KR20240057498A - A system and method to support services to automatically guide user-customized local restaurants based on location - Google Patents

Abstract

A system supporting a location-based user-customized local restaurant automatic guide service according to an embodiment of the present invention uses a local restaurant recommendation service platform to meet user condition information set by a user located in an area adjacent to the user's current location. A user terminal that receives recommendations for local restaurants; And a platform management server that provides location information of local restaurants that meet user condition information set in the local restaurant service platform, wherein the user condition information includes favorite food, taste, taste, atmosphere, family gatherings, lovers, It is characterized by consisting of at least one of the following categories: local food, customer rating ranking, friendliness, proximity to landmarks, and religious food.

Description

{A system and method to support services to automatically guide user-customized local restaurants based on location}

The present invention relates to a system and method for supporting a location-based, user-customized automatic local restaurant guide service.

Location Based Service (LBS) is a technology that combines the location information of moving users with building, road, and local information to provide additional application services needed by users through mobile communication networks such as mobile phones and PDAs. . Location-based services provide services closely related to real life, such as directions, traffic information, tourist information, real estate information, logistics transportation information, bus/subway route information, and local information, making it possible to create a variety of additional services. do. In addition, with the development of Internet and mobile communication technologies and services and the evolution of mobile communication terminals such as mobile phones, personal digital assistants (PDAs), and laptops, location-based services are becoming one of the technology fields with high growth potential.

By applying these location-based services, systems are emerging that recommend places or predict visits based on similarities in movement patterns, including the time and place of a user's visit. However, since conventional place recommendation and user visit prediction systems perform place recommendation or visit prediction based on the similarity of movement patterns, when a user visits an area other than the main activity area, new visitors from other areas visited by the user may occur. Popular places are recommended or predicted.

However, the places frequented by users who newly visit the area may be different from the places frequented by users who are familiar with the area as their main activity destination. In other words, the conventional location recommendation service recommends places to people who are not familiar with the area, considering only the frequency with which people visit a specific place, but does not provide information about places that people who are mainly active in a specific area actually frequently visit. There are many cases.

In addition, the conventional place recommendation system recommends places to visit or predicts visits to specific places through analysis of similarity of movement patterns through visit profile and location history analysis and fusion with other information such as contact information. On the other hand, the conventional method of predicting places to visit has a problem in that the accuracy of place recommendations and visit predictions decreases when the user visits areas other than the main activity area.

Republic of Korea Patent Publication No. 1020170068978 (2017.06.20, Method and system for operating a restaurant food service and computer-readable recording medium recording this method)

The purpose of the present invention is to provide a system and method for supporting a location-based user-customized local restaurant automatic guide service that can solve conventional problems.

The technical problem to be achieved by the present invention is not limited to the technical problem mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the description below. There will be.

In order to solve the above problem, a system supporting a location-based user-customized local restaurant automatic guide service according to an embodiment of the present invention is set by a user located in an area adjacent to the user's current location using a local restaurant recommendation service platform. A user terminal that receives recommendations for local restaurants that meet user condition information; It includes a platform management server that provides location information of local restaurants that meet user condition information set in the local restaurant service platform, and the user condition information includes favorite food, taste, taste, atmosphere, family gathering, lover, and region. It is characterized by consisting of at least one category among food, customer rating ranking, friendliness, proximity to landmarks, and religious food.

In one embodiment, the platform management server relays a series of information for reserving food pre-orders between the terminal of the local restaurant and the user terminal, and the series of information includes the food order table, payment reservation information, and visitation of the local restaurant. It is characterized by information including scheduled time, etc.

In one embodiment, the platform management server generates and provides a local restaurant tour map containing location information of local restaurants located in a preset local area from the user's location based on user condition information provided by the user terminal. It is characterized by

In one embodiment, the platform management server is characterized by supporting a function for processing payment costs for pre-ordering food from users who plan to visit registered local restaurants and then billing the users later.

In one embodiment, the platform management server recommends search terms for local restaurants mainly searched by other users at the location and/or time based on the user's location information.

In one embodiment, when the number of local restaurants recommended to the user terminal is plural, the platform management server compares the response to comments, number of daily visitors, cost-effectiveness, friendliness, revisit rate, etc. of customers who visited the plurality of local restaurants. It is characterized by providing statistical values as a result.

In one embodiment, the platform management server supports a function for sharing reviews of local restaurants visited by users, customer satisfaction ratings, comments, replies, and other shared information among customers.

In order to solve the above problem, a method of supporting a location-based user-customized local restaurant automatic guidance service according to an embodiment of the present invention includes user information including the user's current location information and user condition information at the user terminal, and local restaurant information. Searching and requesting recommendations; Extracting the user's current location information and local restaurants registered in a preset radius from the platform management server, and then extracting a local restaurant that meets the user condition information from among the extracted local restaurants; If there are a plurality of extracted local restaurants, providing statistical values as a result of comparing the plurality of local restaurants in terms of response to comments from customers who visited the plurality of local restaurants, number of daily visitors, cost-effectiveness, friendliness, and revisit rate; And when one of the recommended local restaurants is selected on the user terminal, the order menu information of the selected local restaurant and the payment cost according to the pre-order of the food to be ordered from the order menu are processed in advance and then billed to the user terminal. Includes.

By using a system and method for supporting a location-based user-customized local restaurant automatic guide service according to an embodiment of the present invention, local restaurants suitable for the customer are provided based on the customer's location information, customer's tendencies, and keywords of customer interest. There is an advantage to being able to recommend it.

Customers who use the above-mentioned service can share information about local restaurants in areas of interest with other customers and form a consensus, and local restaurant operators in each region can generate additional sales revenue by referring to customer reviews. , it provides the advantage of encouraging offline small business owners to come online and increasing the profits of novice online sellers.

Figure 1 is a network configuration diagram of a system supporting a location-based user-customized local restaurant automatic guide service according to an embodiment of the present invention.
Figure 2 is a detailed configuration diagram of the platform management server shown in Figure 1.
Figures 3 and 4 are exemplary diagrams of execution screens of the local restaurant recommendation service platform executed on the user terminal shown in Figure 1.
Figure 5 is a flowchart explaining a method of supporting a location-based user-customized local restaurant automatic guide service according to an embodiment of the present invention.
Figure 6 is a diagram illustrating an example computing environment in which one or more embodiments disclosed herein may be implemented.

Hereinafter, embodiments of the present specification are described with reference to the attached drawings. However, this does not limit the technology described herein to specific embodiments, and should be understood to include various modifications, equivalents, and/or alternatives to the embodiments herein. . In connection with the description of the drawings, similar reference numbers may be used for similar components. In this specification, expressions such as “have,” “may have,” “includes,” or “may include” refer to the presence of the corresponding feature (e.g., a numerical value, function, operation, or component such as a part). , and does not rule out the existence of additional features.

As used herein, expressions such as “A or B,” “at least one of A or/and B,” or “one or more of A or/and B” may include all possible combinations of the items listed together. . For example, “A or B,” “at least one of A and B,” or “at least one of A or B” (1) includes at least one A, (2) includes at least one B, or (3) it may refer to all cases including both at least one A and at least one B.

As used herein, expressions such as “first,” “second,” “first,” or “second,” can modify various components regardless of order and/or importance, and refer to one component. It is only used to distinguish from other components and does not limit the components. For example, a first user device and a second user device may represent different user devices regardless of order or importance. For example, a first component may be renamed a second component without departing from the scope of rights described in this specification, and similarly, the second component may also be renamed to the first component.

A component (e.g., a first component) is “(operatively or communicatively) coupled with/to” another component (e.g., a second component). When referred to as being “connected to,” it should be understood that any component may be directly connected to the other component or may be connected through another component (e.g., a third component). On the other hand, when a component (e.g., a first component) is said to be “directly connected” or “directly connected” to another component (e.g., a second component), the component and the It may be understood that no other component (e.g., a third component) exists between other components.

As used herein, the expression “configured to” may mean, for example, “suitable for,” “having the capacity to,” or “having the capacity to.” ," can be used interchangeably with "designed to," "adapted to," "made to," or "capable of." The term “configured (or set to)” may not necessarily mean “specifically designed to” in hardware. Instead, in some contexts, the expression “a device configured to” may mean that the device is “capable of” working with other devices or components.

For example, the phrase "processor configured (or set) to perform A, B, and C" refers to a processor dedicated to performing the operations (e.g., an embedded processor), or by executing one or more software programs stored on a memory device. , may refer to a general-purpose processor (e.g., CPU or application processor) capable of performing the corresponding operations.

Terms used in this specification are merely used to describe specific embodiments and may not be intended to limit the scope of other embodiments. Singular expressions may include plural expressions, unless the context clearly dictates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as generally understood by a person of ordinary skill in the technical field described herein. Among the terms used in this specification, terms defined in general dictionaries may be interpreted to have the same or similar meaning as the meaning they have in the context of related technology, and unless clearly defined in this specification, have an ideal or excessively formal meaning. It is not interpreted as In some cases, even terms defined in this specification cannot be interpreted to exclude embodiments of this specification.

Hereinafter, based on the attached drawings, a system and method for supporting a location-based user-customized automatic local restaurant guide service according to an embodiment of the present invention will be described in more detail.

Figure 1 is a network configuration diagram of a system supporting a location-based user-customized automatic local restaurant guide service according to an embodiment of the present invention, Figure 2 is a detailed configuration diagram of the platform management server shown in Figure 1, and Figure 3 and FIG. 4 is an example of an execution screen of a local restaurant recommendation service platform executed on the user terminal shown in FIG. 1.

First, as shown in FIG. 1, the system 100 supporting a location-based user-customized automatic local restaurant guide service according to an embodiment of the present invention includes a user terminal 200 and a platform management server 300. do.

Each component can communicate through a network, where the network refers to a connection structure that allows information to be exchanged between each node, such as a plurality of terminals and servers. Examples of such networks include RF, 3GPP (3rd Generation Partnership Project) network, LTE (Long Term Evolution) network, 5GPP (5th Generation Partnership Project) network, WIMAX (World Interoperability for Microwave Access) network, Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area) Network), WAN (Wide Area Network), PAN (Personal Area Network), Bluetooth network, NFC network, satellite broadcasting network, analog broadcasting network, DMB (Digital Multimedia Broadcasting) network, etc., but are not limited thereto. .

In the following, the term at least one is defined as a term including singular and plural, and even if the term at least one does not exist, each component may exist in singular or plural, and may mean singular or plural. This should be self-explanatory. Additionally, whether each component is provided in singular or plural form may vary depending on the embodiment.

The user terminal 200 may be a terminal capable of executing the local restaurant recommendation service platform 10 (eg, web page, app page, program, or application) provided by the platform management server 300, which will be described later.

The user terminal 200 may be a terminal that receives information about local restaurants that meet user condition information set by the user using the local restaurant recommendation service platform 10.

The user terminal 200 may be a terminal that receives information on the number of visitors who wish to visit a local restaurant recommended in accordance with user condition information at the current time.

The user terminal 200 may be a terminal that receives a local area map including a local restaurant route created based on local restaurant information that meets the user condition information, so the user can easily enjoy a local restaurant tour in the desired area. there is.

The user terminal 200 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, a laptop, desktop, laptop, etc. equipped with a web browser. At this time, the user terminal 200 may be implemented as a terminal that can connect to a remote server or terminal through a network.

Additionally, the user terminal 200 may be a terminal that records evaluation comments (likes, dislikes) on local restaurants recommended from the local restaurant recommendation service platform 10 and comments on comments posted by other users.

In addition, the user terminal 200 may be configured to provide expected arrival time information to a local restaurant to be visited using the local restaurant recommendation service platform 10 and to request a pre-order of food to be ordered through the terminal of the local restaurant.

When there are multiple local restaurants recommended by the local restaurant recommendation service platform 10, the user terminal 200 may be a terminal that receives comparative statistics on satisfaction among local restaurants.

The user terminal 200 is, for example, a wireless communication device that guarantees portability and mobility, and includes navigation, personal communication system (PCS), global system for mobile communications (GSM), personal digital cellular (PDC), and PHS ( Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet) terminal , may include all types of handheld-based wireless communication devices such as smartphones, smartpads, tablet PCs, etc.

Next, the platform management server 300 may be configured to provide location information of local restaurants that match the user condition information provided by the user terminal 200.

Additionally, the platform management server 300 may be configured to generate and provide a local restaurant tour map of the corresponding area based on user condition information provided by the user terminal 200.

In addition, the platform management server 300 may be configured to relay a series of information for reserving food pre-orders between the user terminal 200 and the terminal 10 of a local restaurant, where the series of information is of the local restaurant. The information may include food order sheet, payment reservation information, scheduled visit time, etc. Accordingly, the local restaurant's terminal can adjust the food cooking time through the payment reservation information, expected visit time, and pre-order.

More specifically, the platform management server 300 includes a user condition information setting unit 310, a local restaurant registration and management unit 320, a search and recommendation unit 330, an order payment support unit 340, and a comparative statistics unit 350. ), a local restaurant tour map creation unit 360, and a customer evaluation management unit 370.

The user condition information setting unit 310 may be configured to set and register user condition information set by the user for each user.

Here, user condition information may include information including favorite food, taste, taste, atmosphere, family gathering, lover, local food, customer rating ranking, friendliness, proximity to landmarks, religious food, etc.

The local restaurant registration and management unit 320 is configured to register and manage location information of local restaurants by region, and receives update information on change, deletion, and modification of location information of registered restaurants in real time from an external server. You can.

Additionally, the local restaurant registration and management unit 320 may be configured to register and manage location information of restaurants by classifying them according to categories of preset user conditions.

Additionally, the local restaurant registration and management unit 320 may be configured to register and manage terminal information of local restaurants for each registered region and food manual information provided by the terminal. Additionally, the local restaurant registration and management unit 320 may be configured to receive and update food manual update information from the local restaurant's terminal in real time.

Next, the search and recommendation unit 330 searches and filters local restaurants that meet the user condition information set by the user based on the location information of the user terminal, and then selects the top preset local restaurant among the search and filtered results. This may be a recommended configuration.

The search and recommendation unit 330 selects the category and location information in the user condition information as a local search word, searches the database of the local restaurant registration and management unit 320 using the search score for the local search word, and produces a search result. It may be a configuration that extracts .

Here, the category for each of the plurality of local search terms may be determined using a Natural Language Understanding (NLU) model. That is, using the determined category, a plurality of local search words can be classified into one category among the plurality of categories. Then, local restaurants that match the user's condition information are searched and recommended within the search category of the geographic area corresponding to the user's location information.

Meanwhile, the search and recommendation unit 330 may recommend search terms for local restaurants mainly searched by other users at the location and/or time based on the user's location information.

Next, the order prepayment support unit 340 processes payment costs for pre-ordering food from users who plan to visit local restaurants registered in the local restaurant registration and management unit 320, and then charges the users later. It may be a configuration that supports the function for.

Next, when the number of local restaurants recommended by the user terminal is plural, the local restaurant comparison statistics unit 350 calculates response to comments from customers who visited the plurality of local restaurants, number of daily visitors, cost-effectiveness, friendliness, revisit rate, etc. It may be a configuration that provides statistical values as a result of comparing .

Next, the local restaurant tour map generator 360 may be configured to generate and provide a regional restaurant tour map of local restaurants that meet or match user condition information.

The customer evaluation management unit 370 may be configured to support a function for sharing reviews of local restaurants visited by the user, customer satisfaction ratings, comments, replies, and other shared information among customers.

The customer evaluation management unit 370 determines the comment entered from the user terminal 200 as a comment with a positive influence or a comment with a negative influence based on the review information, and then provides a function to revoke the comment writing permission if it is determined to be a comment with a negative influence. can be provided.

Additionally, the customer evaluation management unit 370 may collect activity information of each customer by crawling comments posted by customers.

For example, the customer's activity information is collected based on the customer's SNS account information, such as customer A's social media account information, blog account information, or video site account information. Here, the activity information includes the number of customer comments and the positive and negative tendencies of the comments.

In addition, images, videos, or text included in comments and SNS can be extracted to create a database of the content posted by the customer, and the types and components of the content (e.g., images, videos, texts, etc.) By analyzing the arrangement of components, you can analyze the format of content and comments frequently used or registered by the customer.

Additionally, feedback from other users linked to content posted by the customer can be collected and the amount of feedback and the content of the feedback (for example, feedback tendency (positive or negative), etc.) can be analyzed.

In addition, the amount of feedback and the content of the feedback can be used to analyze the customer's feedback trend by content category, feedback trend by content content, or feedback trend by content format in connection with the content category, content content, or content format.

For example, the number of comment views for each restaurant business or service product of the restaurant business (e.g., number of visits, average number of visits in a period, number of views, average number of views in a period, etc.), number of content feedback (e.g., comments, retweets, ' Analytical information can be generated by analyzing at least one of 'likes', etc.) and feedback tendencies (for example, positive or negative).

Meanwhile, the platform management server 300 disclosed herein purifies unstructured data, structured data, and semi-structured data contained in stored raw data to build big data, and meta-structures data. Preprocessing including classification can be performed on the data, and analysis including data mining can be performed on the preprocessed data. Additionally, the analyzed data can be visualized and output. At this time, data mining involves classification, which explores the inherent relationships between preprocessed data and learns a training data set with a known class to predict the class of new data, or clustering, which groups data based on similarity without class information. Clustering) can be performed. Of course, various other mining methods may exist, and mining may be done differently depending on the type of big data collected and stored or the type of query to be requested later. Big data constructed in this way can also go through a verification process using artificial neural network deep learning or machine learning.

At this time, the artificial neural network may use a CNN (Convolutional neural network) structure. CNN is a network structure using convolutional layers and is suitable for image processing. It uses image data as input to classify images based on features within the image. Because you can.

Additionally, text mining is a technology aimed at extracting and processing useful information from unstructured/semi-structured text data based on natural language processing technology. Through text mining technology, you can extract meaningful information from a large amount of text, identify connections with other information, find categories of text, and obtain results that go beyond simple information retrieval. Using this, in the safe transaction service according to an embodiment of the present invention, large-capacity language resources and statistical and regular algorithms can be used to analyze identifiers or natural language input as a query and discover information hidden therein.

In addition, the customer demand analysis system 100 disclosed herein stores collected raw data, which is big data, in parallel and distributed, and unstructured data, structured data, and unstructured data included in the stored raw data. Semi-structured data can be refined, pre-processed including classification into metadata, and analyzed including data mining on the pre-processed data. The analyzed data can then be visualized and output. there is.

Figure 5 is a flowchart explaining a method of supporting a location-based user-customized local restaurant automatic guide service according to an embodiment of the present invention.

Referring to FIG. 5, the method (S700) for supporting a location-based user-customized local restaurant automatic guide service according to an embodiment of the present invention is to provide user information including the user's current location information and user condition information at the user terminal. When requesting local restaurant search and recommendation (S710), the platform management server 300 extracts the user's current location information and local restaurants registered in a preset radius, and then matches the user condition information among the extracted local restaurants. Local restaurants are extracted (S720), and if there are multiple extracted local restaurants, statistics are obtained by comparing the response to comments from customers who visited the plurality of local restaurants, number of daily visitors, cost-effectiveness, friendliness, and revisit rate. Provided (S730).

Afterwards, when one of the local restaurants recommended in the user terminal 200 is selected, the order menu information of the selected local restaurant and the payment cost according to the pre-order of the food to be ordered from the order menu are processed in advance, and then sent to the user terminal. Includes the process of making a claim (S740).

Meanwhile, the method (S700) for supporting a location-based user-customized automatic guide to nearby restaurants according to an embodiment of the present invention includes a local area map including a route to a local restaurant created based on local restaurant information that meets the user condition information. It may further include the step of providing.

The platform management server 300 provides location information of local restaurants that match the user condition information provided by the user terminal 200, and local restaurants in the corresponding area based on the user condition information provided by the user terminal 200. It may be configured to generate and provide a tour map and relay a series of information for reserving food pre-orders between the user terminal 200 and the terminal 10 of a local restaurant, where the series of information includes the food of the local restaurant. The information may include an order table, payment reservation information, scheduled visit time, etc. Accordingly, the local restaurant's terminal can adjust the food cooking time through the payment reservation information, expected visit time, and pre-order.

More specifically, the platform management server 300 may be configured to set and register user condition information set by the user for each user. Here, user condition information may include information including favorite food, taste, taste, atmosphere, family gathering, lover, local food, customer rating ranking, friendliness, proximity to landmarks, religious food, etc.

In addition, it is a configuration that registers and manages location information of local restaurants for each region, and may be configured to receive update information on change, deletion, and modification of location information of registered restaurants in real time from an external server.

In addition, it may be configured to register and manage location information of restaurants by classifying them according to categories of preset user conditions.

Additionally, it may be configured to register and manage terminal information of local restaurants in each registered region and food manual information provided by the terminal. Additionally, the local restaurant registration and management unit 320 may be configured to receive and update food manual update information from the local restaurant's terminal in real time.

In addition, it may be configured to search and filter local restaurants that meet the user condition information set by the user based on the location information of the user terminal, and then recommend the top preset local restaurants among the searched and filtered results.

In addition, the category and location information in the user condition information may be selected as a local search word, searched in the database of the local restaurant registration and management unit 320 using the search score for the local search word, and search results may be extracted. .

Here, the category for each of the plurality of local search terms may be determined using a Natural Language Understanding (NLU) model. That is, using the determined category, a plurality of local search words can be classified into one category among the plurality of categories. Then, local restaurants that match the user's condition information are searched and recommended within the search category of the geographic area corresponding to the user's location information.

Additionally, based on the user's location information, search terms for local restaurants commonly searched by other users in that location and/or time can be recommended.

In addition, it may be configured to support a function for processing payment costs for pre-ordering food from users who plan to visit registered local restaurants and then billing the users later.

In addition, if the number of local restaurants recommended by the user terminal is multiple, statistics may be provided as a result of comparing the response to comments, number of daily visitors, cost-effectiveness, friendliness, revisit rate, etc. of customers who visited the multiple local restaurants. there is.

In addition, it may be configured to generate and provide a local restaurant tour map at the regional level with local restaurants that meet or match user condition information.

Additionally, it may be configured to support a function for sharing reviews of local restaurants visited by the user, customer satisfaction evaluations, comments, replies, and other shared information among customers.

In addition, a comment input from the user terminal 200 is judged to be a comment with a positive influence or a comment with a negative influence based on the review information, and if it is determined to be a comment with a negative influence, a function to revoke comment writing permission may be provided.

Additionally, you can collect activity information about each customer by crawling the comments posted by customers.

For example, the customer's activity information is collected based on the customer's SNS account information, such as customer A's social media account information, blog account information, or video site account information. Here, the activity information includes the number of customer comments and the positive and negative tendencies of the comments.

In addition, images, videos, or text included in comments and SNS can be extracted to create a database of the content posted by the customer, and the types and components of the content (e.g., images, videos, texts, etc.) By analyzing the arrangement of components, you can analyze the format of content and comments frequently used or registered by the customer.

Additionally, feedback from other users linked to content posted by the customer can be collected and the amount of feedback and the content of the feedback (for example, feedback tendency (positive or negative), etc.) can be analyzed.

In addition, the amount of feedback and the content of the feedback can be used to analyze the customer's feedback trend by content category, feedback trend by content content, or feedback trend by content format in connection with the content category, content content, or content format.

For example, the number of comment views for each restaurant business or service product of the restaurant business (e.g., number of visits, average number of visits in a period, number of views, average number of views in a period, etc.), number of content feedback (e.g., comments, retweets, ' Analytical information can be generated by analyzing at least one of 'likes', etc.) and feedback tendencies (for example, positive or negative).

By using a system and method for supporting a location-based user-customized local restaurant automatic guide service according to an embodiment of the present invention, local restaurants suitable for the customer are provided based on the customer's location information, customer's tendencies, and keywords of customer interest. There is an advantage to being able to recommend it.

Customers who use the above-mentioned service can share information about local restaurants in areas of interest with other customers and form a consensus, and local restaurant operators in each region can generate additional sales revenue by referring to customer reviews. , it provides the advantage of encouraging offline small business owners to come online and increasing the profits of novice online sellers.

6 is a diagram illustrating an example computing environment in which one or more embodiments disclosed herein may be implemented, and is an illustration of a system 1000 that includes a computing device 1100 configured to implement one or more embodiments described above. shows. For example, computing device 1100 may include a personal computer, server computer, handheld or laptop device, mobile device (mobile phone, PDA, media player, etc.), multiprocessor system, consumer electronics, minicomputer, mainframe computer, Distributed computing environments including any of the above-described systems or devices, etc. are included, but are not limited thereto.

Computing device 1100 may include at least one processing unit 1110 and memory 1120. Here, the processing unit 1110 may include, for example, a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), etc. and can have multiple cores.

Memory 1120 may be volatile memory (eg, RAM, etc.), non-volatile memory (eg, ROM, flash memory, etc.), or a combination thereof. Additionally, computing device 1100 may include additional storage 1130. Storage 1130 includes, but is not limited to, magnetic storage, optical storage, etc. The storage 1130 may store computer-readable instructions for implementing one or more embodiments disclosed in this specification, and other computer-readable instructions for implementing an operating system, application program, etc. may also be stored. Computer-readable instructions stored in storage 1130 may be loaded into memory 1120 for execution by processing unit 1110. Computing device 1100 may also include input device(s) 1140 and output device(s) 1150.

Here, the input device(s) 1140 may include, for example, a keyboard, mouse, pen, voice input device, touch input device, infrared camera, video input device, or any other input device, etc. Additionally, output device(s) 1150 may include, for example, one or more displays, speakers, printers, or any other output devices. Additionally, the computing device 1100 may use an input device or output device provided in another computing device as the input device(s) 1140 or the output device(s) 1150. Additionally, computing device 1100 may include communication connection(s) 1160 that allows computing device 1100 to communicate with another device (e.g., computing device 1300).

Here, communication connection(s) 1160 may include a modem, network interface card (NIC), integrated network interface, radio frequency transmitter/receiver, infrared port, USB connection, or other device for connecting computing device 1100 to another computing device. May contain interfaces. Additionally, communication connection(s) 1160 may include a wired connection or a wireless connection. Each component of the computing device 1100 described above may be connected by various interconnections such as buses (e.g., peripheral component interconnect (PCI), USB, firmware (IEEE 1394), optical bus structure, etc.) and may be interconnected by a network 1200. As used herein, terms such as "component", "system", etc. generally refer to computer-related entities that are hardware, a combination of hardware and software, software, or software in execution.

The present invention is not limited to the above-described embodiments and attached drawings. For those skilled in the art to which the present invention pertains, it will be clear that components according to the present invention can be replaced, modified, and changed without departing from the technical spirit of the present invention.

100: A system that supports location-based, user-customized automatic local restaurant guidance service
200: Customer terminal
300: Platform management server
310: User condition information setting unit
320: Local restaurant registration and management department
330: Search and recommendation section
340: Order payment support department
350: Department of Comparative Statistics
360: Local restaurant tour map creation unit
370: Customer evaluation management department

Claims (8)

A user terminal that receives recommendations for local restaurants that meet user condition information set by the user located in an area adjacent to the user's current location using a local restaurant recommendation service platform;
It includes a platform management server that provides location information of local restaurants that meet user condition information set in the local restaurant service platform,
The user condition information is a location-based user characterized in that it consists of at least one category of favorite food, taste, taste, atmosphere, family gathering, lover, local food, customer rating ranking, friendliness, proximity to landmark, and religious food. A system that supports customized local restaurant automatic guide service.
According to paragraph 1,
The platform management server is
Relaying a series of information for reserving food pre-orders between the terminal of the local restaurant and the user terminal,
A system that supports a location-based user-customized automatic local restaurant guide service, characterized in that the series of information includes the food order sheet, payment reservation information, and scheduled visit time of the local restaurant.
According to paragraph 1,
The platform management server is
A location-based user-customized local, characterized in that it generates and provides a local restaurant tour map containing location information of local restaurants located in a preset local area from the user's location based on user condition information provided by the user terminal. A system that supports automatic restaurant information service.
According to paragraph 1,
The platform management server is
We support a location-based user-customized local restaurant automatic guide service, which is characterized by supporting a function to bill users later after pre-ordering food from users who plan to visit registered local restaurants. A system that does.
According to paragraph 1,
The platform management server is
A system that supports a location-based user-customized automatic local restaurant guide service, characterized by recommending search terms for local restaurants mainly searched by other users in that location and/or time based on the user's location information.
According to paragraph 1,
The platform management server is
When the number of local restaurants recommended by the user terminal is plural, statistics are provided as a result of comparing the response to comments, number of daily visitors, cost-effectiveness, friendliness, revisit rate, etc. of customers who visited the plurality of local restaurants. A system that supports location-based, user-customized automatic local restaurant guidance service.
According to paragraph 1,
The platform management server is
A system that supports a location-based user-customized local restaurant automatic guide service, characterized by supporting functions for sharing reviews of local restaurants visited by users, customer satisfaction evaluations, comments, replies, and other shared information among customers. .
Requesting local restaurant search and recommendation along with user information including the user's current location information and user condition information at the user terminal;
Extracting the user's current location information and local restaurants registered in a preset radius from the platform management server, and then extracting a local restaurant that meets the user condition information from among the extracted local restaurants; and
If there are a plurality of extracted local restaurants, providing statistical values as a result of comparing the plurality of local restaurants in terms of response to comments from customers who visited the plurality of local restaurants, number of daily visitors, cost-effectiveness, friendliness, and revisit rate; and
When selecting one of the recommended local restaurants on the user terminal, it includes the step of processing the order menu information of the selected local restaurant and the payment cost according to the pre-order of the food to be ordered from the order menu, and then billing the user terminal. A method of supporting a location-based, user-customized automatic local restaurant guide service.