CN113934948B - Intelligent product recommendation method and system - Google Patents
Intelligent product recommendation method and system Download PDFInfo
- Publication number
- CN113934948B CN113934948B CN202111271471.2A CN202111271471A CN113934948B CN 113934948 B CN113934948 B CN 113934948B CN 202111271471 A CN202111271471 A CN 202111271471A CN 113934948 B CN113934948 B CN 113934948B
- Authority
- CN
- China
- Prior art keywords
- information
- user
- real
- mobile equipment
- acquiring
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 28
- 230000008859 change Effects 0.000 claims description 14
- 238000012544 monitoring process Methods 0.000 claims description 8
- 230000006855 networking Effects 0.000 claims description 3
- 230000002093 peripheral effect Effects 0.000 abstract description 3
- 230000008569 process Effects 0.000 description 8
- 239000011449 brick Substances 0.000 description 6
- 239000004570 mortar (masonry) Substances 0.000 description 6
- 230000001133 acceleration Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 230000005484 gravity Effects 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 238000004590 computer program Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- 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
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention is suitable for the technical field of computers, and particularly relates to an intelligent product recommendation method and system, wherein the method comprises the following steps: acquiring real-time state information of mobile equipment, wherein the real-time state information of the mobile equipment at least comprises position information of the mobile equipment and data information acquired by a sensor; judging whether product recommendation is needed or not according to the real-time state information of the mobile equipment; when product recommendation is needed, acquiring information of nearby offline merchants according to the real-time state information of the mobile equipment, and inquiring corresponding online merchant information; and pushing the online merchant information to the user for reference. According to the invention, the real-time position of the user is calculated according to the position information of the user, so that the information of peripheral merchants is provided for the user according to the state information of the user, the commodity information of the corresponding online merchants is synchronously provided, and the commodity information is recommended to the user, so that the user can conveniently compare the online products with the offline products, and the user can conveniently purchase the products.
Description
Technical Field
The invention belongs to the technical field of computers, and particularly relates to an intelligent product recommendation method and system.
Background
Along with the continuous development of society, electronic products are applied more and more in the life of people. The development of the mobile phone is more and more rapid, and along with the improvement of the intelligent degree of the mobile phone, the mobile phone becomes a window for people to know the world, and people can not leave the mobile phone in clothes, food and residents.
In the current society, online shopping has become an important choice for people to purchase goods. In a network environment, people can directly select online through the network, and after the selection is finished, direct payment is made, and the commodity is mailed to an address set by a buyer.
Certainly, many people like to shop in the brick and mortar store, but the price of the product sold by the brick and mortar store is high due to the increase of the operation cost of the brick and mortar store, and the customer can only see pictures and cannot see the real objects on the network, so that the online and offline comparison cannot be carried out, and the obstacle is caused to the customer to buy the desired product at a lower price.
Disclosure of Invention
The embodiment of the invention aims to provide an intelligent product recommendation method, and aims to solve the problems in the third part of the background art.
The embodiment of the invention is realized in such a way that a product intelligent recommendation method comprises the following steps:
acquiring real-time state information of mobile equipment, wherein the real-time state information of the mobile equipment at least comprises position information of the mobile equipment and data information acquired by a sensor;
judging whether product recommendation is needed or not according to the real-time state information of the mobile equipment;
when product recommendation is needed, acquiring information of nearby offline merchants according to the real-time state information of the mobile equipment, and inquiring corresponding online merchant information;
and pushing the online merchant information to the user for reference.
Preferably, the step of determining whether to recommend the product according to the real-time status information of the mobile device specifically includes:
acquiring the current position of a user according to the position information of the mobile equipment;
acquiring altitude information of a position where a user is located according to the position information of the mobile equipment, and monitoring the change condition of the altitude information;
and when the current position of the user is within a preset radius range around the market, judging that the product recommendation is needed.
Preferably, the step of acquiring information of nearby offline merchants according to the real-time status information of the mobile device and querying corresponding information of online merchants when product recommendation is required includes:
judging the initial floor where the user is located when the user enters the mall according to the change condition of the altitude information;
the method comprises the steps of obtaining floor height information of a shopping mall, and judging a real-time floor where a user is located according to position information of the mobile device and data information collected by a sensor;
and determining offline merchant information near the user according to the position information of the mobile equipment, and synchronously acquiring corresponding online merchant information.
Preferably, the step of pushing the online merchant information to the user for the user to refer to specifically includes:
acquiring information of online merchants, and classifying products sold by the online merchants to obtain classified commodity information;
and sorting the classified commodity information to obtain sorted commodity information, and recommending the first sorted commodity in each category to the user.
Preferably, the step of pushing the online merchant information to the user for the user to refer to further comprises acquiring user identity information.
Preferably, in the step of pushing the online merchant information to the user for reference by the user, the online merchant information is displayed to the user in a thumbnail mode.
Preferably, in the step of querying the corresponding online merchant information, a networking query mode is adopted for querying.
Another object of an embodiment of the present invention is to provide an intelligent product recommendation system, where the system includes:
the information acquisition module is used for acquiring real-time state information of the mobile equipment, wherein the real-time state information of the mobile equipment at least comprises position information of the mobile equipment and data information acquired by a sensor;
the information judgment module is used for judging whether product recommendation is needed or not according to the real-time state information of the mobile equipment;
the information query module is used for acquiring information of nearby offline merchants according to the real-time state information of the mobile equipment and querying corresponding online merchant information when product recommendation is needed;
and the information recommendation module is used for pushing the online merchant information to the user for reference.
Preferably, the information determining module includes:
the position acquisition unit is used for acquiring the current position of the user according to the position information of the mobile equipment;
the altitude acquisition unit is used for acquiring altitude information of the position where the user is located according to the position information of the mobile equipment and monitoring the change condition of the altitude information;
and the judging unit is used for judging that the product recommendation is needed when the current position of the user is within the preset radius range around the market.
Preferably, the information query module includes:
the initial floor determining unit is used for judging the initial floor where the user enters the mall according to the change condition of the altitude information;
the real-time floor determining unit is used for acquiring floor height information of a shopping mall and judging the real-time floor where a user is located according to the position information of the mobile equipment and data information acquired by the sensor;
and the online information acquisition unit is used for determining offline merchant information near the user according to the position information of the mobile equipment and synchronously acquiring corresponding online merchant information.
According to the intelligent product recommendation method provided by the embodiment of the invention, the real-time position of the user is calculated according to the position information of the user, so that the information of peripheral merchants is provided for the user according to the state information of the user, the commodity information of the corresponding online merchants is synchronously provided, and the commodity information is recommended to the user, so that the user can conveniently compare the online products with the offline products, and the user can conveniently purchase the products.
Drawings
Fig. 1 is a flowchart of a product intelligent recommendation method according to an embodiment of the present invention;
fig. 2 is a flowchart of a step of determining whether to recommend a product according to real-time status information of a mobile device according to an embodiment of the present invention;
fig. 3 is a flowchart of a step of acquiring information of nearby offline merchants and querying corresponding information of online merchants according to real-time status information of a mobile device when product recommendation is required according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating steps according to pushing online merchant information to a user for reference according to an embodiment of the present invention;
FIG. 5 is an architecture diagram of a product intelligent recommendation system according to an embodiment of the present invention;
FIG. 6 is an architecture diagram of an information determination module according to an embodiment of the present invention;
fig. 7 is an architecture diagram of an information recommendation module according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It will be understood that, as used herein, the terms "first," "second," and the like may be used herein to describe various elements, but these elements should not be limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script, without departing from the scope of the present application.
In the current society, online shopping has become an important choice for people to purchase goods. In a network environment, people can directly select online through the network, and after the selection is finished, direct payment is made, and the commodity is mailed to an address set by a buyer. Certainly, many people like to shop in the brick and mortar store, but the price of the product sold by the brick and mortar store is high due to the increase of the operation cost of the brick and mortar store, and the customer can only see pictures and cannot see the real objects on the network, so that the online and offline comparison cannot be carried out, and the obstacle is caused to the customer to buy the desired product at a lower price.
In the invention, the real-time position of the user is calculated according to the position information of the user, so that the information of peripheral merchants is provided for the user according to the state information of the user, the commodity information of the corresponding online merchants is synchronously provided, and the commodity information is recommended to the user, so that the user can conveniently compare the online products with the offline products, and the user can conveniently purchase the products.
As shown in fig. 1, a flowchart of a product intelligent recommendation method provided in an embodiment of the present invention is shown, where the method includes:
s100, obtaining real-time state information of the mobile equipment, wherein the real-time state information of the mobile equipment at least comprises position information of the mobile equipment and data information collected by a sensor.
In this step, the real-time status information of the mobile device is obtained, the mobile device may be a mobile phone, in the current mobile device, besides a positioning device, various sensors are further provided, such as a distance sensor, an acceleration sensor, a light sensor, a gyroscope, a magnetic field sensor, and the like, corresponding information can be obtained through the sensors, and in this step, the position information of the mobile device and the data information collected by the sensors are mainly obtained through the positioning device and the acceleration sensor.
And S200, judging whether product recommendation is needed or not according to the real-time state information of the mobile equipment.
In the step, whether product recommendation needs to be carried out is judged according to the real-time state information of the mobile equipment, the real-time position of the user is positioned in the moving process of the user, the user is considered to need to carry out product recommendation when the user is close to the market, and the user is considered to temporarily not need to carry out product recommendation when the user does not reach the market.
S300, when product recommendation is needed, acquiring nearby offline merchant information according to the real-time state information of the mobile device, and inquiring corresponding online merchant information.
In the step, when the user arrives near a market, product recommendation is triggered, nearby offline merchants are determined according to the real-time position of the user, and the offline merchants are taken as destinations to which the user intends to go, so that online merchant information is inquired according to the offline merchant information, most of the commodities sold by the online merchants and the offline merchants are the same, so that the information of the online merchants can be pushed to the user, the user can push high-quality commodities to the user on one hand, the user can compare the online products with the offline products and compare the price difference between the online products and the offline products at the same time, and the user can conveniently purchase satisfied products at a substantial price; and in the step of inquiring the corresponding online merchant information, inquiring in a networking inquiry mode.
And S400, pushing the online merchant information to the user for reference.
In the step, in the pushing process, all commodity information contained in the online merchant information is comprehensively analyzed according to the online merchant information, so that the best product or service is pushed to the user for the user to refer to, and the user can select according to the best product or service; the method comprises the steps of obtaining user identity information to verify the identity of a user before the step of pushing online merchant information to the user for reference by the user; and displaying the online merchant information to the user in a thumbnail mode according to the step of pushing the online merchant information to the user for reference by the user.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of determining whether to recommend a product according to the real-time status information of the mobile device specifically includes:
s201, acquiring the current position of the user according to the position information of the mobile equipment.
In this step, after the location information of the mobile device is obtained, the current location of the user is determined according to the location information, so as to achieve the preliminary determination of the location of the user, that is, the real-time location of the mobile phone is obtained by using a positioning device in the mobile phone, and the location is regarded as the location of the user.
S202, acquiring the altitude information of the position of the user according to the position information of the mobile equipment, and monitoring the change condition of the altitude information.
In the step, the altitude information of the position where the user is located is obtained according to the position information of the mobile equipment, and the map database is inquired according to the position where the user is located, so that the theoretical altitude of the current position where the user is located is obtained through inquiry, the actual altitude of the position where the mobile equipment is located is obtained through the mobile equipment, and the actual altitude is monitored in real time.
S203, when the current position of the user is within the preset radius range around the market, the product recommendation is judged to be needed.
In this step, data information of the shopping mall is entered into a shopping mall database, the data information of the shopping mall at least comprises the number of floors, the height of the floors and the distribution condition of shops on each floor, and then the shopping mall is taken as a center, a circle is drawn by taking the preset length as a radius, when the current position of the user is in a circle with the shopping mall as the center, the user is considered to possibly enter the shopping mall, and then the fact that product recommendation needs to be performed is judged.
As shown in fig. 3, as a preferred embodiment of the present invention, when product recommendation is needed, the step of obtaining information of nearby offline merchants according to the real-time status information of the mobile device, and querying corresponding information of online merchants specifically includes:
and S301, judging the initial floor where the user enters the mall according to the change condition of the altitude information.
In the step, the initial floor where the user is located when entering the market is judged according to the change condition of the altitude information, the altitude where the user is located is determined when the user enters the market, and the floor where the user is located when entering the market is determined according to the altitude.
And S302, acquiring the floor height information of the shopping mall, and judging the real-time floor where the user is located according to the position information of the mobile equipment and the data information acquired by the sensor.
In this step, acquire the floor height information of market, inquire the market database promptly, call out the data information of the market in the market database, the data information of market includes the floor number at least, the floor height and the shop distribution condition of every floor, thereby judge whether the user upstairs or downstairs according to the information that gravity sensor gathered, thereby confirm the real-time floor that the user was located, and through monitoring altitude, in order to assist the real-time floor that judges the user and locate.
S303, determining offline merchant information near the user according to the position information of the mobile equipment, and synchronously acquiring corresponding online merchant information.
In the step, the off-line merchant information near the user is determined according to the position information of the mobile equipment, and the on-line merchant information is inquired according to the off-line merchant information, so that the commodity corresponding to the on-line merchant information is found out for selection.
As shown in fig. 4, as a preferred embodiment of the present invention, the step of pushing the online merchant information to the user for reference specifically includes:
s401, obtaining information of the online merchants, and classifying products sold by the online merchants to obtain information of classified commodities.
In this step, the information of the online merchant is acquired, so that all the acquired product information is classified, and a plurality of groups of classified commodity information are acquired.
S402, sorting the sorted commodity information to obtain sorted commodity information, and recommending the first sorted commodity in each category to the user.
In this step, the sorted commodity information is sorted, the commodities are sorted according to sales volume and browsing volume to obtain sorted commodity information, and the commodity sorted first in each category is recommended to the user.
The main working flow of the invention is as follows: the method comprises the steps that position information of the mobile equipment and data information collected by a sensor are obtained through a positioning device and an acceleration sensor, the real-time position of a user is positioned in the moving process of the user, the user is considered to need product recommendation when the user is close to a place near a market, the user is considered not to need product recommendation temporarily when the user does not reach the place near the market, the product recommendation is triggered when the user reaches the place near the market, a nearby offline merchant is determined according to the real-time position of the user, online merchant information is inquired according to the offline merchant information, online products and offline products can be compared, and in the pushing process, all commodity information contained in the online merchant information is comprehensively analyzed according to the online merchant information, so that the best sold products or services are pushed to the user for reference.
As shown in fig. 5, the product intelligent recommendation system provided by the present invention includes:
the information acquiring module 100 is configured to acquire real-time status information of a mobile device, where the real-time status information of the mobile device at least includes location information of the mobile device and data information collected by a sensor.
In the system, the information obtaining module 100 obtains real-time status information of a mobile device, the mobile device may be a mobile phone, in the current mobile device, besides a positioning device, various sensors are further provided, such as a distance sensor, an acceleration sensor, a light sensor, a gyroscope, a magnetic field sensor, and the like, corresponding information can be obtained through the sensors, and in this step, position information of the mobile device and data information collected by the sensors are mainly obtained through the positioning device and the acceleration sensor.
And the information judgment module 200 is configured to judge whether product recommendation needs to be performed according to the real-time state information of the mobile device.
In the system, the information judgment module 200 judges whether product recommendation needs to be performed according to the real-time state information of the mobile device, positions the real-time position of the user in the moving process of the user, determines that the product recommendation needs to be performed when the user is close to a shopping mall, and determines that the user does not need to perform the product recommendation temporarily when the user does not reach the shopping mall.
The information query module 300 is configured to, when product recommendation needs to be performed, obtain information of nearby offline merchants according to the real-time status information of the mobile device, and query corresponding information of online merchants.
In the system, when a user arrives near a market, the information query module 300 triggers product recommendation, determines nearby offline merchants according to the real-time position of the user, and regards the offline merchants as the destination to which the user intends to go at the moment, so that the information of the online merchants is queried according to the information of the offline merchants.
And the information recommendation module 400 is used for pushing the online merchant information to the user for reference.
In the system, the information recommendation module 400 comprehensively analyzes all commodity information contained in the online merchant information according to the online merchant information in the pushing process, so that the best product or service sold is pushed to the user for the user to refer to, and the user can select according to the best product or service sold.
As shown in fig. 6, as a preferred embodiment of the present invention, the information determining module 200 includes:
a location obtaining unit 201, configured to obtain a current location of the user according to the location information of the mobile device.
In this module, after obtaining the location information of the mobile device, the location obtaining unit 201 determines the current location of the user according to the location information, so as to achieve a preliminary determination of the location of the user, that is, obtain the real-time location of the mobile phone by using a positioning device in the mobile phone, and regard the location as the location of the user.
And the altitude acquisition unit 202 is used for acquiring the altitude information of the position where the user is located according to the position information of the mobile device and monitoring the change condition of the altitude information.
In this module, the altitude acquisition unit 202 acquires altitude information of a location where the user is located according to the location information of the mobile device, and queries the map database according to the location where the user is located, so as to obtain a theoretical altitude of the current location of the user through querying, and further acquire an actual altitude of the location where the mobile device is located by using the mobile device, and monitor the actual altitude in real time.
The determining unit 203 is configured to determine that product recommendation needs to be performed when the current location of the user is within a preset radius range around the mall.
In this module, the determining unit 203 inputs the data information of the market into the market database, the data information of the market at least includes the number of floors, the height of the floors, and the distribution of the shops on each floor, and further draws a circle with the preset length as a radius by using the market as a center, when the current position of the user is in a circle with the market as the center, the user is considered as possibly entering the market, and then it is determined that product recommendation needs to be performed.
As shown in fig. 7, as a preferred embodiment of the present invention, the information query module 300 includes:
the initial floor determining unit 301 is configured to determine, according to a change of the altitude information, an initial floor where the user is located when entering the mall.
In this module, the initial floor determination unit 301 determines the initial floor where the user is located when entering the mall according to the change condition of the altitude information, determines the altitude where the user is located when the user enters the mall, and determines the floor where the user is located when entering the mall according to the altitude.
And the real-time floor determining unit 302 is configured to obtain floor height information of a shopping mall, and determine a real-time floor where the user is located according to the position information of the mobile device and the data information acquired by the sensor.
In this module, real-time floor confirms that unit 302 acquires the floor height information of market, inquire the market database promptly, call out the data information of the market in the market database, the data information of market includes the floor number at least, the shop distribution condition of floor height and every floor, thereby judge whether the user goes upstairs or downstairs according to the information that gravity sensor gathered, thereby confirm the real-time floor that the user located, and through monitoring altitude, in order to assist the real-time floor that judges the user and locate.
And an online information obtaining unit 303, configured to determine offline merchant information near the user according to the location information of the mobile device, and synchronously obtain corresponding online merchant information.
In this module, the online information obtaining unit 303 determines offline merchant information near the user according to the location information of the mobile device, and queries the online merchant information according to the offline merchant information, so as to find out the goods corresponding to the online merchant information for selection.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternatingly with other steps or at least a portion of sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (2)
1. A method for intelligently recommending products is characterized by comprising the following steps:
acquiring real-time state information of mobile equipment, wherein the real-time state information of the mobile equipment at least comprises position information of the mobile equipment and data information acquired by a sensor; judging whether product recommendation is needed or not according to the real-time state information of the mobile equipment; when product recommendation is needed, acquiring information of nearby offline merchants according to the real-time state information of the mobile equipment, and inquiring corresponding online merchant information; pushing the online merchant information to a user for reference by the user;
the step of judging whether to recommend the product according to the real-time state information of the mobile device specifically comprises the following steps: acquiring the current position of a user according to the position information of the mobile equipment; acquiring altitude information of a position where a user is located according to the position information of the mobile equipment, and monitoring the change condition of the altitude information; when the current position of the user is within a preset radius range around a market, judging that product recommendation is needed;
when product recommendation is needed, the steps of obtaining information of nearby offline merchants according to the real-time state information of the mobile device and inquiring corresponding information of online merchants include: judging the initial floor where the user is located when the user enters the mall according to the change condition of the altitude information; the method comprises the steps of obtaining floor height information of a shopping mall, and judging a real-time floor where a user is located according to position information of the mobile device and data information collected by a sensor; determining offline merchant information near the user according to the position information of the mobile equipment, and synchronously acquiring corresponding online merchant information;
the step of pushing the online merchant information to the user for reference by the user specifically comprises the following steps: acquiring information of online merchants, and classifying products sold by the online merchants to obtain classified commodity information; sorting the classified commodity information to obtain sorted commodity information, and recommending the first sorted commodity in each category to a user;
the method comprises the steps of obtaining user identity information before the step of pushing online merchant information to a user for reference, displaying the online merchant information to the user in a thumbnail mode in the step of pushing the online merchant information to the user for reference, and inquiring the corresponding online merchant information in a networking inquiry mode.
2. An intelligent product recommendation system for implementing the intelligent product recommendation method of claim 1, the system comprising: the information acquisition module is used for acquiring real-time state information of the mobile equipment, wherein the real-time state information of the mobile equipment at least comprises position information of the mobile equipment and data information acquired by a sensor; the information judgment module is used for judging whether product recommendation is needed or not according to the real-time state information of the mobile equipment; the information query module is used for acquiring information of nearby offline merchants according to the real-time state information of the mobile equipment and querying corresponding online merchant information when product recommendation is needed; the information recommendation module is used for pushing the online merchant information to the user for reference; the information judgment module comprises: the position acquisition unit is used for acquiring the current position of the user according to the position information of the mobile equipment; the altitude acquisition unit is used for acquiring altitude information of the position where the user is located according to the position information of the mobile equipment and monitoring the change condition of the altitude information; the judging unit is used for judging that the product recommendation is needed when the current position of the user is within a preset radius range around the market; the information inquiry module comprises: the initial floor determining unit is used for judging the initial floor where the user enters the mall according to the change condition of the altitude information; the real-time floor determining unit is used for acquiring floor height information of a shopping mall and judging the real-time floor where the user is located according to the position information of the mobile equipment and the data information acquired by the sensor; and the online information acquisition unit is used for determining offline merchant information near the user according to the position information of the mobile equipment and synchronously acquiring corresponding online merchant information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111271471.2A CN113934948B (en) | 2021-10-29 | 2021-10-29 | Intelligent product recommendation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111271471.2A CN113934948B (en) | 2021-10-29 | 2021-10-29 | Intelligent product recommendation method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113934948A CN113934948A (en) | 2022-01-14 |
| CN113934948B true CN113934948B (en) | 2022-08-05 |
Family
ID=79285022
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111271471.2A Active CN113934948B (en) | 2021-10-29 | 2021-10-29 | Intelligent product recommendation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113934948B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104913779A (en) * | 2015-05-07 | 2015-09-16 | 广东欧珀移动通信有限公司 | Emergency evacuation navigation method and apparatus thereof |
| CN109242651A (en) * | 2018-11-05 | 2019-01-18 | 广州大学 | A kind of commodity intelligent recommendation System and method for based on Internet of Things search |
| CN110490689A (en) * | 2019-07-15 | 2019-11-22 | 广州大学 | It is new to be sold lower consumer's channel behavior routing resource and system |
| CN112700307A (en) * | 2021-01-07 | 2021-04-23 | 董华江 | Commodity recommendation method based on data analysis |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8676937B2 (en) * | 2011-05-12 | 2014-03-18 | Jeffrey Alan Rapaport | Social-topical adaptive networking (STAN) system allowing for group based contextual transaction offers and acceptances and hot topic watchdogging |
| CN103631946A (en) * | 2013-12-11 | 2014-03-12 | 北京光年无限科技有限公司 | Content pushing system based on geographic positions |
| CN105225129B (en) * | 2015-09-16 | 2020-01-31 | 泉州师范学院 | Mobile O2O recommendation method and system thereof |
| CN111738812B (en) * | 2020-08-21 | 2020-12-08 | 深圳索信达数据技术有限公司 | Information pushing method and system based on user group micro-segmentation |
-
2021
- 2021-10-29 CN CN202111271471.2A patent/CN113934948B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104913779A (en) * | 2015-05-07 | 2015-09-16 | 广东欧珀移动通信有限公司 | Emergency evacuation navigation method and apparatus thereof |
| CN109242651A (en) * | 2018-11-05 | 2019-01-18 | 广州大学 | A kind of commodity intelligent recommendation System and method for based on Internet of Things search |
| CN110490689A (en) * | 2019-07-15 | 2019-11-22 | 广州大学 | It is new to be sold lower consumer's channel behavior routing resource and system |
| CN112700307A (en) * | 2021-01-07 | 2021-04-23 | 董华江 | Commodity recommendation method based on data analysis |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113934948A (en) | 2022-01-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9633389B2 (en) | System, method, and non-transitory computer-readable storage media for allowing a customer to place orders remotely and to pick-up the order at a store | |
| AU2016208998B2 (en) | System and method for managing and optimizing delivery networks | |
| AU2020231365A1 (en) | Cashier interface for linking customers to virtual data | |
| JP5782939B2 (en) | Store information provision device | |
| CN108537575A (en) | System and method for vehicle mounted guidance shopping | |
| CN110348868A (en) | Information on services acquisition methods and device | |
| CN112232876A (en) | Accurate marketing method and device based on user scene attribute information | |
| US20180074034A1 (en) | Vehicle Identification System and Associated Methods | |
| CN112488605A (en) | Big data-based product inventory and sales prediction auxiliary system | |
| CN113934948B (en) | Intelligent product recommendation method and system | |
| CN115660524A (en) | E-commerce logistics monitoring method and system | |
| WO2018102141A1 (en) | System and method for determining best venue for selling a vehicle | |
| US20200104899A1 (en) | Systems and methods for automated predictive product procurement | |
| US20180060884A1 (en) | Vehicle Suspension Measurement System and Associated Methods | |
| CN116611796A (en) | Exception detection method and device for store transaction data | |
| CN110648197A (en) | Shop and area combination order-based method in O2O scene | |
| CN113362144B (en) | Big data-based e-commerce shopping recommendation method and system | |
| CN113034789B (en) | Server device, control device, storage medium, mobile store, and method for operating information processing system | |
| US20170148079A1 (en) | System and Method of Providing Customers with In-Store Product Information | |
| CN113052643A (en) | Coupon processing method, system, client and server based on 5G message | |
| JP2002245333A (en) | Store information providing system | |
| KR102004704B1 (en) | Providing method of remarketing information using remarketing system with a connection between online and offline | |
| KR101703737B1 (en) | Prodcut pchasing and deliverying method using a moving market | |
| JP2021033471A (en) | Server device, information processing system, program, mobile store, and method for operating information processing system | |
| JP2020091685A (en) | Information processing device, information processing method, and information processing program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address |
Address after: Room 1201, Building A1, No. 23 Spectral Middle Road, Huangpu District, Guangzhou City, Guangdong Province 510000 Patentee after: Guangzhou Zimai Information Technology Co.,Ltd. Country or region after: China Address before: 511365 room 1015, No. 7, Junwen street, Huangpu District (Zhongxin Guangzhou Knowledge City), Guangzhou City, Guangdong Province (office only) Patentee before: Guangzhou Zimai Information Technology Co.,Ltd. Country or region before: China |
|
| CP03 | Change of name, title or address |