matched with the first position information; if yes, acquiring merchant information from the takeout platform, wherein the merchant information comprises distribution time and a distribution range; judging whether the takeout address is located in a distribution range through the takeout platform; if not, extracting a distribution range, and importing the distribution range into the electronic map; establishing a first preset range in the electronic map by taking the first position information as a circle center and taking a preset distance as a radius; extracting second position information around the first position information in a preset range; judging whether the second position information is located in a distribution range through the takeout platform; if so, the first location information is listed in the delivery range.
Description
Technical Field
The invention relates to the field of big data, in particular to an address matching method and system based on big data.
Background
Due to the development of internet technology, the development scale of take-out platforms is huge, people tend to take out to solve the problem of eating, but the huge take-out system also has a lot of inconvenience in use, which causes great trouble to the ordering selection of users, for example, the users order dishes in the same merchant successfully for many times, but under the condition that the merchant and the platform do not modify the distribution range, the system prompts that the receiving place exceeds the distribution range of the merchant when in payment, but the receiving address is located in the distribution range of the merchant, which wastes the time for selecting dishes by the users and delays the eating time.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the disadvantages in the background art, embodiments of the present invention provide an address matching method and system based on big data, which can effectively solve the problems related to the background art.
The technical scheme is as follows: a big data-based address matching method comprises the following steps:
101: acquiring a takeout address set by a user, analyzing the takeout address, and dividing the content included in the takeout address into a first-level address, a second-level address and a third-level address according to a region range;
102: acquiring first position information of a user through intelligent equipment of the user, and importing the first position information into an electronic map preset by a system;
103: judging whether the takeaway address is matched with the first position information;
104: if yes, acquiring merchant information from the takeout platform, wherein the merchant information comprises distribution time and a distribution range;
105: acquiring the current moment and judging whether the current moment is within the distribution time;
106: if yes, judging whether the takeout address is located in the distribution range through a takeout platform;
107: if not, extracting the distribution range, and importing the distribution range into the electronic map;
108: establishing a first preset range in the electronic map by taking the first position information as a circle center and a preset distance as a radius;
109: extracting second position information around the first position information in the preset range one by one according to the third-level address, the second-level address and the first-level address;
110: judging whether the second position information is located in the distribution range through a take-out platform;
111: and if so, listing the first position information in the distribution range.
As a preferable aspect of the present invention, the extracting of the second position information around the first position information further includes:
acquiring third position information of the merchant;
calculating a distance value between the third location information and the first location information;
establishing a second preset range by taking the third position information as a circle center and the distance value as a radius;
extracting a difference set of the first preset range and the second preset range;
and extracting second position information around the first position information from the difference set.
As a preferable aspect of the present invention, if the second location information is not located within the delivery range, the method further includes:
extracting a complementary set of a second preset range;
randomly extracting fourth position information from the complementary set;
judging whether the fourth position information is located in the distribution range through a take-out platform;
and if so, listing the first position information in the distribution range.
As a preferable aspect of the present invention, the extracting of the second position information around the first position information further includes:
respectively calculating distance values between all the extracted second position information and the first position information;
and arranging the second position information according to the ascending order of the distance values according to a principle of from near to far.
As a preferable mode of the present invention, the determining, by the takeout platform, whether the second location information is within the delivery range further includes:
and comparing the second position information with the distribution range one by one according to the ascending sequence.
A big-data based address matching system, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is configured to acquire a takeout address set by a user;
the analysis module is configured to divide the content included in the takeout address into a first-level address, a second-level address and a third-level address according to a region range;
the second acquisition module is configured to acquire first position information of the user through the intelligent equipment of the user;
the first import module is configured to import the first position information into an electronic map preset by a system;
a first determination module configured to determine whether the take-away address matches the first location information;
the third acquisition module is configured to acquire merchant information from the takeaway platform, wherein the merchant information comprises delivery time and delivery range;
the second judgment module is configured to acquire the current moment and judge whether the current moment is within the distribution time;
the third judging module is configured to judge whether the takeout address is located in the delivery range through a takeout platform;
the second import module is configured to import the distribution range into an electronic map preset by a system;
the first establishing module is configured to establish a preset range in the electronic map by taking the first position information as a circle center and a preset distance as a radius;
the first extraction module is configured to extract second position information around the first position information within the preset range one by one according to the third-level address, the second-level address and the first-level address;
the fourth judging module is configured to judge whether the second position information is located in the distribution range through a takeout platform;
a modification module configured to list the first location information within the delivery range.
As a preferred embodiment of the present invention, the present invention further comprises:
the fourth acquisition module is configured to acquire third position information of the merchant;
a first calculation module configured to calculate a distance value between the third location information and the first location information;
the second establishing module is configured to establish a second preset range by taking the third position information as a circle center and the distance value as a radius;
a second extraction module configured to extract a difference set of the first preset range and the second preset range.
As a preferred embodiment of the present invention, the present invention further comprises:
a third extraction module configured to extract a complement of a second preset range;
a fourth extraction module configured to randomly extract fourth location information from the complementary set;
a fifth judging module configured to judge whether the fourth location information is within the delivery range through a takeout platform.
As a preferred mode of the present invention, the second calculating module is configured to calculate distance values between all the extracted second location information and the first location information, respectively;
the sorting module is configured to sort the second position information in an ascending order according to the distance value according to a principle of from near to far.
The invention realizes the following beneficial effects:
the big data-based address matching method is suitable for application and takeaway delivery, can reduce the loophole that the takeaway address set by the user is not in the delivery range of a merchant, and improves the accuracy of takeaway address matching; setting a first preset range with judgment efficiency, extracting a plurality of second position information in the first preset range, and if the second position information in the distribution range exists, listing the first position information in the distribution range; and extracting a difference set of the first preset range and the second preset range, wherein the distance between any second position information and third position information in the difference set is larger than the distance between the first position information and the third position information, and the reliability of the second position information as a judgment standard is improved by reducing the first preset range.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
FIG. 1 is a flow chart of a big data-based address matching method according to the present invention;
FIG. 2 is a flowchart of an address matching method according to the present invention;
FIG. 3 is a flow chart of another address matching method provided by the present invention;
FIG. 4 is a flowchart of a second location information ranking method provided by the present invention;
FIG. 5 is a flowchart of a second position information comparison method according to the present invention;
fig. 6 is a block diagram of a structure of an address matching system based on big data according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Example one
As shown in fig. 1, an address matching method based on big data includes the following steps:
101: acquiring a takeout address set by a user, analyzing the takeout address, and dividing the content included in the takeout address into a first-level address, a second-level address and a third-level address according to a region range;
102: acquiring first position information of a user through intelligent equipment of the user, and importing the first position information into an electronic map preset by a system;
103: judging whether the takeaway address is matched with the first position information;
104: if yes, acquiring merchant information from the takeout platform, wherein the merchant information comprises distribution time and a distribution range;
105: acquiring the current moment and judging whether the current moment is within the distribution time;
106: if yes, judging whether the takeout address is located in a distribution range through the takeout platform;
107: if not, extracting a distribution range, and importing the distribution range into the electronic map;
108: establishing a first preset range in the electronic map by taking the first position information as a circle center and taking a preset distance as a radius;
109: extracting second position information surrounding the first position information within a preset range one by one according to the third-level address, the second-level address and the first-level address;
110: judging whether the second position information is located in a distribution range through the takeout platform;
111: if so, the first location information is listed in the delivery range.
Specifically, in step 101, a takeaway address set by a user is obtained through account information of the user, where the takeaway address is a receiving address of takeaway, the takeaway address includes sub-addresses of several levels, such as province, city, county, street, house number, and the like, and each level of sub-address is defined as a first level address, a second level address, a third level address, and the like, where the range of the first level address is the smallest, the second level address is the second, and so on.
In step 102, when the user logs in the takeout platform by using the smart device, if the user starts the positioning function of the smart device, the system automatically obtains the location information of the smart device, where the location information is the first location information of the user, and at the same time, the first location information is imported into an electronic map preset by the system.
In step 103, it is determined whether the takeaway address matches the first location information, that is, whether the takeaway address and the first location information are the same address, and the system presets an error value, and if the distance between the takeaway address and the first location information is less than or equal to the error value, it is determined that the takeaway address matches the first location information.
In step 104, if the takeout address matches the first location information, a takeout delivery service may be provided for the user, and merchant information is obtained from a database of the takeout platform, where the merchant information only includes public information such as delivery time and delivery range.
In step 105, the current time when the user logs in the takeaway platform is obtained, whether the current time is within the distribution time or not is judged, and if not, the merchant is not displayed.
In step 106, if the current time is within the delivery time, whether the takeaway address set by the user is within the delivery range is judged according to the calculation rule of the takeaway platform.
In step 107, if the takeaway address is located within the delivery range, the user may order a meal in the merchant, and if the takeaway address is not located within the delivery range, the error of address matching of the takeaway platform may be reduced by the intelligent address matching method provided by the present invention.
In step 108, a first preset range is established in the electronic map preset by the system with the first position information as a center of a circle and the preset distance as a radius, in this embodiment, the preset distance is set to be 1 km, that is, the first preset range is a circular area with the first position information as a center of a circle and the radius of 1 km.
In step 109, the electronic map includes first location information and a first preset range, and the two are overlapped in the electronic map, and are gradually screened from a higher-level address to a lower-level address, for example, the takeaway address set by the user includes a first-level address, a second-level address, and a third-level address, the system first extracts an address corresponding to the first-level address, then extracts an address corresponding to the second-level address from the extracted addresses, then extracts an address corresponding to the third-level address from the addresses corresponding to the second-level address, and then determines whether the finally extracted address is located within the first preset range, if so, the address is taken as second location information, and if not, the address is deleted.
In step 110, it is determined whether the second location information is within the distribution range of the merchant according to the calculation rule of the takeaway platform.
In step 111, if the second location information is located in the distribution range, it indicates that the first location information closer to the second location information should also be located in the distribution range, and the first location information is listed in the distribution range, so that the user can order in the merchant.
Example two
As shown in fig. 2, the extracting of the second location information around the first location information further includes:
acquiring third position information of the merchant;
calculating a distance value between the third position information and the first position information;
establishing a second preset range by taking the third position information as a circle center and the distance value as a radius;
extracting a difference set of a first preset range and a second preset range;
second position information surrounding the first position information is extracted from the difference set.
As shown in fig. 3, if the second location information is not located within the distribution range, the method further includes:
extracting a complementary set of a second preset range;
randomly extracting fourth position information from the complementary set;
judging whether the fourth position information is located in a distribution range through the takeout platform;
if so, the first location information is listed in the delivery range.
Specifically, before the first position information is listed in the distribution range, the position relationship among the position of the merchant, the first position information and the second position information needs to be judged, the extracted second position information needs to be ensured to have accurate judgment efficiency, the third position information of the merchant is obtained from a database of the takeout platform, the third position information is led into an electronic map preset by the system, the distance value between the third position information and the first position information is calculated, namely the distance value between the merchant and the user is calculated, in the electronic map, the third position information is taken as the center of a circle, the distance is taken as the radius to establish a second preset range, the first preset range and the second preset range are compared, the difference set of the first preset range and the second preset range is calculated, and the distance between any second position information in the difference set and the third position information is larger than the distance between the first position information and the third position information, and then judging whether the second position information in the difference set is located in the distribution range, if so, arranging the first position information which is closer to the second position information in the distribution range, and listing the first position information in the distribution range.
The first preset range is a small-range area established by first position information, if second position information in the small-range area does not belong to a distribution range, the first preset range is probably in an error range, at the moment, a full set is set according to a first-level address or a second-level address or a third-level address, the full set range can be defined by users, a complementary set of the second preset range is extracted from the full set, fourth position information is randomly extracted from the complementary set, the distance between any fourth position information and the third position information in the complementary set is larger than the distance between the first position information and the third position information, whether fourth position information in the complementary set is located in the distribution range is judged, if yes, the first position information closer to the complementary set is located in the distribution range, and the first position information is listed in the distribution range.
EXAMPLE III
As shown in fig. 4, the extracting of the second location information around the first location information further includes:
respectively calculating distance values between all the extracted second position information and the first position information;
and arranging the second position information according to the ascending order of the distance values according to a principle of going from near to far.
As shown in fig. 5, the determining, by the takeaway platform, whether the second location information is located within the delivery range further includes:
and comparing the second position information with the distribution range one by one according to the ascending sequence.
Specifically, if there is non-unique second location information in the first preset range, it is necessary to compare each second location information of the first preset range with the distribution range, and stop the determination until one of the second location information is located in the distribution range.
Example four
As shown in fig. 6, a big data based address matching system includes:
a first obtaining module 401 configured to obtain a takeout address set by a user;
the analyzing module 402 is configured to divide the content included in the takeaway address into a first-level address, a second-level address and a third-level address according to a region range;
a second obtaining module 403, configured to obtain first location information of the user through the smart device of the user;
a first import module 404 configured to import the first location information into an electronic map preset by the system;
a first determining module 405 configured to determine whether the takeaway address matches the first location information;
a third obtaining module 406, configured to obtain merchant information from the takeaway platform, where the merchant information includes a delivery time and a delivery range;
a second determining module 407, configured to obtain a current time and determine whether it is within the delivery time;
a third determining module 408 configured to determine whether the takeout address is within the delivery range through the takeout platform;
a second import module 409 configured to import the distribution range into an electronic map preset by the system;
the first establishing module 410 is configured to establish a preset range in the electronic map by taking the first position information as a circle center and taking a preset distance as a radius;
the first extraction module 411 is configured to extract second location information around the first location information within a preset range one by one according to the third-level address, the second-level address and the first-level address;
a fourth determining module 412, configured to determine whether the second location information is located within the delivery range through the takeout platform;
a modification module 413 configured to list the first location information within a delivery range;
a fourth obtaining module 414 configured to obtain third location information of the merchant;
a first calculation module 415 configured to calculate a distance value between the third location information and the first location information;
a second establishing module 416, configured to establish a second preset range with the third position information as a center and the distance value as a radius;
a second extraction module 417 configured to extract a difference set of the first preset range and the second preset range;
a third extraction module 418 configured to extract a complement of the second preset range;
a fourth extraction module 419 configured to randomly extract fourth location information from the complementary set;
a fifth judging module 420 configured to judge whether the fourth location information is within the delivery range through the takeout platform;
a second calculating module 421 configured to calculate distance values between all the extracted second location information and the first location information, respectively;
a sorting module 422 configured to sort the second location information in ascending order of distance values on a near-to-far basis.
The system provided in the fourth embodiment is only illustrated by dividing the functional modules, and in practical applications, the functions may be distributed by different functional modules according to needs, that is, the internal structure of the system is divided into different functional modules to complete all or part of the functions described above.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All equivalent changes or modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (7)
1. A big data-based address matching method is characterized in that: the method comprises the following steps:
101: acquiring a takeout address set by a user, analyzing the takeout address, and dividing the content included in the takeout address into a first-level address, a second-level address and a third-level address according to a region range;
102: acquiring first position information of a user through intelligent equipment of the user, and importing the first position information into an electronic map preset by a system;
103: judging whether the takeaway address is matched with the first position information;
104: if yes, acquiring merchant information from the takeout platform, wherein the merchant information comprises distribution time and a distribution range;
105: acquiring the current moment and judging whether the current moment is within the distribution time;
106: if yes, judging whether the takeout address is located in the distribution range through a takeout platform;
107: if not, extracting the distribution range, and importing the distribution range into the electronic map;
108: establishing a first preset range in the electronic map by taking the first position information as a circle center and a preset distance as a radius;
109: extracting second position information surrounding the first position information within the first preset range one by one according to the third-level address, the second-level address and the first-level address:
acquiring third position information of the merchant;
calculating a distance value between the third location information and the first location information;
establishing a second preset range by taking the third position information as a circle center and the distance value as a radius;
extracting a difference set of the first preset range and the second preset range;
extracting second position information around the first position information from the difference set;
110: judging whether the second position information is located in the distribution range through a take-out platform;
111: and if so, listing the first position information in the distribution range.
2. The big data-based address matching method according to claim 1, wherein: if the second location information is not located in the distribution range, the method further comprises:
extracting a complementary set of a second preset range;
randomly extracting fourth position information from the complementary set;
judging whether the fourth position information is located in the distribution range through a take-out platform;
and if so, listing the first position information in the distribution range.
3. The big data-based address matching method according to claim 1, wherein: extracting second location information surrounding the first location information further includes:
respectively calculating distance values between all the extracted second position information and the first position information;
and arranging the second position information according to the ascending order of the distance values according to a principle of from near to far.
4. The big data-based address matching method according to claim 3, wherein: judging whether the second location information is located within the delivery range through a take-away platform further comprises:
and comparing the second position information with the distribution range one by one according to the ascending sequence.
5. An address matching system based on big data, characterized in that: the method comprises the following steps:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is configured to acquire a takeout address set by a user;
the analysis module is configured to divide the content included in the takeout address into a first-level address, a second-level address and a third-level address according to a region range;
the second acquisition module is configured to acquire first position information of the user through the intelligent equipment of the user;
the first import module is configured to import the first position information into an electronic map preset by a system;
a first determination module configured to determine whether the take-away address matches the first location information;
the third acquisition module is configured to acquire merchant information from the takeaway platform, wherein the merchant information comprises delivery time and delivery range;
the second judgment module is configured to acquire the current moment and judge whether the current moment is within the distribution time;
the third judging module is configured to judge whether the takeout address is located in the delivery range through a takeout platform;
the second import module is configured to import the distribution range into an electronic map preset by a system;
the first establishing module is configured to establish a first preset range in the electronic map by taking the first position information as a circle center and taking a preset distance as a radius;
the first extraction module is configured to extract second position information around the first position information within the first preset range one by one according to the third-level address, the second-level address and the first-level address;
the fourth acquisition module is configured to acquire third position information of the merchant;
a first calculation module configured to calculate a distance value between the third location information and the first location information;
the second establishing module is configured to establish a second preset range by taking the third position information as a circle center and the distance value as a radius;
a second extraction module configured to extract a difference set of the first preset range and the second preset range;
the fourth judging module is configured to judge whether the second position information is located in the distribution range through a takeout platform;
a modification module configured to list the first location information within the delivery range.
6. The big-data based address matching system as claimed in claim 5, wherein: further comprising:
a third extraction module configured to extract a complement of a second preset range;
a fourth extraction module configured to randomly extract fourth location information from the complementary set;
a fifth judging module configured to judge whether the fourth location information is within the delivery range through a takeout platform.
7. The big-data based address matching system as claimed in claim 6, wherein: further comprising:
the second calculation module is configured to calculate distance values between all the extracted second position information and the first position information respectively;
the sorting module is configured to sort the second position information in an ascending order according to the distance value according to a principle of from near to far.
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| CN110309468A (en) * | 2019-03-29 | 2019-10-08 | 云送(上海)科技有限公司 | A kind of take-away supply system of modifiable coverage |
| CN112101873A (en) * | 2020-09-21 | 2020-12-18 | 口碑(上海)信息技术有限公司 | Order data processing method, device and system |
| CN117349451A (en) * | 2023-12-01 | 2024-01-05 | 广东中思拓大数据研究院有限公司 | Data processing method, data processing apparatus, computer device, and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101339638A (en) * | 2007-07-03 | 2009-01-07 | 周磊 | Method and system for automatic matching of commercial articles dispensing scope and goods receiving address for ordering platform |
| CN103473238A (en) * | 2012-06-08 | 2013-12-25 | 纽海信息技术（上海）有限公司 | Distribution address positioning system and method |
| CN104484790A (en) * | 2014-12-26 | 2015-04-01 | 清华大学深圳研究生院 | Address match method and device of logistics business |
| CN105335877A (en) * | 2015-12-08 | 2016-02-17 | 苏州天擎电子通讯有限公司 | Take-out system |
| CN106651247A (en) * | 2016-11-16 | 2017-05-10 | 成都地图慧科技有限公司 | Address area block matching method based on GIS topology analysis and address area block matching system thereof |
| CN107123012A (en) * | 2016-10-11 | 2017-09-01 | 北京小度信息科技有限公司 | A kind of method and system for automatically selecting ship-to |
| CN108446871A (en) * | 2018-02-09 | 2018-08-24 | 北京三快在线科技有限公司 | A kind of dispatching processing method and processing device of order |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7110964B2 (en) * | 2003-08-29 | 2006-09-19 | Exit41, Inc. | Order processing |
| US20160071050A1 (en) * | 2014-09-04 | 2016-03-10 | Evan John Kaye | Delivery Channel Management |
-
2018
- 2018-10-25 CN CN201811253535.4A patent/CN109447753B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101339638A (en) * | 2007-07-03 | 2009-01-07 | 周磊 | Method and system for automatic matching of commercial articles dispensing scope and goods receiving address for ordering platform |
| CN103473238A (en) * | 2012-06-08 | 2013-12-25 | 纽海信息技术（上海）有限公司 | Distribution address positioning system and method |
| CN104484790A (en) * | 2014-12-26 | 2015-04-01 | 清华大学深圳研究生院 | Address match method and device of logistics business |
| CN105335877A (en) * | 2015-12-08 | 2016-02-17 | 苏州天擎电子通讯有限公司 | Take-out system |
| CN107123012A (en) * | 2016-10-11 | 2017-09-01 | 北京小度信息科技有限公司 | A kind of method and system for automatically selecting ship-to |
| CN106651247A (en) * | 2016-11-16 | 2017-05-10 | 成都地图慧科技有限公司 | Address area block matching method based on GIS topology analysis and address area block matching system thereof |
| CN108446871A (en) * | 2018-02-09 | 2018-08-24 | 北京三快在线科技有限公司 | A kind of dispatching processing method and processing device of order |
Non-Patent Citations (2)
| Title |
|---|
| 地址树模型的中文地址提取方法;亢孟军，杜清运，王明军;《测绘学报》;20150131;99-107 * |
| 基于GIS的动态物流网络***的设计与实现;王雅丹;《中国优秀硕士学位论文全文数据库 信息科技辑》;20180415;I138-1490 * |
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