JP2016038744A - Area attribute estimation apparatus and area attribute estimation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To estimate attribute information of an area, such as an area where home of a user belongs or an area where a destination of the user belongs, on the basis of a moving history of the user.SOLUTION: An area attribute estimation apparatus acquires position information indicating a position of a user, divides a user moving area into a plurality of areas, determines an area where the user is located, on the basis of the position information, holds history information indicating areas where the user is located, which change as the user moves, determines the frequency of visits for each of the areas, on the basis of the history information, and estimates an area having the highest frequency of visit, as an area where home of the user belongs.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a technique for estimating area attributes.

  Conventionally, in a vehicle-mounted system such as a navigation device, a technique for estimating attribute information of a specific area such as a user's home or work place from a movement history has been proposed (for example, Patent Document 1).

JP 2014-34374 A JP 2009-36594 A

  Conventionally, when estimating the position of a user's home or work place, for example, a point where the parking frequency is high at night on weekdays is estimated as the home, and the point where the person goes out every day during the weekday is estimated as the work place.

  However, this estimation method is based on the premise that the user goes to work during the daytime on weekdays, and can only be applied to a limited lifestyle.

  In addition, in the case of an in-vehicle system, departure / arrival etc. can be determined by turning on / off the ignition. However, information corresponding to turning on / off the ignition can be obtained from portable terminals such as smartphones that have been widely used in recent years. Therefore, it was not possible to estimate the home or work place with the same algorithm as the in-vehicle system.

  Therefore, an object of the present invention is to make it possible to estimate attribute information such as an area to which the user's home belongs and an area to which the user's destination belongs based on the movement history of the user.

The area attribute estimation apparatus according to the present invention is:
A position information acquisition unit that acquires position information indicating the position of the user;
The area where the user moves is divided into a plurality of areas, the area where the user is located is determined based on the position information, and history information indicating the transition of the area where the user is located as the user moves is retained. A history storage unit,
Based on the history information, the frequency of visit for each area is obtained, and the estimation unit that estimates the area with the highest visit frequency as the area to which the user's home belongs,
Have

  In the area attribute estimation device, the estimation unit may estimate the area having the largest amount of movement in the area as the area to which the user's destination belongs among the areas having the visit frequency equal to or higher than a threshold. good.

In addition, the area attribute estimation device according to the present invention,
A position information acquisition unit that acquires position information indicating the position of the user;
The area where the user moves is divided into a plurality of areas, the area where the user is located is determined based on the position information, and history information indicating the transition of the area where the user is located as the user moves is retained. A history storage unit,
Based on the history information, a visit frequency for each area is obtained, and among the areas having the visit frequency equal to or higher than a threshold, the area having the largest amount of movement in the area is estimated as an area to which the user's destination belongs. An estimator to
Have

  The area attribute estimation device may maintain the previous estimation result without the estimation unit estimating the area when the visit frequency is less than a threshold.

  In the area attribute estimation device, the estimation unit may obtain a variation in arrival time for each area based on the history information, and perform the estimation for an area where the variation in arrival time is equal to or greater than a threshold value.

  In the area attribute estimation apparatus, the estimation unit may obtain a stay time for each area based on the history information, and may perform the estimation for an area whose stay time is equal to or greater than a threshold value.

Moreover, the area attribute estimation method according to the present invention includes:
Obtaining position information indicating the position of the user;
The area where the user moves is divided into a plurality of areas, the area where the user is located is determined based on the position information, and history information indicating the transition of the area where the user is located as the user moves is retained. And steps to
Obtaining a visit frequency for each area based on the history information, and estimating the area having the highest visit frequency as an area to which the user's home belongs;
Is executed by the computer.

  The area attribute estimation method may estimate the area having the largest amount of movement in the area among the areas having the visit frequency equal to or higher than a threshold as an area to which the destination of the user belongs.

Moreover, the area attribute estimation method according to the present invention includes:
Obtaining position information indicating the position of the user;
The area where the user moves is divided into a plurality of areas, the area where the user is located is determined based on the position information, and history information indicating the transition of the area where the user is located as the user moves is retained. And steps to
Based on the history information, a visit frequency for each area is obtained, and among the areas having the visit frequency equal to or higher than a threshold, the area having the largest amount of movement in the area is estimated as an area to which the user's destination belongs. And steps to
Is executed by the computer.

  In the area attribute estimation method, when the visit frequency is less than a threshold, the estimation unit may maintain the previous estimation result without estimating the area.

  In the area attribute estimation method, the estimation unit may obtain a variation in arrival time for each area based on the history information, and perform the estimation for an area where the variation in the arrival time is a threshold value or more.

In the area attribute estimation method, the estimation unit may obtain a stay time for each area based on the history information, and perform the estimation for an area whose stay time is equal to or greater than a threshold value.
The contents described in the means for solving the problems can be combined as much as possible without departing from the problems and technical ideas of the present invention. The contents of the means for solving the problems can be provided as a device such as a computer or a system including a plurality of devices, a method executed by the computer, or a program executed by the computer. Further, a recording medium that holds the program may be provided.

  According to the present invention, attribute information such as an area to which the user's home belongs and an area to which the user's destination belongs can be estimated based on the user's movement history.

FIG. 1 is a functional block diagram of the area attribute estimation apparatus. FIG. 2 is an explanatory diagram of a regional mesh. FIG. 3 is a diagram illustrating an example of history information held by the history storage unit. FIG. 4 is a diagram illustrating an example of a feature amount obtained by the estimation unit based on history information. FIG. 5 is an explanatory diagram of the observation date when the feature amount is obtained. FIG. 6 is a diagram illustrating an example of calculating the arrival time information amount. FIG. 7 is an apparatus configuration diagram illustrating an example of a computer. FIG. 8 is a diagram illustrating an example of processing for storing a movement history. FIG. 9 is a diagram illustrating an example of the estimation process. FIG. 10 is a diagram illustrating an example of a home area estimation process. FIG. 11 is a diagram illustrating an example of work area estimation processing. FIG. 12 is a diagram illustrating an example of a home area estimation process according to the first modification. FIG. 13 is a diagram illustrating an example of the estimation process according to the second modification.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. In addition, the following embodiment is an illustration of this invention and this invention is not limited to the following structure.
<Functional explanation>
FIG. 1 is a functional block diagram of the area attribute estimation apparatus according to the present embodiment. The area attribute estimation device of the present embodiment is a user terminal (mobile device) 1 such as a mobile phone, a smartphone, a tablet terminal (slate PC (Personal Computer)), a notebook PC, or a portable game machine that is used by the user. A position information acquisition unit 11, a history storage unit 12, and an estimation unit 13 are included.

The position information acquisition unit 11 is a sensor capable of acquiring position information, such as a GPS (Global Positioning System) receiver, and is position information indicating the position of the user as the position information of the user terminal 1 that is carried by the user and moves with the user. Get as. Further, the position information acquisition unit 11 may acquire the position not only by GPS but also by autonomous navigation using an acceleration sensor.

  The history storage unit 12 divides an area where the user moves into a plurality of areas, determines an area where the user is located based on position information, and represents a transition of the area where the user is located as the user moves. Holds history information.

The estimation unit 13 obtains at least the visit frequency for each area based on the history information, and estimates the area with the highest visit frequency as the area to which the user's home belongs (home area). Moreover, the estimation part 13 estimates the area with the largest amount of movement within an area among the areas where the visit frequency is equal to or greater than the threshold as the area to which the user's destination belongs. Here, the user's destination is a place where the user customarily visits, for example, a work place. The destination may be an employee place engaged in a business of a store or company managed by the user. Further, it may be a place where a club activity or volunteer activity is performed, a school destination, a hospital destination, or the like. In the present application, a destination where these users regularly go is also referred to as a work place for convenience, and an area to which the destination belongs is also referred to as a work area.

In the present embodiment, a regional mesh defined by JIS X0410 of Japanese Industrial Standard is used as this area. FIG. 2 is an explanatory diagram of a regional mesh. The regional meshes are a primary mesh (also referred to as “first regional partition”), a secondary mesh (also referred to as “secondary regional partition”, “integrated regional mesh”), and a tertiary mesh (“third region”). The size of each step of the standard area mesh such as “next area section” and “reference area mesh”, and the divided area mesh such as the half area mesh, the quarter area mesh, and the eighth area mesh. It is composed of meshes and is specified by a mesh code indicating each mesh.

  The primary mesh is obtained by dividing an area into a substantially rectangular area having a side length of about 80 km, and the primary mesh code is an upper two-digit number representing latitude and a lower 2 representing longitude. It is expressed as a 4-digit number consisting of a numeric value. The secondary mesh is obtained by dividing the primary mesh into eight equal parts in the east-west direction and the north-south direction, respectively, and the secondary mesh code is the first one digit representing the latitude direction and the last one digit representing the longitude direction. This is expressed in a format in which a two-digit number consisting of the following numbers is connected to the primary mesh code by “-(hyphen)”. The tertiary mesh is obtained by dividing the secondary mesh into 10 equal parts in the east-west direction and the north-south direction, respectively. The tertiary mesh code is a first digit representing the latitude direction and a last digit representing the longitude direction. This is expressed in a form in which a two-digit number consisting of a number of 1 is connected to a primary mesh code and a secondary mesh code. The half-region mesh is the third mesh divided into two equal parts in the east-west direction and north-south direction. The half-region mesh code is 1 for the southwest region, 2 for the southeast region, and northwest. The area is 3 and the area in the northeast is 4 and is expressed in a form connected to the primary to tertiary mesh codes. The quarter region mesh is a halve of the half region mesh in the east-west direction and the north-south direction. The quarter region mesh code is 1 for the southwest region and 2 for the southeast region. , The northwest region is 3 and the northeast region is 4, and is expressed in a format connected to the primary to half-region mesh codes. One-eighth region mesh is a quarter-region mesh divided into two equal parts in the east-west direction and north-south direction. The eighth-region mesh code is 1 for the southwest region and 2 for the southeast region. , The northwest region is 3 and the northeast region is 4, and is expressed in a format connected to the primary to quarter region mesh codes.

  The history storage unit 12 obtains the mesh code of the mesh where the user terminal 1 is located from the position information including the latitude and longitude acquired by the position information acquisition unit 11. That is, position information including latitude and longitude is converted into a regional mesh code. Note that the process of converting the position information into the regional mesh code can be performed using an existing algorithm, and thus details are omitted. Further, the area in the present embodiment is not limited to an existing area mesh, and a mesh that is divided into a mesh shape having a position and size uniquely determined for the area may be used.

  By using the regional mesh code in this way, it is possible to reduce the cost for updating and managing the map information as compared with the case of using the map information.

  FIG. 3 is a diagram illustrating an example of history information held by the history storage unit 12. As shown in FIG. 3, the history information stores arrival date / time, arrival area, departure date / time, destination area, and the like in association with each other. The arrival date and time is information indicating the date and time of arrival in the arrival area. The arrival area is a mesh code indicating the area that has arrived. The departure date and time is information indicating the date and time of movement from the arrival area. The movement destination area is a mesh code indicating the area after movement. In addition, when the arrival area and the destination area are the same, the movement within the same area is shown.

Since the area attribute estimation device of the present embodiment is a user terminal (mobile device) 1 such as a smartphone, it is activated by turning on the ignition switch of the vehicle at the time of departure, unlike a conventional in-vehicle device, Arriving and turning off the ignition switch of the vehicle does not stop the operation, and it is difficult to detect departure or arrival. Therefore, in this embodiment, it is assumed that the position information is periodically acquired and moved when the distance is more than a predetermined distance compared to the previous position information, and is not moved when the distance is not more than the predetermined distance. As a thing (staying), the departure time and the arrival time are obtained every time it moves. For example, it is assumed that the user has moved when position information at a position 10 m or more away from the previous position information is detected, and the arrival time at the position detected this time and the departure time of the position detected last time are stored. Specific position information (latitude, longitude, etc.) used for this comparison may be stored as history information together with the mesh code, or may be held in the memory for a predetermined period.

  The position detected in the predetermined period is not limited to the comparison with the previously detected position, and the position detected within the predetermined period may be compared with the position detected this time, and may be moved when the distance is more than a predetermined distance. In this case, the distance from the center of gravity of the position detected within the predetermined period to the position detected this time, the distance from the center of the mesh to which the position detected within the predetermined period and the representative points such as the four corners to the position detected this time, It is good also as what moved when it was away from the predetermined distance or more.

  Further, the departure time and arrival time are not limited to each detection position, but may be determined for each area or each destination. For example, it is assumed that the location information is periodically acquired and moved when the area to which the current location information belongs is different from the area to which the previous location information belongs, and is not moved when it is the same. As a thing (staying), the departure time and the arrival time are obtained every time it moves. For example, when the previous time is area A and this time is area B, it is assumed that the user has moved from area A to area B, and the arrival time to area B and the departure time of area A are stored.

  Here, when the work place exists over a plurality of areas (for example, areas A and B), it may be determined that the work place is moving despite staying at the work place. For this reason, an area that has been visited within a predetermined period may be regarded as one area (area group), and the arrival time and departure time of this area may be stored. For example, area A → Area B → Area A → Area B → Area C → Area D is first located in Area A, and after coming and going between Area A and Area B, it is adjacent to Area B When moving to area C and then moving to area D adjacent to area C, areas A and B are regarded as one area, and the first time in area A is taken as the arrival time. The time of moving to the area C that is not adjacent, or the time of moving to the area D that is not adjacent to the areas A and B may be set as the departure times of the areas A and B.

  Furthermore, according to the staying time of each area, an area or a group of areas staying for a predetermined time (for example, 1 hour) or more may be set as a destination (staying place), and departure time and arrival time to the destination may be stored. For example, when moving from area A to area F via areas B, C, D, and E, the stay time in areas A and F is longer than a predetermined time, and the stay time in areas B, C, D, and E is predetermined. If it is less than the time, the area F is the destination for the area A, the time of moving from the area A to the area B is the departure time of the area A, and the time of arrival of the area F via the area E is the arrival time of the area F As for areas B, C, D, and E, storage of departure time and arrival time may be omitted. Thus, by using the departure time and arrival time limited to the destination (stay place), it is possible to improve the accuracy of estimation described later. The departure time and arrival time to the destination, the departure time and arrival time for each area, and the departure time and arrival time for each detection position may be stored, and any departure time and arrival time can be estimated. It may be selected as appropriate for use.

  FIG. 4 is a diagram illustrating an example of a feature amount obtained by the estimation unit 13 based on history information, and FIG. 5 is an explanatory diagram of an observation date when the feature amount is obtained. As illustrated in FIG. 4, the estimation unit 13 of the present embodiment obtains a visit frequency, an average stay time, an average number of movements, a departure time information amount, and an arrival time information amount as feature amounts.

  The visit frequency is a value (unit: days) obtained by dividing the number of days of visiting the area (mesh) by the number of observation days. In this example, since the number of visits is counted every day, the number of days visited is counted as 1 even when visiting multiple times a day. The number of observation days is the number of days to acquire data for calculating the feature quantity, and the data is acquired by going back a day having valid data from the starting day as shown in FIG. 5 by a predetermined number of days. . In the example of FIG. 5, when the area attribute is determined on July 25, the data for the current day is not yet prepared, so the data is acquired retroactively for a predetermined number of days (for example, six days) from July 25. At this time, holidays and long vacation periods are often excluded because they often take different actions and may not be valid data. Note that the long vacation period is New Year's holiday or Golden Week, and is arbitrarily set. Moreover, the day when the user terminal 1 was not normally used, for example, the day when it was not carried by the user or the day when the power was turned off is excluded. In the example of FIG. 5, since July 21 is a holiday, it will be excluded, and July 24 will be excluded because it is out of power, and data for 6 observation days will be acquired retroactively to July 17. To do. That is, in an area where the number of visit days from July 17 to July 23 is 5, the number of visit days (5 days) / the number of observation days (6 days) = visit frequency (0.833...).

  The average stay time is calculated by summing up the difference between the departure date and time and the arrival date and time (departure date and time-arrival date and time) for each mesh code as the time spent in the area (mesh) and dividing by the number of visit days.

Departure time information amount is the information amount of time distribution that departs from the area (mesh) (unit: bit)
It is also a value indicating the variation in departure time, and takes a large value if the variation in departure time is large, and takes a small value if the variation in departure time is small. For example, a day is divided into a predetermined number of time zones (in this example, 24 time zones in increments of 1 hour), and the number of departures from that area to another non-adjacent area is counted for each time zone to obtain a frequency distribution. It was. In other words, the frequency distribution was obtained by excluding cases of movement within an area or movement between adjacent areas. In calculating the frequency distribution, a pseudo count may be added to the value of each time zone.

The arrival time information amount is the information amount of time distribution arriving at the area (mesh) (unit: bit)
It is also a value indicating the variation in arrival time, and takes a large value if the arrival time variation is large, and takes a small value if the arrival time variation is small. For example, a day is divided into a predetermined number of time zones (in this example, 24 time zones in increments of 1 hour), and the number of times of arrival in this area after leaving another area not adjacent to each time zone is counted. The distribution was determined. In other words, the frequency distribution was obtained by excluding cases of movement within an area or movement between adjacent areas. In calculating the frequency distribution, a pseudo count may be added to the value of each time zone. For example, in order to be able to quickly reflect in the estimation results that the home or work place has changed due to moving or moving, it is necessary to set the observation period to be short and to be able to estimate from the data within this short observation period. There is. However, if the observation period is set to be short, the appearance frequency of an event with a low appearance frequency becomes almost zero, which is not correctly reflected in the estimation result, and a so-called zero frequency problem occurs. Therefore, the pseudo count is added to the value of each time zone to correct the appearance frequency of the event having a low appearance frequency, thereby avoiding the zero frequency problem. Note that the value of the pseudo count may be changed according to the length of the observation period, the range (width) of the feature amount used for estimation, variation, and the like. It may be obtained and stored as a relational expression or a data table, and a pseudo count value corresponding to an observation period or a feature amount may be used during estimation processing.

FIG. 6 is a diagram illustrating an example of calculating the arrival time information amount. In the example of FIG. 6, the observation days are 20 days, the number of arrivals is counted in 24 time zones from 0 to 23:00, incremented by 1, and the logarithm of the logarithm is calculated using equation (1). The calculation result when the base is 2 is obtained as the arrival time information amount. The arrival probability Pt is a value obtained by dividing the number of arrivals including the pseudo count by the total. Also, the departure time information amount can be obtained in the same manner using equation (1).

<Device configuration>
FIG. 7 is an apparatus configuration diagram illustrating an example of a computer (information processing apparatus). The user terminal 1 is a computer as shown in FIG. 7, for example. 7 includes a CPU (Central Processing Unit) 1001, a main storage device 1002, an auxiliary storage device (external storage device) 1003, a communication IF (Interface) 1004, an input / output IF (Interface) 1005, a drive device 1006, A communication bus 1007 is provided. The CPU 1001 performs processing and the like according to this embodiment by executing a program. The main storage device 1002 caches programs and data read by the CPU 1001 and develops a work area of the CPU. Specifically, the main storage device is a RAM (Random Access Memory), a ROM (Read Only Memory), or the like. The auxiliary storage device 1003 stores programs executed by the CPU 1001, position information, and the like. Specifically, the auxiliary storage device 1003 is an HDD (Hard-disk Drive), an SSD (Solid State Drive), an eMMC (embedded Multi-Media Card), a flash memory, or the like. Main storage device 1002 and auxiliary storage device 100
3 functions as the history storage unit 12 of the user terminal 1. The communication IF 1004 transmits / receives data to / from other computers. The user terminal 1 is connected to a network via a communication IF 1004. The communication IF 1004 is specifically a wired or wireless network card or the like. The input / output IF 1005 is connected to the input / output device and accepts input from the user or outputs information to the user. Specifically, the input / output device is a keyboard, a mouse, a display, a touch panel, an acceleration sensor, or the like. The drive device 1006 reads data recorded on a storage medium such as a magnetic disk, a magneto-optical disk, and an optical disk, and writes data to the storage medium. The above components are connected by a communication bus 1007. A plurality of these components may be provided, or some of the components (for example, the drive device 1006) may not be provided. Further, the input / output device may be integrated with the computer. In addition, the program executed in this embodiment is provided via a portable storage medium readable by the drive device 1006, a portable auxiliary storage device 1003 such as a flash memory, a communication IF 1004, and the like. It may be. Then, the CPU 1001 executes the program, thereby causing the computer as shown in FIG. 7 to work as the user terminal 1 shown in FIG.

<Estimation method>
Next, the detail of the process which the user terminal 1 performs according to a program is demonstrated. The user terminal 1 stores a movement history as the user moves, and estimates a home area, a work area, and the like based on the movement history.

  FIG. 8 is a diagram illustrating an example of processing for storing a movement history. The user terminal 1 starts the process of FIG. 8 at a predetermined timing. For example, the process of FIG. 8 may be started periodically every hour or every 15 minutes, or when the movement of the user terminal 1 is detected by an acceleration sensor, the process of FIG. 8 may be started. .

  When the process of FIG. 8 is started, the user terminal 1 first acquires the latitude and longitude of the position where the user terminal 1 exists as the position information of the user by the GPS receiver as the position information acquisition unit 11 (step S10).

  Moreover, the user terminal 1 converts the acquired latitude and longitude into a mesh code by the function of the history storage unit 12, and specifies the area where the user is located (step S20).

Then, the user terminal 1 associates the mesh code with the time by the function of the history storage unit 12 to obtain history information as shown in FIG. Here, the history storage unit 12 stores the time of arrival at the position as the arrival date and time, and the time of movement from the position as the departure date and time.

  FIG. 9 is a diagram illustrating an example of the estimation process. The estimation unit 13 of the user terminal 1 executes the process of FIG. 9 at a predetermined timing. For example, the processing in FIG. 9 may be started periodically every 6 hours or every 24 hours, or when a request is received from another application or system, or when the user selects activation, FIG. The process may be started.

  When the process of FIG. 9 is started, the user terminal 1 first reads data for a predetermined number of observation days from the storage device, and calculates the feature amount as shown in FIG. 4 (step S110).

Further, the user terminal 1 merges the feature amounts of adjacent areas based on the calculated feature amount (step S120). For example, the feature amounts (vectors) calculated in step S110 are arranged in descending order of visit frequency. For an area (mesh code) whose visit frequency is second or lower, it is checked whether there is an adjacent area among those having a higher rank than the area.
If there are adjacent areas, they are merged as one area having the same attribute as when, for example, a work place extends over a plurality of areas, and the feature values of this area are also merged. The mesh code of the merged area is the mesh code of the area having the highest visit frequency rank among the plurality of merged areas. When merging visit frequencies, a set sum is taken for each visit date (arrival date), and the sum is summed and divided by the number of observation days to obtain a visit frequency. When merging the average stay time, the values before dividing by the number of visit days are totaled and then divided by the visit days to obtain the average stay time. When merging the average number of movements, return to the history information, count the number of movements in the merged area for each observation date, add them, and divide by the number of visits to obtain the average number of movements. When merging departure time information amounts, return to the history information, find the departure time to leave the merged area, divide the day into a predetermined number of time zones, and depart from the merged area to other areas for each time zone The frequency distribution is obtained using the equation (1) in FIG. 6 as described above. When merging the amount of arrival time information, return to the history information, find the arrival time that arrived in the merged area, divide the day into a predetermined number of time zones, and arrived at the merged area from other areas for each time zone The number of times is counted, and the frequency distribution is obtained using Equation 1 as described above.

  Then, the user terminal 1 performs home area estimation (step S130) and work area estimation (step S140) using the feature amounts calculated in step S110 and step S120.

  FIG. 10 is a diagram illustrating an example of a home area estimation process. First, the user terminal 1 determines whether or not the visit frequency of each area exceeds a predetermined threshold (step S210).

  Then, the user terminal 1 estimates that the area with the highest visit frequency among the areas where the visit frequency exceeds the threshold is the home area (step S220).

  On the other hand, when it is determined in step S210 that none of the areas exceeds the threshold, the previous estimation result is taken over without estimating the home area (step S230).

  FIG. 11 is a diagram illustrating an example of work area estimation processing. First, the user terminal 1 determines whether or not the visit frequency of each area exceeds a predetermined threshold (step S310). The threshold in step S310 may be set lower than the threshold in step S210 described above.

Then, the user terminal 1 estimates the area where the average number of movements is the largest among the areas where the visit frequency exceeds the threshold and is not set as the home area in step S130 as the work area (step S320). ).

  On the other hand, when it is determined in step S310 that none of the areas exceeds the threshold, the previous estimation result is taken over without estimating the work area (step S330).

  As described above, according to the present embodiment, the home area and the work area can be accurately estimated according to the movement history of the user. In other words, the user can automatically set the home area or work area without requiring the user to input the work area. As a result, it can be used for route setting in a navigation system, selection of an information provision area in a recommendation system, and the like.

  In addition, by adopting conditions that can be estimated in a short period of time and repeating the estimation process and updating the estimation result as needed, it is possible to follow changes in the home or work place due to moving or moving.

  In addition, if the estimation conditions are temporarily not met on a business trip or a trip, maintaining the previous results without performing the estimation may change the home area or work place unnecessarily. It is preventing.

<Modification 1>
In the general lifestyle, the frequency of visiting the home area is the highest as described above. However, in the case of a lifestyle that involves, for example, railways, hospitals, police, and fire fighting, and takes a nap at work, the frequency of home area visits may be low. Therefore, the home area may be estimated using the arrival time information amount.

  FIG. 12 is a diagram illustrating an example of a home area estimation process according to the first modification. Note that the first modification is different from the first embodiment in the configuration using the arrival time information amount, and the other configurations are the same, and thus redundant description is omitted. The user terminal 1 of this example determines whether or not the visit frequency of each area exceeds a predetermined threshold (step S210), and the arrival time information amount is predetermined among the areas where the visit frequency exceeds the threshold. Are extracted (step S215), and the extracted area having the highest visit frequency is estimated as the home area (step S220).

  On the other hand, when it is determined in step S210 that none of the areas exceeds the threshold, the previous estimation result is taken over without estimating the home area (step S230).

  As described above, in the first modification, the home area is estimated when the arrival time information amount is equal to or greater than the threshold and the visit frequency is maximum. Since the amount of arrival time information is a value indicating the variation in time of arrival in the area, it is small in an area where employees work at a fixed time, such as a work place, and large in an area where arrival time is not defined, such as at home. is expected. By estimating the home area using the arrival time information amount being equal to or greater than the threshold, the home area can be estimated with higher accuracy.

  In this modification, the area where the arrival time information amount is greater than or equal to the predetermined threshold is extracted in step S215. However, the present invention is not limited to this, and an area having a larger arrival time information amount than the departure time information amount may be extracted. Alternatively, an area in which the ratio of the arrival time information amount to the departure time information amount (arrival time information amount / departure time information amount) is equal to or greater than a threshold may be extracted.

<Modification 2>
As described above, the frequency of visits to the home area and the work area is usually high, but the frequency of visits to the nearest station and transfer station may also be high. In addition, if a shopping mall is added to these stations, the average number of movements may be high. However, these are passing points, and the staying time is different from the home area or work area. For this reason, you may estimate a home area or a work area using average stay time.

  FIG. 13 is a diagram illustrating an example of the estimation process according to the second modification. In addition, since this modification 2 differs in the structure which used the average stay time compared with the above-mentioned Embodiment 1, and the other structure is the same, the overlapping description is abbreviate | omitted.

  When the processing of FIG. 13 is executed at a predetermined timing, the estimation unit 13 of the user terminal 1 calculates feature amounts as described above (step S110), merges the feature amounts of adjacent areas (step S120), and Among these, an area where the average stay time is a predetermined threshold or more is extracted (step S125).

  Then, the user terminal 1 performs estimation of the home area (step S130) and estimation of the work area (step S140) using the feature amount of the area extracted in step S125.

  As described above, in the second modification, the home area and the work area are estimated for the area where the average stay time is equal to or greater than the threshold value, so that data of simple passing points can be eliminated and the home area and the work area can be estimated with high accuracy. can do.

<Others>
The present invention includes a computer program that executes the above-described processing. Furthermore, a computer-readable recording medium on which the program is recorded also belongs to the category of the present invention. The recording medium on which the program is recorded can be estimated by causing the computer to read and execute the program on the recording medium.

  Here, the computer-readable recording medium refers to a recording medium in which information such as data and programs is accumulated by electrical, magnetic, optical, mechanical, or chemical action and can be read from a computer. Examples of such a recording medium that can be removed from the computer include a flexible disk, a magneto-optical disk, an optical disk, a magnetic tape, and a memory card. In addition, examples of the recording medium fixed to the computer include a hard disk drive and a ROM.

  In the above embodiment and the modification, the example in which the area attribute estimation device is realized by a user terminal such as a smartphone carried by the user is shown. However, the present invention is not limited to this, and the area attribute estimation device includes the position information acquisition unit 11, history As long as it has the memory | storage part 12 and the estimation part 13, another structure may be sufficient. For example, a user carries a terminal having a position information acquisition unit 11 and a history storage unit 12 like a GPS logger, and a computer having an estimation unit 13 acquires history information from the terminal via a network to obtain a home area. And the structure which estimates a work area may be sufficient.

1 user terminal 2 network 11 position information acquisition unit 12 history storage unit 13 estimation unit

Claims (8)

A position information acquisition unit that acquires position information indicating the position of the user;
The area where the user moves is divided into a plurality of areas, the area where the user is located is determined based on the position information, and history information indicating the transition of the area where the user is located as the user moves is retained. A history storage unit,
Based on the history information, the frequency of visit for each area is obtained, and the estimation unit that estimates the area with the highest visit frequency as the area to which the user's home belongs,
An area attribute estimation device. A position information acquisition unit that acquires position information indicating the position of the user;
The area where the user moves is divided into a plurality of areas, the area where the user is located is determined based on the position information, and history information indicating the transition of the area where the user is located as the user moves is retained. A history storage unit,
Based on the history information, a visit frequency for each area is obtained, and among the areas having the visit frequency equal to or higher than a threshold, the area having the largest amount of movement in the area is estimated as an area to which the user's destination belongs. An estimator to
An area attribute estimation device.   The area attribute estimation device according to claim 1 or 2, wherein when the visit frequency is less than a threshold, the estimation unit maintains the previous estimation result without estimating the area.   The said estimation part calculates | requires the dispersion | variation in the arrival time for every said area based on the said log | history information, and performs the said estimation about the area where the dispersion | variation in the arrival time is more than a threshold value. Area attribute estimation device.   The area attribute estimation device according to any one of claims 1 to 4, wherein the estimation unit obtains a stay time for each area based on the history information, and performs the estimation for an area having the stay time equal to or greater than a threshold value. . Obtaining position information indicating the position of the user;
The area where the user moves is divided into a plurality of areas, the area where the user is located is determined based on the position information, and history information indicating the transition of the area where the user is located as the user moves is retained. And steps to
Obtaining a visit frequency for each area based on the history information, and estimating the area having the highest visit frequency as an area to which the user's home belongs;
An area attribute estimation method executed by a computer. Obtaining position information indicating the position of the user;
The area where the user moves is divided into a plurality of areas, the area where the user is located is determined based on the position information, and history information indicating the transition of the area where the user is located as the user moves is retained. And steps to
Based on the history information, a visit frequency for each area is obtained, and among the areas having the visit frequency equal to or higher than a threshold, the area having the largest amount of movement in the area is estimated as an area to which the user's destination belongs. And steps to
An area attribute estimation method executed by a computer. Obtaining position information indicating the position of the user;
The area where the user moves is divided into a plurality of areas, the area where the user is located is determined based on the position information, and history information indicating the transition of the area where the user is located as the user moves is retained. And steps to
Based on the history information, a visit frequency for each area is obtained, and among the areas having the visit frequency equal to or higher than a threshold, the area having the largest amount of movement in the area is estimated as an area to which the user's destination belongs. And steps to
Area attribute estimation program for causing a computer to execute.

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