KR102123324B1 - System and Method for Recommending Optimal moving line based on User preferences - Google Patents

Abstract

The optimal moving line recommendation system based on user preference according to an aspect of the present invention extracts a plurality of keywords from an external message received from the outside or an internal message generated from the outside, and extracts user association information including the extracted plurality of keywords. A user-related information collection unit to be generated; A user preference analysis unit generating user preference data by analyzing the user association information; When entering a specific area including a plurality of places, the place of interest determining unit for determining at least one of the plurality of places as the place of interest using the user preference data; And a recommended moving line determining unit determining at least one moving line among the plurality of moving lines connecting the at least one point of interest and the current location of the user as a recommended moving line.

Description

System and Method for Recommending Optimal moving line based on User preferences}

The present invention relates to a user preference-based service, and more particularly, to an optimal circulation recommendation based on a user preference.

Recently, various types of route search services have been provided. The route search service provides the optimal route to the destination entered by the user based on the user's current location.

It is common for most route search services to simply provide a route with a minimum travel time for a user to move from a current position to a destination or a route with a minimum travel distance for a user to move from a current position to a destination as an optimal route.

However, the user may want to go to a destination that he or she usually has interest or prefers while traveling to a destination. To this end, there is a hassle of retrieving whether the point of interest exists or the location of the point of interest several times from a plurality of paths that the user can move from the current location to the destination.

Also, a user can visit a plurality of places of interest within a specific area. To this end, the user has to search multiple times for a plurality of places of interest within a specific area. In addition, the user has to make a lot of effort to search for locations of points of interest existing within a specific area and select a route to visit them.

The present invention is to solve the above-mentioned problems, and to provide an optimal moving line recommendation system and method based on user preference that can recommend an optimal moving line through which a user can visit a plurality of places of interest within a specific area. This is a technical task.

An optimal circulation recommendation system based on user preference according to an aspect of the present invention for achieving the above object extracts a plurality of keywords from an external message received from the outside or an internal message generated from the outside, and extracts the extracted multiple keywords A user association information collection unit for generating user association information including; A user preference analysis unit generating user preference data by analyzing the user association information; When entering a specific area including a plurality of places, the place of interest determining unit for determining at least one of the plurality of places as the place of interest using the user preference data; And a recommended moving line determining unit determining at least one moving line among the plurality of moving lines connecting the at least one point of interest and the current location of the user as a recommended moving line.

In one embodiment, the external message includes transaction information and conversation information consisting of at least one of POI information, transaction time, product information, and service information in which the transaction has been performed, and the internal message includes search information input by the user. Or, it characterized in that it comprises the evaluation information for at least one of the POI information, the product information, the service information input by the user.

In one embodiment, the user preference data includes category information indicating information classifying places, products, and services into a plurality of categories, and preferences indicating preferences for places, products, and services classified according to the category information. It is characterized by including information.

In one embodiment, the user preference analysis unit determines a preference based on the frequency of related keywords for each of places, products, and services classified according to the category information.

In another embodiment, the user preference analysis unit determines a preference based on frequency and evaluation information of related keywords for each of places, products, and services classified according to the category information.

In one embodiment, the user preference analysis unit is characterized by determining preferences for the plurality of categories for each time zone or environment.

In one embodiment, the place of interest determining unit is characterized in that, among the plurality of places located in the specific region, the place where the preference information included in the user preference data is greater than a predetermined value is determined as the place of interest.

In one embodiment, the recommended moving line determining unit determines that at least one moving line having a short moving distance of the user is a recommended moving line among a plurality of moving lines connecting the at least one point of interest and the current location of the user. .

In another embodiment, the recommended moving line determining unit selects a place corresponding to a category having a high preference in a time zone corresponding to the current time, and among the plurality of moving lines connecting the at least one point of interest and the user's current location It is characterized in that the moving lines having the fastest visit order of the selected place are extracted, and at least one moving line having a short user movement distance is determined as a recommended moving line among the extracted moving lines.

In one embodiment, the recommended moving line determining unit is characterized in that periodically checking the position, and changing the recommended moving line using the identified position.

In order to achieve the above object, the method for recommending optimal circulation based on user preference according to another aspect of the present invention extracts a plurality of keywords from an external message received from the outside or an internal message generated from the outside, and extracts the extracted multiple keywords. Generating user association information based on the basis; Generating user preference data by analyzing the user association information; When entering a specific area including a plurality of places, determining at least one of the plurality of places as a place of interest using the user preference data; And displaying at least one copper wire among the plurality of copper wires connecting the at least one point of interest and the current location of the user as a recommended copper wire.

In one embodiment, the step of displaying the recommended moving line includes: calculating a plurality of moving lines connecting the at least one place of interest and the current location of the user; And selecting at least one of the plurality of copper wires based on at least one of a current time, a current location, and a user moving distance, and displaying the selected at least one copper wire as a recommended copper wire.

In one embodiment, the external message includes transaction information and conversation information consisting of at least one of POI information, transaction time, product information, and service information in which the transaction has been performed, and the internal message includes search information input by the user. Or, it characterized in that it comprises the evaluation information for at least one of the POI information, the product information, the service information input by the user.

In one embodiment, the user preference data includes category information indicating information classifying places, products, and services into a plurality of categories, and preferences indicating preferences for places, products, and services classified according to the category information. It is characterized by including information.

In one embodiment, the step of generating the user preference data comprises determining a preference based on at least one of frequency and evaluation information of related keywords for each of places, products, and services classified according to the category information. It is characterized by.

In one embodiment, the step of generating the user preference data is characterized by determining preferences for the plurality of categories for each time zone or environment.

In one embodiment, the step of generating the user preference data is characterized in that the user preference data is generated using an internal analysis module.

In one embodiment, the step of generating the user preference data comprises: dividing the user association information into a plurality of analysis segments and transmitting the plurality of analysis segments to a plurality of external terminals; And receiving a plurality of analysis result segments from the plurality of external terminals, and generating the user preference data based on the received plurality of analysis result segments.

According to the present invention, it is possible to select places of interest preferred by a user within a specific area in consideration of user preferences, and recommend the optimal circulation for visiting them. Accordingly, the present invention does not require an effort for the user to search several times whether places of interest are located in a specific area, and to select a copper wire in consideration of their locations. That is, the user convenience of the present invention can be improved.

In addition, the present invention determines the user preference by analyzing an external message received by the user terminal or an internal message directly input by the user, so the accuracy of the user preference is high. Accordingly, the present invention can improve the reliability of the service.

In addition, the present invention can use a plurality of external terminals located in a specific area in analyzing user preferences. Accordingly, the present invention can provide a service even in a user terminal having low specification hardware, and improve service processing speed.

In addition, according to the present invention, the recommended moving line can be determined and changed in consideration of the preference of the category for each time zone or environment, thereby providing the optimal moving line to the user.

In addition, the present invention is capable of all processing within a user terminal without going through a separate server. Since the present invention does not need to build a separate server, it is possible to reduce the server construction cost and maintenance cost.

1 is a view for explaining an optimal moving line recommendation system based on user preferences according to an embodiment of the present invention.
FIG. 2 is a block diagram schematically showing the configuration of the user terminal illustrated in FIG. 1.
3 is a diagram for describing category information and preference information corresponding to each of a plurality of places located in a specific area.
4 is a view showing an example of a recommended copper wire.
5 is a view showing another example of a recommended copper wire.
6 is a flowchart illustrating a method for recommending optimal circulation based on user preferences according to an embodiment of the present invention.

The present invention can be applied to a variety of transformations and may have various embodiments, and specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all conversions, equivalents, and substitutes included in the spirit and scope of the present invention. In the description of the present invention, if it is determined that a detailed description of known technologies related to the present invention may obscure the subject matter of the present invention, the detailed description will be omitted.

Terms such as first and second may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from other components.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise.

In this specification, terms such as “include” or “have” are intended to indicate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, or one or more other. It should be understood that features or numbers, steps, operations, components, parts or combinations thereof are not excluded in advance.

In addition, in the present specification, when one component'transmits' data to another component, the component may directly transmit the data to the other component, or through at least one other component It means that the data may be transmitted to the other components. Conversely, when one component'directly transmits' data to another component, it means that the data is transmitted from the component to the other component without passing through the other component.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings. The same reference numerals in each drawing denote the same members.

FIG. 1 is a diagram for explaining a system for recommending optimal circulation based on user preferences according to an embodiment of the present invention, and FIG. 2 is a block diagram schematically showing the configuration of the user terminal illustrated in FIG. 1.

Referring to FIG. 1, an optimal moving line recommendation system 100 based on user preferences according to an embodiment of the present invention includes a user terminal 110 and an information providing server 140.

The user terminal 110 analyzes the preferences of the user who uses the terminal 110. When the user terminal 110 enters the specific region 120, the user terminal 110 is preferred by the user among a plurality of places 120a, 120b, ..., 120h located in the specific region 120 It is recommended to the user for the optimal circulation for the places.

To this end, the user terminal 110, as shown in Figure 2, the receiving unit 210, the input unit 220, the user-related information collection unit 230, the user preference analysis unit 240, the database 250, the area It may include a sensing unit 260, a place of interest determining unit 270, a moving line calculation unit 280, a recommended moving line determination unit 290, an additional information acquisition unit 310, and a moving line display unit 320.

The receiving unit 210 receives an external message from the outside. The external message may be a short text message, a long text message, a message received through an application, or a mail. The external message may include at least one of transaction information and conversation information. At this time, the transaction information may include at least one of point of interest (POI) information, transaction time, product information, and service information in which the transaction has been performed.

The input unit 220 receives input from a user and generates an internal message. The input unit 220 may generate an internal message by receiving text from a user through a virtual keyboard displayed on a touch screen. The internal message may include POI, product, service, and evaluation information of at least one in which the transaction has been performed. Here, the POI may indicate an online or offline store where a user purchases a product or service. The internal message may include conversation information entered by the user in the message window or search information entered by the user in the search window.

The user association information collection unit 230 collects information associated with the user through the reception unit 210 and the input unit 220.

More specifically, the user association information collection unit 230 collects external messages received through the reception unit 210. The user association information collection unit 230 parses an external message to extract a plurality of keywords related to at least one of places, products, and services.

When the external message is transaction information, the user association information collection unit 230 may extract at least one of point of interest (POI) information, transaction time, product information, and service information in which the transaction included in the transaction information is processed as a keyword. have.

When the external message is conversation information, the user-related information collection unit 230 may extract at least one of places, products, and services from the conversation information as keywords. For example, if the conversation information is'meet in A cafe', the user-related information collection unit 230 may extract'A cafe' as a keyword.

The user association information collection unit 230 generates user association information including a plurality of extracted keywords, and provides the generated user association information to the user preference analysis unit 240.

In addition, the user-related information collection unit 230 collects an internal message input through the input unit 220. The user association information collection unit 230 parses an internal message to extract a plurality of keywords related to at least one of places, products, and services.

When the internal message is evaluation information for the POI, product, service, and at least one in which the transaction has been performed, the user-related information collection unit 230 may extract at least one of POI, product, service, and evaluation from the evaluation information as keywords. .

When the internal message is conversation information, the user-related information collection unit 230 may extract at least one of places, products, and services from the conversation information as keywords. For example, the conversation information is'too sleepy. If you want to drink coffee,' the user-related information collection unit 230 may extract'coffee' as a keyword. For another example, when the conversation information is'the clock is broken', the user-related information collection unit 230 may extract the'clock' as a keyword.

The user association information collection unit 230 generates user association information including a plurality of extracted keywords, and provides the generated user association information to the user preference analysis unit 240.

The user preference analysis unit 240 generates user preference data by analyzing user association information. User preference data may include category information and preference information as shown in FIG. 3. The category information may include information classifying places, products, and services.

The user preference analysis unit 240 may classify places, products, and services into a plurality of categories.

In one embodiment, the user preference analysis unit 240 may classify places, products, and services into a first category and a second category. In this case, the first category may be a plurality, and the second category may be a sub-category for each of the plurality of first categories. For example, the first category may include eating out, dessert, shopping, beauty, alcoholic beverage, tourism, education, medical care, leisure, and the like. The second category may include Korean, Chinese, Japanese, Western food, etc. with respect to eating out. Alternatively, the second category may include shoes, watches, clothing, household appliances, furniture, bedding, etc. for shopping.

In one embodiment, the user preference analysis unit 240 may classify places, products, and services into a first category, a second category, and a third category. At this time, the third category may indicate a name for a place or a place for selling a product or service. For example, it may represent a'a' food store, a'b' cafe, a'c' clothing store, and the like.

The user preference analysis unit 240 determines preferences for places, products, and services classified according to category information.

In one embodiment, the user preference analysis unit 240 may determine preferences based on the frequency of keywords associated with each of places, products, and services classified according to category information. The user preference analysis unit 240 may receive user association information including a plurality of keywords from the user association information collection unit 230. The user preference analysis unit 240 may analyze keywords included in the user association information to specify at least one of places, products, and services classified according to category information. The user preference analysis unit 240 may increase the preference of a specified place, product or service. At this time, the preference may indicate the frequency of keywords related to the place, product or service, but is not necessarily limited thereto.

In one embodiment, the user preference analysis unit 240 may determine preferences based on the frequency and cumulative period of keywords associated with each of places, products, and services classified according to category information. The user preference analysis unit 240 may set a period for calculating the frequency of keywords. For example, the user preference analysis unit 240 may determine the frequency of keywords associated with each of places, products, and services classified according to category information within the past 30 days as preferences.

In one embodiment, the user preference analysis unit 240 may determine preferences based on the frequency of keywords related to the locations, products, and services classified according to the category information and evaluation information on the keywords related thereto. The user preference analysis unit 240 may analyze keywords included in the user association information to specify at least one of places, products, and services classified according to category information. The user preference analysis unit 240 may increase or decrease the preference of a specific place, product or service according to the evaluation information. The user preference analysis unit 240 may decrease the preference of the specified place, product or service if the evaluation information for the specified place, product or service has a relatively low value. On the other hand, the user preference analysis unit 240 may increase the preference of the specified place, product or service if the evaluation information for the specified place, product or service has a relatively high value.

For example, the user preference analysis unit 240 may identify the A food store by analyzing the first keyword. The user preference analysis unit 240 may check the evaluation information for the A food store, and if the evaluation information is 2 out of 5, the preference of the A food store may be reduced by 1.

Meanwhile, the user preference analysis unit 240 may analyze the second keyword to specify the B food store. The user preference analysis unit 240 may check the evaluation information for the B food store and increase the preference of the B food store by 1 if the evaluation information is 4 out of 5 points.

Furthermore, the user preference analysis unit 240 may increase or decrease in proportion to the relative value of the evaluation information. The user preference analysis unit 240 may analyze the third keyword to specify the C food store. The user preference analysis unit 240 may check the evaluation information for the C food store, and increase the preference of the C food store by 2 if the evaluation information is 5 out of 5 points.

In one embodiment, the user preference analysis unit 240 may determine a category preference for each time zone. The user preference analysis unit 240 may determine a category preference for each time zone using keywords related to time among keywords included in user association information.

For example, the user related information may include keywords '14:00' and'cafe'. In this case, the user preference analysis unit 240 may increase the preference for the category dessert at 14 o'clock.

For another example, the user-related information may include keywords '18:20' and'Chinese house'. In this case, the user preference analysis unit 240 may increase the preference for catering out at 18.

In one embodiment, the user preference analysis unit 240 may determine the preference of the category according to the environment. The user preference analysis unit 240 may acquire current environment information. The user preference analysis unit 240 may analyze keywords included in the user association information to specify at least one of places, products, and services classified according to category information. The user preference analysis unit 240 may increase the preference for a category of a place, product, or service specified in the current environment.

For example, the user preference analysis unit 240 may acquire current temperature information. If the current temperature information is '38 degrees', and the specified place, product or service category is shopping or air conditioning, the user preference analysis unit 240 may increase the preference for'air conditioner' on a hot day.

The user preference analysis unit 240 stores category information and preference information for places, products, and services in the database 250.

Meanwhile, FIG. 2 illustrates that the user preference analysis unit 240 provided in the user terminal 110 determines preferences of each of places, products, and services classified according to category information, but is not limited thereto.

In another embodiment, the user terminal 110 may determine the preference of each of places, products, and services classified according to category information using the external terminal 130.

More specifically, the user terminal 110 may divide user-related information into a plurality of analysis segments. The user terminal 110 may transmit a plurality of analysis segments to a plurality of external terminals 130. In this case, the plurality of external terminals 130 may be terminals located in a specific region 120 where the user terminal 110 has entered.

The plurality of external terminals 130 may generate an analysis result segment by analyzing the analysis segment when the analysis segment is received from the user terminal 110. The plurality of external terminals 130 may transmit the analysis result segment back to the user terminal 110.

The user terminal 110 may receive a plurality of analysis result segments from a plurality of external terminals 130 and collect the plurality of analysis result segments to generate user preference data.

That is, the user terminal 110 may divide the process performed by the user preference analysis unit 240 by omitting the user preference analysis unit 240 and distribute the processed data in a plurality of external tamars 130. Accordingly, the user terminal 110 can shorten the time it takes to analyze the user preferences, and can easily acquire the user preferences even with low-spec hardware.

The area detection unit 260 detects that the user terminal 110 has entered the specific area 120. The specific area 120 may be an administrative unit designated by the country, but is not limited thereto. The specific area 120 is a plurality of places 120a, 120b, ..., 120h in the area, and may be a specific building or a specific place, such as a department store, a shopping mall, an amusement park, or a tourist attraction.

In one embodiment, the area detection unit 260 may detect that it has entered the specific area 120 by obtaining identification information of the short-range wireless communication device installed in the specific area 120. The short-range wireless communication device may be a Wi-Fi device, but is not limited thereto. In another embodiment, the short-range wireless communication device may be a wireless communication device equipped with Bluetooth or a beacon.

In another embodiment, the area detection unit 260 may detect that the user has entered the specific area 120 using the GPS information of the terminal 110.

The ROI determining unit 270 determines the ROI using the user preference data when it is detected that the region detection unit 260 has entered the specific region 120.

The place of interest determining unit 270 acquires place information for a plurality of places 120a, 120b, ..., 120h located in the specific region 120.

In one embodiment, place information may be stored in the external information providing server 140. The user terminal 110 may request location information for a plurality of places 120a, 120b, ..., 120h located in a specific area 120 to the external information providing server 140. The external information providing server 140 requests the user terminal 110 to place information on a plurality of places 120a, 120b, ..., 120h located in a specific area 120 at the request of the user terminal 110. ). At this time, the place information is information that can identify the place, and may include a category, a store name, a place name, and a location.

In another embodiment, place information may be stored in advance in the user terminal 110.

The place of interest determining unit 270 determines a place of interest with high user preference among a plurality of places 120a, 120b, ..., 120h located in the specific region 120.

In one embodiment, the place of interest determining unit 270 is at least one place of a plurality of places (120a, 120b, ..., 120h) located in a specific area 120 is higher than a user preference value Can be extracted. The location of interest determining unit 270 may determine at least one extracted location as a location of interest.

For example, the place of interest determining unit 270 may extract a place having a preference of 50 or more from the user preference data from a plurality of places 120a, 120b, ..., 120h located in the specific region 120. . If the preferences for each of the plurality of places 120a, 120b, ..., 120h located in the specific region 120 are as illustrated in FIG. 3, the place of interest determining unit 270 is the place A 120a , Place B (120b), place E (120e), and place H (120h) may be determined as a place of interest.

In one embodiment, the place of interest determining unit 270 is at least one place having a high user preference among a plurality of places (120a, 120b, ..., 120h) located in a specific area 120 according to the environment information Can be extracted. Environmental information may be obtained by the environment acquisition unit 316. The environment acquisition unit 316 may acquire weather information, temperature information, humidity information, brightness information, and the like.

The user preference data may include preferences of categories according to the environment. The place of interest determining unit 270 may obtain environmental information from the environment obtaining unit 316. The place of interest determining unit 270 selects a place corresponding to a category having a high preference in an environment corresponding to environment information obtained from a plurality of places 120a, 120b, ..., 120h located in a specific area 120 Can be extracted. The location of interest determining unit 270 may determine at least one extracted location as a location of interest.

The copper wire calculating unit 280 calculates a plurality of copper wires connecting at least one location of interest determined by the location of interest determining unit 270 and the current location of the user. The user's current location P may be obtained by the location obtaining unit 314. The location acquisition unit 314 may acquire GPS information.

The copper wire calculating unit 280 may calculate a plurality of copper wires when there are two or more places of interest. For example, if the place of interest is place A (120a), place B (120b), the moving line calculator 280 is connected to the user's current location (P), place A (120a), place B (120b) It is possible to calculate a second copper wire connected to the first copper wire and the user's current location (P), B location (120b), and A location (120a).

As such, as the number of places of interest increases, the number of copper wires may increase in the copper wire calculating unit 280. For example, when the place of interest is A place 120a, B place 120b, E place 120e, and H place 120h, the copper line calculating unit 280 may calculate 24 copper lines.

Meanwhile, the copper wire calculating unit 280 may calculate a user's movement distance for each of the plurality of copper wires.

The recommended copper wire determining unit 290 determines at least one copper wire among the plurality of copper wires calculated by the copper wire calculating unit 280 as a recommended copper wire.

In one embodiment, the recommended copper wire determining unit 290 may determine at least one copper wire among a plurality of copper wires as a recommended copper wire using a user's movement distance. The recommended copper wire determining unit 290 may determine at least one copper wire having a short user's movement distance among the plurality of copper wires as the recommended copper wire. For example, when the copper wire calculating unit 280 calculates 24 copper wires, the recommended copper wire determining unit 290 may determine two copper wires as the recommended copper wires in the order of shortest moving distance among the 24 copper wires. .

In one embodiment, the recommended moving line determination unit 290 may determine at least one moving line among the plurality of moving lines using the current time and the user's moving distance. The current time may be obtained by the time acquisition unit 312.

User preference data may include category preferences for each time zone. The recommended moving line determination unit 290 may acquire the current time from the time acquisition unit 312. The recommended route determining unit 290 may select a place corresponding to a category having a high preference in a time zone corresponding to the current time from among the places of interest, and extract lines with a fast visit order to the selected place. The recommended copper wire determining unit 290 may determine a copper wire having a short user travel distance among the extracted copper wires as the recommended copper wire.

For example, the user may have a high preference for catering out at 12 o'clock. When the current time is 12:20, the recommended route determining unit 290 may select a place corresponding to catering, which is a category with high preference at 12 o'clock, at the place of interest. If the preferences for each of the plurality of places 120a, 120b, ..., 120h located in the specific region 120 are as illustrated in FIG. 3, the recommended moving line determination unit 290 is the location A 120a It is possible to extract traffic lines with a fast visit order. As illustrated in FIG. 4, the recommended moving line determination unit 290 may determine a moving line having a short user travel distance from among moving lines having a fast visit order to the location A 120a.

On the other hand, the user may have a low preference for catering out at 3 o'clock. When the current time is 3:20, the recommended moving line determining unit 290 may extract moving lines having a slow visit order to the location A 120a. As illustrated in FIG. 5, the recommended moving line determination unit 290 may determine a moving line having a short user travel distance from among moving lines having a slow visit order to the location A 120a as the recommended moving line.

The recommended moving line determination unit 290 may change the recommended moving line. In one embodiment, the recommended moving line determination unit 290 may change the recommended moving line using the user's current location. The recommended moving line determination unit 290 may periodically acquire location information from the location acquisition unit 314. The recommended moving line determination unit 290 may change the recommended moving line according to the user's current location.

In another embodiment, the recommended moving line determination unit 290 may change the recommended moving line using the user movement speed and the user's current location. The recommended moving line determination unit 290 may periodically acquire location information from the location acquisition unit 314. The recommended moving line determination unit 290 may calculate a user movement speed based on the acquired location information.

The recommended moving line determination unit 290 may predict the time when the user arrives at places of interest located in the recommended moving line using the calculated user moving speed and the current position of the user. The recommended moving line determination unit 290 may change the recommended moving line using the category preference for each of the predicted time and time zone.

For example, the user may have a high preference for catering in the category at 18. The recommended moving line determination unit 290 may predict a time at which the category arrives at place A, which is catering, using the user's moving speed and the user's current location at 20:00. The recommended moving line determination unit 290 may change the recommended moving line so that it can arrive at the 18th place in the A place.

The recommended copper wire display unit 320 displays at least one recommended copper wire determined by the recommended copper wire determining unit 290 on the display.

The user terminal 110 according to the present invention may be equipped with an application for recommending the optimum circulation including the components shown in FIG. 2.

Hereinafter, a method for recommending optimal circulation based on user preference will be described with reference to FIG. 6.

6 is a flowchart illustrating a method for recommending optimal circulation based on user preferences according to an embodiment of the present invention. The optimal route recommendation method based on user preference shown in FIG. 6 may be performed by the user terminal 110 shown in FIG. 1.

First, the user terminal 110 extracts user association information from an external message received from the outside or an internal message generated from the inside (S601).

The user terminal 110 may receive an external message from the outside or receive input from the user to generate an internal message. The external message may be a short text message, a long text message, a message received through an application, or a mail. The external message may include at least one of transaction information and conversation information. At this time, the transaction information may include at least one of point of interest (POI) information, transaction time, product information, and service information in which the transaction has been performed.

The internal message may include POI, product, service, and evaluation information of at least one in which the transaction has been performed. Here, the POI may indicate an online or offline store where a user purchases a product or service. The internal message may include conversation information entered by the user in the message window or search information entered by the user in the search window.

The user terminal 110 extracts user-related information from an external message or an internal message. The user terminal 110 parses an external message or an internal message to extract a plurality of keywords related to at least one of places, products, and services. The user terminal 110 generates user association information including a plurality of extracted keywords.

Next, the user terminal 110 analyzes the user association information to generate user preference data (S602).

The user terminal 110 generates user preference data by analyzing a plurality of keywords included in user association information. The user preference data may include category information and preference information. The category information may include information classifying places, products, and services.

The user terminal 110 may classify places, products, and services into a plurality of categories. In one embodiment, the user terminal 110 may classify places, products, and services into a first category and a second category. In this case, the first category may be a plurality, and the second category may be a sub-category for each of the plurality of first categories.

In one embodiment, the user terminal 110 may classify places, products, and services into a first category, a second category, and a third category. At this time, the third category may indicate a name for a place or a place for selling a product or service.

The user terminal 110 may determine preferences for places, products, and services classified according to category information.

In one embodiment, the user terminal 110 may determine preferences based on the frequency of keywords associated with each of places, products, and services classified according to category information. The user terminal 110 may analyze keywords included in the user association information to specify at least one of places, products, and services classified according to category information. The user terminal 110 may increase the preference of a specified place, product or service. At this time, the preference may indicate the frequency of keywords related to the place, product or service, but is not necessarily limited thereto.

In one embodiment, the user terminal 110 may determine preference based on the frequency and cumulative period of keywords associated with each of places, products, and services classified according to category information.

In one embodiment, the user terminal 110 may determine the preference based on the frequency of the keyword associated with each of the places, products, and services classified according to the category information and evaluation information about the keyword. The user terminal 110 may analyze keywords included in the user association information to specify at least one of places, products, and services classified according to category information. The user terminal 110 may increase or decrease the preference of a specified place, product or service according to the evaluation information. The user terminal 110 may reduce the preference of the specified place, product or service if the evaluation information for the specified place, product or service has a relatively low value. On the other hand, the user terminal 110 may increase the preference of the specified place, product or service if the evaluation information for the specified place, product or service has a relatively high value.

In one embodiment, the user terminal 110 may determine a category preference for each time zone. The user terminal 110 may determine a category preference for each time zone by using a keyword related to time among keywords included in user association information.

In one embodiment, the user terminal 110 may determine the preference of the category according to the environment. The user terminal 110 may obtain current environment information. The user terminal 110 may analyze keywords included in the user association information to specify at least one of places, products, and services classified according to category information. The user terminal 110 may increase the preference for a category of a place, product, or service specified in the current environment.

Next, when the user terminal 110 enters a specific area including a plurality of places, it determines a place of interest among the plurality of places (S603).

The user terminal 110 detects that it has entered a specific area. A specific area may be an administrative unit designated by a country, but is not limited thereto. The specific area is a plurality of places located in the area, and may be a specific building or a specific place, such as a department store, a shopping mall, an amusement park, or a tourist attraction.

In one embodiment, the user terminal 110 may detect that it has entered the specific area by acquiring identification information of the short-range wireless communication device installed in the specific area. The short-range wireless communication device may be a Wi-Fi device, but is not limited thereto. In another embodiment, the short-range wireless communication device may be a wireless communication device equipped with Bluetooth or a beacon.

In another embodiment, the user terminal 110 may detect that it has entered a specific area using GPS information.

When it is sensed that the user terminal 110 has entered the specific area, the user preference data is used to determine the place of interest.

The user terminal 110 acquires place information for a plurality of places located in a specific area. At this time, the place information is information that can identify the place, and may include a category, a store name, a place name, and a location.

In one embodiment, place information may be stored in an external information providing server. The user terminal 110 may receive place information for a plurality of places located in a specific area from an external information providing server.

In another embodiment, place information may be stored in advance in the user terminal 110.

The user terminal 110 determines a place of interest with high user preference among a plurality of places located in a specific area.

In one embodiment, the user terminal 110 may extract at least one place having a user preference greater than or equal to a preset value from a plurality of places located in a specific area. The user terminal 110 may determine at least one extracted location as a place of interest.

In one embodiment, the user terminal 110 may extract at least one place having a high user preference from among a plurality of places located in a specific area according to environment information. The environment information may include weather information, temperature information, humidity information, brightness information, and the like.

The user preference data may include preferences of categories according to the environment. The user terminal 110 may extract a place corresponding to a category having a high preference from an environment corresponding to the acquired environment information among a plurality of places located in a specific area. The user terminal 110 may determine at least one extracted location as a place of interest.

Next, the user terminal 110 calculates a plurality of copper wires connecting at least one place of interest and the current location of the user (S604).

The user terminal 110 calculates a plurality of copper wires connecting at least one place of interest and the current location of the user. The user terminal 110 may calculate a plurality of copper wires when there are two or more places of interest.

Meanwhile, the user terminal 110 may calculate the user's movement distance for each of the plurality of copper wires.

Next, the user terminal 110 determines at least one copper wire among the plurality of copper wires as the recommended copper wire (S605 ).

The user terminal 110 may determine at least one copper wire among the plurality of copper wires as the recommended copper wire using the user's movement distance. The user terminal 110 may determine at least one copper wire having a shorter moving distance among the plurality of copper wires as the recommended copper wire.

In one embodiment, the user terminal 110 may determine at least one copper line among the plurality of copper lines as a recommended copper line using the current time and the movement distance of the user.

User preference data may include category preferences for each time zone. The user terminal 110 may select a place corresponding to a category having a high preference in a time zone corresponding to the current time from among the places of interest, and extract traffic lines having a fast visit order to the selected place. The user terminal 110 may determine a copper wire having a short user travel distance among the extracted copper wires as a recommended copper wire.

Next, the user terminal 110 displays the recommended copper wire (S606). The user terminal 110 displays at least one recommended moving line on the display.

Next, the user terminal 110 changes and displays the recommended route (S607).

In one embodiment, the user terminal 110 may change the recommended route using the user's current location. The user terminal 110 may periodically acquire location information. The user terminal 110 may change the recommended route according to the user's current location.

In another embodiment, the user terminal 110 may change the recommended movement line using the user movement speed and the user's current location. The user terminal 110 may periodically acquire location information. The user terminal 110 may calculate the user movement speed based on the acquired location information.

The user terminal 110 may use the calculated user movement speed and the user's current location to predict the time when the user arrives at places of interest located in the recommended route. The user terminal 110 may change the recommended traffic line using the preference of the category for each predicted time and time zone.

For example, the user may have a high preference for catering in the category at 18. The user terminal 110 may predict the time to arrive at the place A where the category is catering at 20 o'clock using the user's moving speed and the user's current location. The recommended moving line determination unit 290 may change the recommended moving line so that it can arrive at the 18th place in the A place.

The user terminal 110 displays the changed recommended moving line on the display.

Those skilled in the art to which the present invention pertains will understand that the above-described present invention can be implemented in other specific forms without changing its technical spirit or essential features.

For example, the optimal route recommendation method based on user preference shown in FIG. 6 may be implemented in a program form such as an application or an agent and mounted on a medium capable of reading the corresponding program. When the optimal moving route recommendation method based on user preference according to the present invention is implemented as a program, each step shown in FIG. 6 is implemented as a code, and codes for implementing a specific function are implemented as a single program or a plurality of programs It may be implemented by partitioning.

It should be understood that the embodiments described above are illustrative in all respects and not restrictive. The scope of the present invention is indicated by the following claims rather than the above detailed description, and it should be interpreted that all changes or modifications derived from the meaning and scope of the claims and equivalent concepts are included in the scope of the present invention. do.

100: Optimal circulation recommendation system based on user preference
110: user terminal 120: a specific area
130: external terminal 140: information providing server
210: receiving unit 220: input unit
230: user-related information collection unit 240: user preference analysis unit
250: database 260: area detection unit
270: point of interest determination unit 280: copper line calculation unit
290: recommended route determining unit 310: additional information acquisition unit
320: recommended copper display

Claims (16)

A user association information collection unit for extracting a plurality of keywords from an external message received from the outside to the user terminal and an internal message generated inside the user terminal, and generating user association information including the extracted plurality of keywords;
A user preference analysis unit configured to generate user preference data by analyzing the user association information;
A point of interest determining unit for determining at least one of the plurality of places as a place of interest by using the user preference data when entering a specific area including a plurality of places; And
And a recommended moving line determining unit determining at least one moving line among the plurality of moving lines connecting the at least one point of interest and the current location of the user as a recommended moving line,
The external message includes transaction information and conversation information consisting of at least one of POI information, transaction time, product information, and service information in which a transaction has been performed.
The internal message includes conversation information or search information input by a user, or user preference based optimal circulation including evaluation information for at least one of the POI information, the product information, and the service information input by the user Recommendation system. delete According to claim 1,
The user preference data includes user preferences that include category information indicating information that classifies places, products, and services into a plurality of categories, and preference information indicating preferences for places, products, and services classified according to the category information. Based optimal circulation recommendation system. According to claim 3,
The user preference analysis unit determines a preference based on the frequency of related keywords for each of places, products, and services classified according to the category information. According to claim 3,
The user preference analysis unit determines a preference based on frequency and evaluation information of related keywords for each place, product, and service classified according to the category information. According to claim 3,
The user preference analysis unit is a user preference based optimal circulation recommendation system for determining preferences for the plurality of categories according to time zones or environments. According to claim 1,
The place-of-interest determining unit determines a place where the preference information included in the user preference data is greater than a predetermined value among a plurality of places located in the specific area as a place of interest based on the user preference based optimal circulation recommendation system. According to claim 1,
The recommended moving line determining unit determines the at least one moving line having a short moving distance of the user among the plurality of moving lines connecting the at least one point of interest and the user's current location as a recommended moving line based on user preference. According to claim 1,
The recommended route determining unit selects a place corresponding to a category having a high preference in a time zone corresponding to the current time, and a visit order of the selected place among a plurality of lines connecting the at least one place of interest and the user's current location Optimal moving line recommendation system based on user preferences that extracts the fastest moving lines and determines at least one moving line having a shorter user travel distance among the extracted moving lines as a recommended moving line. Extracting a plurality of keywords from an external message received from the outside to the user terminal and an internal message generated inside the user terminal, and generating user association information based on the extracted plurality of keywords;
Generating user preference data by analyzing the user association information;
When entering a specific area including a plurality of places, determining at least one of the plurality of places as a place of interest using the user preference data; And
And displaying at least one copper wire among the plurality of copper wires connecting the at least one point of interest and the current location of the user as a recommended copper wire,
The external message includes transaction information and conversation information consisting of at least one of POI information, transaction time, product information, and service information in which a transaction has been performed.
The internal message includes conversation information or search information input by a user, or user preference based optimal circulation including evaluation information for at least one of the POI information, the product information, and the service information input by the user Recommended method. The method of claim 10, wherein the step of marking with the recommended copper wire is:
Calculating a plurality of copper wires connecting the at least one point of interest and the current location of the user; And
Optimal circulation recommendation based on user preferences, comprising selecting at least one of the plurality of movement lines based on at least one of a current time, a current location, and a user movement distance, and displaying the selected at least one movement line as a recommended movement line. Way. delete The method of claim 10,
The user preference data includes user preferences including category information indicating information that classifies places, products, and services into a plurality of categories, and preference information indicating preferences for places, products, and services classified according to the category information. Based on the best way to recommend copper wire. The method of claim 13, wherein the generating the user preference data comprises:
A method for recommending optimal circulation based on user preferences for determining preferences based on at least one of frequency and evaluation information of related keywords for each of places, products, and services classified according to the category information. The method of claim 13, wherein the generating the user preference data comprises:
A method for recommending optimal circulation based on user preferences for determining preferences for the plurality of categories for each time zone or environment. The method of claim 10, wherein generating the user preference data comprises:
Dividing the user association information into a plurality of analysis segments, and transmitting the plurality of analysis segments to a plurality of external terminals; And
And receiving a plurality of analysis result segments from the plurality of external terminals, and generating the user preference data based on the received plurality of analysis result segments.

Images