KR20220150081A - Method and apparatus for recommending places - Google Patents

Abstract

Disclosed are a method and apparatus for recommending places. The method for recommending places, performed by a server, according to an embodiment includes the steps of: obtaining a list of places corresponding to a reference location; calculating a quality score and a variance score of the corresponding place based on the degree of interest of the corresponding place, by corresponding to each of the places, calculating; and selecting at least one recommendation target from among the places based on the quality score and the variance score calculated by corresponding to each of the places.

Description

Location recommendation method and device {METHOD AND APPARATUS FOR RECOMMENDING PLACES}

The following embodiments relate to a method and apparatus for recommending a place, and more particularly, to a method for recommending a place corresponding to a reference location in a map application or a map website, and to a server providing a place recommendation service.

In recent years, the use of map applications for searching, finding directions, or checking real-time traffic information in mobile terminals such as smart phones, tablets, and wearable devices has become common. The map application uses GPS information to determine the real-time location of the terminal, provides information about various places such as restaurants, cafes, convenience stores, and subway stations located nearby, and provides a route finding function using real-time traffic information. We provide a variety of services. As the use of map applications increases, the development of technology for providing various location-based functions is required.

Through the following embodiments, a service for recommending a place may be provided by reflecting users' recent interest in places.

Through the following embodiments, it is possible to provide a place recommendation service in which a list of recommended places is changed according to the timing of a user's request for place recommendation for the same area.

However, the technical problems are not limited to the above-described technical problems, and other technical problems may exist.

According to one aspect, a method for recommending a place performed by a server includes: obtaining a list of places corresponding to a reference location; corresponding to each of the places, calculating a quality score of the corresponding place based on the cumulative interest level of the corresponding place; and calculating a change amount score of the corresponding place based on a distribution of moving average values for each time unit of interest of the corresponding place and a moving average value of a reference time unit. and selecting at least one recommendation target from among the places based on the quality score and the variation score calculated for each of the places.

The selecting of the recommendation target may include: determining, as an outlier, a place exceeding a first threshold value with respect to a variance score obtained based on a quantile of variance scores of the places; and setting the change amount score of the place determined as the outlier to a minimum value.

The determining of the outliers may include: converting the variation scores of the places into a logarithmic scale; obtaining a first threshold value for the variance score based on the quantiles of the transformed variance scores; and determining, among the places, a place in which the converted change amount score exceeds the first threshold value as an outlier.

The determining as the outlier may include: obtaining a first threshold value for the variance score based on quantiles of variance scores of the places; obtaining a second threshold value related to the degree of interest based on the degree of interest corresponding to the reference time unit of the places; and determining, as an outlier, a place in which the variation score exceeds a first threshold value and the degree of interest corresponding to the reference time unit exceeds a second threshold value among the places.

The calculating of the variance score may include calculating an average and standard deviation of moving average values of previous time units of the reference time unit; calculating a standard score of the moving average value of the reference time unit based on the standard deviation and the average; and determining the variation score based on the standard score.

Calculating the standard score may include correcting by adding a predetermined value to the standard deviation; and calculating a standard score of the moving average value of the reference time unit based on the corrected standard deviation and the average.

Calculating the variance score may include setting the variance score to a minimum value when the moving average value of the reference time unit is smaller than an average of moving average values of previous time units of the reference time unit. .

The step of selecting the recommended target may include calculating a final score of the corresponding place by summing the quality score of the corresponding place and the variation score of the corresponding place corresponding to each of the places; and selecting at least one of the places to be recommended based on the final scores of the places.

The calculating of the final score includes weighting and summing the quality score of the corresponding place and the variation score of the corresponding place based on a first weight corresponding to the quality score and a second weight corresponding to the variation score. calculating a final score for the venue.

The second weight may be set to be greater than the first weight.

The calculating of the final score may include: normalizing the variation score obtained for each of the places to have a value within a predetermined range; and calculating the final score of the corresponding place by weighted summing the quality score of the corresponding place and the normalized variation score of the corresponding place, corresponding to each of the places.

The time unit may include a week unit.

The moving average values for each time unit of the interest may include average values of the interest for a week obtained based on daily time series data regarding the interest in a predetermined range.

The degree of interest may be determined based on at least one of a search amount for a specific place and a number of clicks for the specific place.

The obtaining of the list of places may include: obtaining time series data corresponding to the number of clicks on the places; and obtaining time series data corresponding to a search amount for the places.

The selecting of the recommendation target may include calculating a distance between a location of the corresponding location and the reference location corresponding to each of the locations; and selecting at least one recommendation target from among the places based on the quality score, the variation score, and the distance calculated for each of the places.

Acquiring the list of places may include receiving information about a category of a place from a user, and obtaining the list of places based on the reference location and the information about the category.

The server may include a server that provides at least one of a map application and a map website.

A server according to one side obtains a list of places corresponding to a reference location, and, corresponding to each of the places, calculates a quality score of the corresponding place based on the cumulative interest level of the corresponding place, and the degree of interest of the corresponding place based on the distribution of moving average values for each time unit and the moving average value of the reference time unit, calculates the variation score of the corresponding place, and based on the quality score and the variation score calculated for each of the places , at least one processor for selecting at least one recommendation target from among the places.

The processor is configured to determine, as an outlier, a place exceeding a first threshold value with respect to a variance score obtained based on a quantile of variance scores of the places as an outlier in selecting the recommendation target; The change score of the place determined as an outlier can be set to the minimum value.

In calculating the variance score, the processor calculates an average and standard deviation of moving average values of previous time units of the reference time unit, and based on the standard deviation and the average, the moving average of the reference time unit A standard score of the values may be calculated, and the variance score may be determined based on the standard score.

In selecting the recommended target, the processor calculates a final score of the corresponding place by summing the quality score of the corresponding place and the variation score of the corresponding place, corresponding to each of the places, and the final score of the places. Based on the locations, at least one recommendation target among the places may be selected.

According to the following embodiments, the list of recommended places is changed according to the time of the user's request for place recommendation corresponding to the same area, so that it is possible to provide a service capable of recommending various places for the same area.

Through the following embodiments, it is possible to provide a service for recommending a place reflecting the recent interest in consideration of the deviation of the interest level according to the day of the week.

1 is an operation flowchart of a place recommendation method according to an embodiment.
2 is an exemplary diagram of time-series data for each day with respect to the degree of interest corresponding to each of the places.
3 is a diagram for explaining a moving average value for each time unit of interest in an individual place according to an embodiment.
4 is an operation flowchart of a method of calculating a change amount score and a quality score of an individual place according to an embodiment.
5 is a flowchart illustrating a method of removing an outlier according to an embodiment.
6 is an exemplary diagram of a configuration of an apparatus for providing a place recommendation service according to an embodiment.

Specific structural or functional descriptions of the embodiments are disclosed for purposes of illustration only, and may be changed and implemented in various forms. Accordingly, the actual implementation form is not limited to the specific embodiments disclosed, and the scope of the present specification includes changes, equivalents, or substitutes included in the technical spirit described in the embodiments.

Although terms such as first or second may be used to describe various elements, these terms should be interpreted only for the purpose of distinguishing one element from another. For example, a first component may be termed a second component, and similarly, a second component may also be termed a first component.

When a component is referred to as being “connected” to another component, it may be directly connected or connected to the other component, but it should be understood that another component may exist in between.

The singular expression includes the plural expression unless the context clearly dictates otherwise. In this specification, terms such as "comprise" or "have" are intended to designate that the described feature, number, step, operation, component, part, or combination thereof exists, and includes one or more other features or numbers, It should be understood that the possibility of the presence or addition of steps, operations, components, parts or combinations thereof is not precluded in advance.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present specification. does not

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. In the description with reference to the accompanying drawings, the same components are assigned the same reference numerals regardless of the reference numerals, and the overlapping description thereof will be omitted.

1 is an operation flowchart of a place recommendation method according to an embodiment.

Referring to FIG. 1 , a method for recommending a place performed in a server according to an embodiment includes obtaining a list of places corresponding to a reference location ( 110 ), and calculating a quality score and a change amount score corresponding to each of the places. ( 120 ), and selecting ( 130 ) a recommendation target for at least one of the places may be included.

The server according to an embodiment may provide a place recommendation service, which will be described below, to the user terminal. The user terminal may include, for example, a personal computer (PC), a netbook, a notebook computer, a personal digital appliance (PDA), a smart phone, a wearable device, and various devices performing similar functions. The server may include at least one processor for performing a process for the place recommendation service, and may include a memory for storing data for the place recommendation service. A detailed configuration of the server according to an embodiment will be described in detail with reference to FIG. 6 below.

According to an embodiment, the server may provide a place recommendation service through a map application. The map application obtains the location of the terminal where the application is installed using GPS, displays a map around the acquired location of the terminal or a location designated by the user, and includes a function to provide information about the area included in the displayed map can do. The user terminal may be driven by an installed map application, and the user may use a service provided by the server through the map application installed in the terminal. The server may be linked with a map application installed in the user terminal for a user interface (UI), a function, an operation, or a service.

According to an embodiment, the server may provide a place recommendation service through a map website. The map website obtains the location of the terminal accessing the website using GPS, displays a map around the acquired location of the terminal or a location designated by the user, and provides information on the area included in the displayed map. function may be included. The user can use the service provided by the server through the map website accessed through the terminal.

Step 110 according to an embodiment may correspond to obtaining a list of places included in a regional range determined based on a reference location. The reference location may be determined as the location of the terminal, a location designated by a user, or a location set as a default. For example, a location corresponding to an address or place name input by the user may be determined as the reference location. The regional range determined based on the reference location may include a regional range within a predetermined distance from the reference location, for example, an area within a radius of 3 km from the reference location.

Places according to an embodiment may correspond to places registered in the server. The places registered in the server may mean places where identification information and location information of the place are stored in the server. For example, places registered in the server may include category information. According to an embodiment, places of a specific category are places classified into similar types, and may include, for example, places corresponding to a restaurant category, places corresponding to a cafe category, and places corresponding to a convenience store category. . The server may store identification information of a plurality of places, location information, and category information.

Acquiring the list of places 110 according to an embodiment may further include receiving information on a reference location from a user. For example, the user may input a reference position through an application, and the server may receive the reference position input by the user. More specifically, the user may input the address of the reference location through the application, input the current terminal location as the reference location, or select a specific location within the map displayed through the application and input it as the reference location. For example, when a user searches for 'Pangyo Station' through the application, a list of places included in a certain area with 'Pangyo Station' as a reference location may be obtained.

According to an embodiment, the list of places may include places belonging to a plurality of categories. For example, when a user searches for 'Pangyo Station' through the application, a list of places belonging to various categories such as convenience stores, restaurants, and cafes included in a certain area with 'Pangyo Station' as the reference location will be obtained. can

According to an embodiment, the step of obtaining a list of places 110 may include receiving information about a category of a place from a user and obtaining a reference location and a list of places corresponding to a specific category. . For example, the user may input a category of a place to be recommended through the application. More specifically, any one of a plurality of categories provided through the application may be selected, or a category name may be directly entered into a search box provided through the application. For example, when the user searches for 'restaurants' through the application, a list of places belonging to the 'restaurant' category included in a certain area corresponding to the determined reference location may be acquired.

According to an embodiment, the obtained list of places may further include places belonging to a category similar to the information about the category received by the user. For example, when a user searches for 'restaurant' through the application, it is included in a certain area range corresponding to the determined reference location, and is included in the 'restaurant' category related to 'restaurant' which is information about the category received by the user. A list of places belonging to and places belonging to the 'cafe' category may be obtained.

Step 120 according to an embodiment may include calculating a quality score and a change amount score based on the degree of interest of the corresponding place, corresponding to each of the places obtained in step 110 .

The degree of interest according to an embodiment is a value of measuring the degree of users' interest in a specific place, for example, based on data about a specific place that can be collected from a server, the degree of interest of users in the corresponding place is expressed as a numerical value. It may include converted values.

According to an embodiment, the degree of interest in a specific place may be determined based on at least one of a search amount for the specific place and the number of clicks on the specific place. For example, the degree of interest in a specific place may be determined as a search amount value for a specific place, a value of clicks for a specific place, or a sum of a search amount value and a click value for a specific place. The search volume for a specific place may include the number of searches of that place that can be collected from the server, for example, the number of times that place was searched for through an application, and the number of times that place was searched for on a website linked to the server. have. The number of clicks on a specific place may include the number of clicks on the corresponding place that can be collected from the server, for example, the number of clicks on the corresponding place through the application, and the number of clicks on the corresponding place on the website linked to the server can do.

Hereinafter, a case in which the degree of interest of a specific place is determined based on at least one of a search amount for a specific place and the number of clicks for a specific place will be described as an example, but the method of determining the degree of interest in a specific place is not limited, The degree of interest in a specific place may be determined by various quantifiable methods.

According to an embodiment, step 110 , which is a step before step 120 , may further include acquiring time series data corresponding to the degree of interest in places. For example, operation 110 may further include at least one of obtaining time series data corresponding to the number of clicks for places and obtaining time series data corresponding to a search amount for places. The time series data means a sequence of data arranged at regular time intervals. For example, daily time series data may include a sequence of data arranged at intervals of one day.

For example, referring to FIG. 2 , daily time series data for November 10 to November 19 with respect to the degree of interest corresponding to each of the obtained places may be obtained. The daily time series data for the degree of interest may include data in which interest values acquired in units of one day are listed in time order. As described above, the daily interest value for a specific place may be determined based on at least one of a daily search amount and daily clicks for the corresponding place. In other words, the server may obtain a list of places including ID information (place_id) and name information (place_name) for identifying each of the places according to step 110 of FIG. 1 , and corresponding to each obtained place It is possible to obtain daily time series data for the degree of interest.

According to an embodiment, the server may store daily time-series data of a certain range for the degree of interest of an individual place. For example, the server may store daily time-series data in the range of the most recent one month on the degree of interest of individual places.

In step 120 according to an embodiment, corresponding to each of the places obtained in step 110 , based on the accumulated interest level of the corresponding place, calculating a quality score of the corresponding place and the time unit of the interest of the corresponding place The method may include calculating a change amount score of the corresponding place based on the distribution of the moving average values for each star and the moving average value of the reference time unit. In other words, the variance score and the quality score may be calculated for each location.

A detailed operation of calculating a change amount score and a quality score of an individual place according to an embodiment will be described with reference to FIG. 4 .

Referring to FIG. 4 , a quality score of a specific place according to an embodiment may be calculated 410 based on at least one of a cumulative interest in the corresponding place for a certain period and a score related to basic information of the corresponding place ( 410 ). The cumulative interest level may be determined as a sum of interest-related data acquired for a certain period of time. The score for the basic information of a specific place is a quantitative number of information held about the place, for example, additional information about the place (e.g., business hours, menu, facility information, road view, website link, etc.) ), the amount of review information about the place, and the amount of image information about the place, it may include a score converted into a numerical value. According to an embodiment, a score regarding the basic information of a specific place may be determined by weighted summing values of items included in the basic information. For example, the score regarding the basic information of the place may be determined by weighting the amount of additional information about the place, the amount of review information about the place, and the amount of image information about the place.

According to an embodiment, the quality score of a specific place may be determined based on the sum of the accumulated interest in the corresponding place and the score regarding basic information of the corresponding place. For example, the quality score of a specific place may be determined as a simple sum or a weighted sum of the accumulated interest in the corresponding place and the scores on basic information of the corresponding place. In other words, the quality score is a score determined based on the absolute magnitude of interest corresponding to a certain period and the amount of information useful to the user. The higher the cumulative interest, the higher the quality score can be determined. .

As an example, referring to FIG. 2 , the quality score of a place with place_id of 111 is 1645, which is the sum of time series data of daily interest of the corresponding place, and the quality score of a place with place_id of 112 is the sum of time series data of daily interest of the corresponding place. 1390 may be determined.

As another example, the quality score of a specific place is a value proportional to the sum of the time series data of the daily interest of the corresponding place, a value obtained by normalizing the sum of the time series data of the daily interest of the corresponding place to have a value within a specific range, or daily of places It may be determined as a value proportional to a quantile according to the sum of time series data of interest. In addition to the above-described example, the quality score of a specific place may be determined in various ways based on the sum of time series data of daily interest in the corresponding place.

Referring again to FIG. 4 , the change score of a specific place according to an embodiment may be determined based on a distribution of moving average values for each time unit of interest in the corresponding place and a moving average value of a reference time unit. The distribution of moving average values for each time unit of interest is a set of data in which the moving average value corresponding to each time unit is an observation value or a variable. For example, the time unit may include a week unit, and the moving average value for each time unit of interest may include average values of interest for a week obtained based on daily time series data related to interest in a predetermined range. have. According to an embodiment, since the time unit is set to one week, the variation score may be calculated in consideration of daily time series data regarding the degree of interest corresponding to all days of the week. Hereinafter, a case in which the time unit is set to a week will be described as an example, but the time unit is not limited to a week, and may be variously set in units of minutes, hours, and days.

For example, referring to FIG. 3 , the distribution of moving average values for each time unit of interest is the average value (1240/7) of interest corresponding to the unit of week 310 from November 10 to November 16, 11 The average value of interest (1240/7) corresponding to the weekly unit (320) from month 11 to November 17, the average value of interest corresponding to the weekly unit (330) from November 12 to November 18 ( 1214/7), is a set of average values (1243/7) of interest corresponding to a weekly unit (340) from November 13 to November 19.

According to an embodiment, in calculating the variance score, the sum of time series data values for each time unit may be used instead of the moving average value for each time unit. For example, referring to FIG. 3 , instead of an average value obtained by dividing the sum of time series data corresponding to a week unit by 7, the sum of time series data corresponding to a week unit may be used to calculate the variation score. In other words, the moving average means an average obtained by dividing the sum of data values of some sets by the size of the set, but may also mean the sum of data values of some sets according to an embodiment.

According to an embodiment, the moving average may include a moving average calculated in various ways such as a simple moving average, a cumulative moving average, a weighted moving average, and an exponential moving average. Hereinafter, for convenience of explanation, the moving average is calculated and described as a simple moving average.

The reference time unit according to an embodiment is a time unit corresponding to the current time point, and the current time point may mean a time point at which the place recommendation method is performed. The time unit corresponding to the current time may correspond to a time unit in which the time immediately preceding the time including the current time is the end point of the time unit. The time including the current time may correspond to a day when the time unit corresponds to a plurality of days, such as a week, and may correspond to a time when the time unit corresponds to a plurality of times, such as 7 hours. It may correspond to, and when the time unit corresponds to a plurality of minutes, such as 7 minutes, it may correspond to a minute. For example, referring to FIG. 3 , when the time unit is one week and the current time point is included in November 20, the week unit 310 having the end point of November 19, which is the day immediately preceding the 20th, is the reference time unit. corresponds to According to an embodiment, a time unit corresponding to the current time may correspond to a time unit in which a time including the current time is the end point of the time unit.

According to an embodiment, the change score may be determined based on whether the interest level has recently increased by using a rate of change of the interest level of an individual place. The rate of change of the interest level of each place may be measured based on the distribution of moving average values for each time unit of the individual place.

Referring back to FIG. 4 , the calculating of the variance score according to an embodiment includes calculating the average and standard deviation of the moving average values of the previous time units of the reference time unit ( 420 ), the calculated standard deviation and the average. Based on the step, calculating a standard score of the moving average value of the reference time unit ( 430 ), and calculating a variance score based on the standard score ( 440 ) may be included. For example, referring to FIG. 3 , when the reference time unit is a week unit 310 until November 19, previous time units of the reference time unit are a week unit 320 until November 18 and November 17 It may include a week unit 330 until November 16, and a week unit 340 until November 16.

According to an embodiment, the target of calculating the average and standard deviation may include moving average values of previous time units of the reference time unit, and the moving average value of the reference time unit may be excluded from the target of calculating the average and standard deviation. have. The degree of interest according to an embodiment does not have an upper limit value, and due to the characteristic that the number of populations subject to calculation of the mean and standard deviation is limited to a predetermined number, the moving average value of the reference time unit exceeds the mean and standard deviation can affect For example, when the average of the moving average values of the previous time units of the reference time unit is 1 and the moving average value of the reference time unit is 100, the moving average value of the reference time unit is included in the calculation of the average and standard deviation. When the calculated standard score and the calculated standard score are compared without including the moving average value of the reference time unit in the calculation of the mean and standard deviation, the latter standard score is calculated to be larger than the former. In the former case, the moving average value of the reference time unit has an excessive influence on the average and standard deviation, so that the standard score may not appear high even when the interest level has recently increased sharply. Accordingly, by excluding the moving average value of the reference time unit from the target of calculating the average and standard deviation for calculating the standard score, it is possible to prevent an over-influence of the moving average value of the reference time unit on the standard score.

According to an embodiment, the number of moving average values of previous time units to be calculated for the average and standard deviation may be predetermined. For example, previous time units subject to calculation of the mean and standard deviation may be determined to include two time units immediately preceding the reference time unit. For example, referring to FIG. 3 , when the reference time unit is a week unit 310 until November 19, previous time units of the reference time unit are until November 18, which are two time units immediately before the reference time unit. The average and standard deviation may be calculated with respect to the moving average values corresponding to the weekly unit 320 and the weekly unit 330 until November 17th.

According to an embodiment, the standard score of the moving average value of the reference time unit may be calculated based on the average and standard deviation of the moving average values of the previous time units of the reference time unit. For example, the standard score (std_score) of the reference time unit may be expressed as in Equation 1 below.

Here, MA _t- is the moving time average of the reference time unit (t), MA _tx is the moving time average of the time unit before x of the reference time unit, Average(x:y) is the average of values of x to y, Std( x:y) means the standard deviation of the values of x to y. k is a value determined according to the number of moving average values of previous time units subject to average and standard deviation calculation. As described above, the number of moving average values of previous time units subject to standard deviation calculation is predetermined. can be done

For example, referring to FIG. 3 , when the reference time unit corresponds to the week unit 310 until the 19th, and k is 2, the average and standard deviation of the previous time units are respectively expressed by Equations 2 and 3 below and can be calculated together. In Equations 2 and 3, for convenience of calculation, the average and standard deviation are calculated based on the sum of the daily time series data of the week unit instead of the moving average obtained by dividing the sum of the daily time series data of the week unit by 7.

The standard score of the reference time unit 310 may be calculated according to Equation 1 and Equation 4 below.

According to an embodiment, the standard deviation of the moving average values of previous time units for calculating the standard score may be corrected to prevent it from being zero. As an example, the step of calculating the standard score includes the step of correcting by adding a predetermined value (eg, 1) to the standard deviation, and calculating the standard score of the moving average value of the reference time unit based on the corrected standard deviation and average. may include steps.

For example, referring to FIG. 3 , based on the standard deviation value corrected by adding 1 to the standard deviation value calculated according to Equation 3, the standard score of the reference time unit 310 as shown in Equation 5 below. can be calculated.

According to an embodiment, since the standard score of the reference time unit is determined as the standard deviation of the previous time units is smaller, the difference between the interest value corresponding to the reference time unit and the average of the previous time units is larger, so that the standard score of the previous time unit is larger. As the interest value corresponding to the reference time unit is greater than the interest values corresponding to the units, it may be determined to be larger. In other words, the standard score of the reference time unit may be calculated as a larger value as the recent interest level increases significantly.

According to an embodiment, the change amount score may be determined based on the standard score of the reference time unit. A standard score may be determined as a variance score as a variance score as it is, and a score obtained by normalizing the standard score may be determined as a variance score. The process of normalizing the standard score is detailed below.

According to an embodiment, the calculating of the variance score includes: when the moving average value of the reference time unit is smaller than the average of the moving average values of the previous time units of the reference time unit, setting the variance score of the corresponding place to a minimum value may include. For example, when the moving average value of the reference time unit is smaller than the average of the moving average values of previous time units of the reference time unit, the change amount score of the corresponding place may be set to a minimum value of 0. In other words, in the case of a place where the moving average value of the reference time unit is increased than the average of the moving average values of previous time units of the reference time unit, the standard score of the reference time unit according to Equation 1 is calculated, and the calculated standard score is Based on the variance score may be determined. On the other hand, in the case where the moving average value of the reference time unit is less than or equal to the average of the moving average values of the previous time units of the reference time unit, the standard score calculation process according to Equation 1 may not be performed, and the change score is It can be determined as 0.

Referring to FIG. 4 , a final score may be calculated 450 based on the quality score and the variation score calculated for a specific place. The final score may be a criterion for selecting a place recommendation target. The specific process of calculating the final score ( 450 ) will be described in detail below.

Referring back to FIG. 1 , step 130 according to an embodiment may include selecting at least one recommendation target from among the places based on the quality score and variation score calculated for each of the places. have.

Step 130 according to an embodiment may include removing an outlier in order to prevent a place having an increased interest from being recommended due to a factor related to a purpose different from the purpose of the place recommendation. Factors related to the purpose of the place recommendation and other purposes may include, for example, when the purpose of the place recommendation is to recommend a restaurant, a social issue that may increase the search volume of the place, such as a trademark dispute, may include the occurrence.

A detailed operation of removing the outlier according to an embodiment will be described with reference to FIG. 5 .

Referring to FIG. 5 , in the step of selecting a recommendation target (eg, step 130 of FIG. 1 ) according to an embodiment, a first threshold with respect to a variance score obtained based on a quantile of variance scores of places The method may further include determining ( 530 ) a place exceeding the value as an outlier, and setting ( 540 ) a change amount score of the place determined as an outlier to a minimum value.

A quantile is a position value according to the size order of the data, and may be classified according to the size of the equal parts of the data arranged in the size order. For example, a quartile is an observation value that divides data arranged in size order, and the first quartile (lower quartile or Q1) is a value corresponding to the 25% rank of the data arranged in size order, the second quartile (median or Q2) is the value corresponding to the 50% rank of the data arranged in size order, the third quartile (upper quartile or Q3) is the value corresponding to the 75% rank of the data arranged in the size order, the fourth quartile (Q4) corresponds to the value corresponding to the 100% rank of the data listed in order of size.

For example, the first threshold value T ₁ for the variance score may be calculated as in Equation 6 below based on the quantiles of variance scores of places.

In Equation 6, an interquartile range (IQR) may be calculated as Q3-Q1 as a range including 50% of the entire data. a is a constant of a predetermined value, for example, may be set to 2.5.

According to an embodiment, among the places, the place where the change score exceeds the first threshold value T ₁ may be determined as an outlier, and the change score of the place determined as the outlier may be set to 0. According to an embodiment, not only places where the variance score exceeds the first threshold value T ₁ , but also places where the variance score is equal to the first threshold value T ₁ among places may be determined as outliers.

According to an embodiment, the determining as an outlier may include converting variance scores of places into a log scale ( 510 ), and obtaining a first threshold value for variance score based on the quantiles of the transformed variance scores. ( 520 ), and determining ( 530 ) a place in which the converted variation score exceeds a first threshold value among the places as an outlier. Transforming the variance scores of the places to a log scale may include taking the logarithm of the variance scores of the places. According to an embodiment, the process of converting the variance scores of places into a log scale may include adding a certain number to the variance scores and then taking a logarithm.

For example, the change score (v_score') obtained by converting the change amount score (v_score) of a specific place into a log scale may be expressed as in Equation 7 below.

According to an embodiment, a first threshold value is obtained according to Equation 6 above based on the quantiles of the variance scores converted to a log scale, and among places where the converted variance score exceeds the first threshold value may be considered as an outlier.

Although not shown in FIG. 5 , the step of determining as an outlier according to an embodiment may further include acquiring a second threshold value regarding the degree of interest based on the degree of interest corresponding to the reference time unit of the places. In addition, the step 530 of determining the place exceeding the first threshold value as the outlier may include determining the outlier based on the first threshold value and the second threshold value. In other words, the determining as an outlier according to an embodiment includes: obtaining a first threshold value for the variance score based on the quantiles of the variance scores of the places; , obtaining a second threshold value for the degree of interest, and determining a place in which the variation score exceeds the first threshold value and the degree of interest corresponding to the reference time unit exceeds the second threshold value as an outlier may include. The second threshold value may be predetermined as a specific value (eg, 300).

For example, referring to FIG. 3 , the degree of interest corresponding to the reference time unit 310 of a specific place may correspond to 1243 which is the sum of time series data for each day included in the reference time unit 310 . When the second threshold value is less than (or less than) 1243, the corresponding place may be an outlier determination target, and may be determined as an outlier based on a comparison between the change amount score of the corresponding place and the first threshold value. On the other hand, when the second threshold value is 1243 or more (or more than), the corresponding place may not correspond to an outlier determination target, and may not be determined as an outlier regardless of the change amount score of the corresponding place.

According to an embodiment, among the places where the variance score exceeds the first threshold value or is equal to the first threshold value, and the place in which the degree of interest corresponding to the reference time unit exceeds the second threshold value or is equal to the second threshold value, among places It can be considered as an outlier.

Referring back to FIG. 1 , in step 130 according to an exemplary embodiment, a recommendation target may be selected based on a final score. The final score may be determined based on the quality score and the variance score. As an example, the step of selecting a recommendation target may include calculating a final score of the corresponding place by adding the quality score of the corresponding place and the variation score of the corresponding place corresponding to each of the places, and based on the final scores of the places, The method may include selecting at least one recommendation target from among the places.

According to an embodiment, the final score of a specific place may be determined as a simple sum or a weighted sum of a quality score and a variation score of the corresponding place. As an example, the calculating of the final score may include weighting and summing the quality score of the corresponding place and the variation score of the corresponding place based on the first weight corresponding to the quality score and the second weight corresponding to the variation score to determine the final score of the corresponding place. and calculating a score, wherein the second weight may be set to be greater than the first weight. According to an embodiment, the sum of the first weight and the second weight may be determined to be 1.

According to an embodiment, in calculating the final score, the variation score may be normalized to have a value within a predetermined range. For example, calculating the final score may include normalizing the variation score obtained for each of the locations to have a value within a predetermined range, and corresponding to each of the locations, the quality score of the corresponding location and the normalized variation of the location. calculating a final score for the place by weighted summing the scores.

For example, variance scores corresponding to places may be normalized to have values of 0 or more and 1 or less, and the normalized variance score (x') of variance score (x) can be expressed as Equation 8 below have.

According to an embodiment, normalization of the variance scores between the plurality of places may be performed so that the relative magnitude relationship of the variance scores between the plurality of places may be maintained even after being normalized.

According to an embodiment, the step of selecting a recommendation target 130 may include calculating a distance between the location of the corresponding location and the reference location in response to each of the locations, and the quality score calculated in response to each of the locations, and the amount of change The method may include selecting at least one recommendation target from among the places based on the score and the distance.

For example, the final score of a specific place may be expressed as in Equation 9 below.

In Equation 9, q_score may correspond to the quality score of the corresponding place, v_score may correspond to the change amount score of the corresponding place, and d_score may correspond to a distance score based on the distance between the location of the corresponding place and the reference location. The distance score may correspond to a value obtained by converting the distance between the location of the corresponding place and the reference location into a score according to a certain rule. a, b, and c may correspond to a first weight corresponding to the quality score, a second weight corresponding to the variation score, and a third weight corresponding to the distance score, respectively. As described above, the value of b may be determined to be larger than that of a.

According to an embodiment, based on the final score calculated for each of the places, at least one recommendation target may be selected. For example, a predetermined number of places may be selected as recommendation targets according to the order of highest final score. According to an embodiment, since the variation score and the quality score are calculated corresponding to the time unit according to the time unit including the time of requesting the place recommendation, the recommended place may be selected differently depending on the time of requesting the place recommendation. . For example, a place selected as a recommendation target may vary according to the date when the place recommendation is requested.

The server according to an embodiment may provide information about a place selected as a recommendation target to the user terminal. For example, information on the selected recommended place may be provided through a map application installed in the user terminal or a user interface of a map website interworking with a server.

6 is an exemplary diagram of a configuration of an apparatus for providing a place recommendation service according to an embodiment.

Referring to FIG. 6 , the device 600 includes a processor 601 , a memory 603 , and an input/output device 605 . The device 600 may correspond to a server, and may include a user device (eg, a smart phone, a personal computer, a tablet PC, etc.) according to an embodiment.

The apparatus 600 according to an embodiment may include an apparatus for performing the above-described method for recommending a place and/or an apparatus for providing a service for recommending a place. The processor 601 may perform the operations of at least one method step described above with reference to FIGS. 1 to 5 . For example, the processor 601 may perform each operation of the above-described place recommendation method, and may perform operations for providing a place recommendation service to the user terminal through the above-described map application. According to an embodiment, the processor 601 stores data for performing the operations of the place recommendation method and/or data generated by performing the operations of the place recommendation method in the memory 602 or an external database accessible from the device 600 . can be stored in

The memory 603 may store information related to the above-described method for recommending a place, and may store data generated according to the execution of an operation of the processor 601 . The memory 603 may be a volatile memory or a non-volatile memory.

The device 600 according to one side may be connected to an external device (eg, a user terminal or a network) through the input/output device 605 and exchange data. For example, the device 600 may receive a request for a place recommendation through the input/output device 605 , and may receive information about a reference location for the place recommendation. Also, for example, the device 600 may provide the recommended place selected through the input/output device 605 to the user terminal. Information on the selected recommended place may be provided through a user interface of a map application installed in the user terminal.

According to an embodiment, the memory 703 may store a program in which the above-described method for recommending a place is implemented. The processor 701 may execute a program stored in the memory 703 and control the device 700 . The code of the program executed by the processor 701 may be stored in the memory 703 .

The embodiments described above may be implemented by a hardware component, a software component, and/or a combination of a hardware component and a software component. For example, the apparatus, methods and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate (FPGA). array), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions, may be implemented using a general purpose computer or special purpose computer. The processing device may execute an operating system (OS) and a software application running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that may include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

The software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be any kind of machine, component, physical device, virtual equipment, computer storage medium or device, to be interpreted by or to provide instructions or data to the processing device. , or may be permanently or temporarily embody in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in a computer-readable recording medium.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer readable medium may store program instructions, data files, data structures, etc. alone or in combination, and the program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and available to those skilled in the art of computer software. have. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic such as floppy disks. - includes magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like.

The hardware devices described above may be configured to operate as one or a plurality of software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described with reference to the limited drawings, a person skilled in the art may apply various technical modifications and variations based thereon. For example, the described techniques are performed in a different order than the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (20)

In the place recommendation method performed in the server,
obtaining a list of places corresponding to the reference location;
Corresponding to each of the above places,
calculating a quality score of the corresponding place based on the accumulated interest of the corresponding place; and
calculating a change amount score of the corresponding place based on a distribution of moving average values for each time unit of interest of the corresponding place and a moving average value of a reference time unit; and
selecting at least one recommendation target from among the places based on the quality score and the variation score calculated for each of the places;
containing,
How to recommend a place.
According to claim 1,
The step of selecting the recommended target is
determining, based on a quantile of the variance scores of the places, a place exceeding a first threshold value for the obtained variance score as an outlier; and
Setting the change amount score of the place determined as the outlier to the minimum value
further comprising,
How to recommend a place.
3. The method of claim 2,
The step of determining the outlier is
converting the variance scores of the places to a log scale;
obtaining a first threshold value for the variance score based on the quantiles of the transformed variance scores; and
Determining a place where the converted change score exceeds the first threshold among the places as an outlier
containing,
How to recommend a place.
3. The method of claim 2,
The step of determining the outlier is
obtaining a first threshold value for a variance score based on a quantile of variance scores of the places;
obtaining a second threshold value related to the degree of interest based on the degree of interest corresponding to the reference time unit of the places; and
determining, as an outlier, a place in which the variation score exceeds a first threshold value and the degree of interest corresponding to the reference time unit exceeds a second threshold value among the places;
containing,
How to recommend a place.
According to claim 1,
The step of calculating the variance score is
calculating an average and standard deviation of moving average values of previous time units of the reference time unit;
calculating a standard score of the moving average value of the reference time unit based on the standard deviation and the average; and
determining the variance score based on the standard score
containing,
How to recommend a place.
6. The method of claim 5,
The step of calculating the standard score is
correcting by adding a predetermined value to the standard deviation; and
calculating a standard score of the moving average value of the reference time unit based on the corrected standard deviation and the average
containing,
How to recommend a place.
According to claim 1,
The step of calculating the variance score is
When the moving average value of the reference time unit is smaller than the average of the moving average values of previous time units of the reference time unit, setting the variation score to a minimum value;
containing,
How to recommend a place.
According to claim 1,
The step of selecting the recommended target is
corresponding to each of the places, calculating a final score of the corresponding place by summing the quality score of the corresponding place and the variation score of the corresponding place; and
selecting at least one of the places to be recommended based on the final scores of the places;
containing,
How to recommend a place.
9. The method of claim 8,
The step of calculating the final score is
calculating the final score of the corresponding place by weighted summing the quality score of the corresponding place and the variation score of the corresponding place based on the first weight corresponding to the quality score and the second weight corresponding to the variance score
including,
the second weight is set to be greater than the first weight;
How to recommend a place.
9. The method of claim 8,
The step of calculating the final score is
normalizing the change amount score obtained for each of the places to have a value within a predetermined range; and
corresponding to each of the places, calculating a final score of the corresponding place by weighted summing the quality score of the corresponding place and the normalized variation score of the corresponding place;
containing,
How to recommend a place.
According to claim 1,
The time unit includes a week unit,
The moving average values for each time unit of the interest include average values of the interest for a week obtained based on daily time series data about the interest in a predetermined range,
How to recommend a place.
According to claim 1,
The interest is
is determined based on at least one of a search amount for a specific place and a number of clicks for the specific place,
Obtaining a list of the places includes:
obtaining time series data corresponding to the number of clicks for the places; and
obtaining time series data corresponding to a search amount for the places;
further comprising at least one of
How to recommend a place.
According to claim 1,
The step of selecting the recommended target is
calculating a distance between a location of the corresponding location and the reference location corresponding to each of the locations; and
selecting at least one recommendation target from among the places based on the quality score, the variation score, and the distance calculated for each of the places;
containing,
How to recommend a place.
According to claim 1,
Obtaining a list of the places includes:
receiving information about a category of a place from a user; and
obtaining a list of the places based on the reference location and the information about the category;
containing,
How to recommend a place.
According to claim 1,
The server includes a server that provides at least one of a map application and a map website,
How to recommend a place.
16. A computer program stored on a medium in combination with hardware to execute the method of any one of claims 1 to 15.
Obtain a list of places corresponding to the reference location,
Corresponding to each of the above places,
Based on the accumulated interest of the place, calculate the quality score of the place,
Calculate the change amount score of the corresponding place based on the distribution of moving average values for each time unit of interest of the corresponding place and the moving average value of the reference time unit,
selecting at least one recommendation target from among the places based on the quality score and the variation score calculated for each of the places;
at least one processor
containing,
server.
18. The method of claim 17,
The processor is
In selecting the recommended target,
determining as an outlier a place that exceeds a first threshold value for an obtained variance score based on a quantile of variance scores of the places;
Setting the change amount score of the place determined as the outlier to the minimum value,
server.
18. The method of claim 17,
The processor is
In calculating the variance score,
calculating the average and standard deviation of the moving average values of previous time units of the reference time unit,
calculating a standard score of the moving average value of the reference time unit based on the standard deviation and the average,
determining the variance score based on the standard score,
server.
18. The method of claim 17,
The processor is
In selecting the recommended target,
corresponding to each of the places, calculating the final score of the corresponding place by summing the quality score of the corresponding place and the variation score of the corresponding place;
selecting at least one of the places to recommend based on the final scores of the places;
server.

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