JP2018160285A - Information processing device, information processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processing device, information processing method, and program capable of performing information provision and sales promotion effective to a user without depending on an ID for identifying the user.SOLUTION: A terminal device includes: acquisition means (control unit 41) that obtains a log of position information of the device itself (terminal device 40); extraction means (control unit 41) that extracts a feature pattern of the position information log on the basis of the position information log obtained by the acquisition means; identification means (control unit 41) that identifies an individual on the basis of the feature pattern extracted by the extraction means; and storage means (storage unit 44) that stores a feature pattern of the position information of the device itself beforehand. In addition, the feature pattern includes at least one pattern of either a moving route between stay places or moving means; and the identification means identifies an individual on the basis of the feature pattern extracted by the extraction means and the feature pattern stored in the storage means.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an information processing apparatus, an information processing method, and a program.

Conventionally, an apparatus that predicts a user's future behavior by analyzing a user's behavior history acquired through a portable terminal device such as a smartphone or a tablet has been proposed.
As an example, an apparatus is disclosed that can predict a user's destination with high accuracy by calculating a behavior class by extracting a combination of characteristic days of the week for each user based on the user's movement history ( For example, see Patent Document 1).

JP 2009-36594 A

  However, the above conventional technique is based on the premise that the user can be continuously identified. User identification requires a user ID for identifying the user (for example, a login ID or a terminal ID for using various services). Cannot be identified. Further, when a user is identified by a terminal ID, the user cannot be identified if the terminal itself changes due to a model change or the like. And as mentioned above, when a user cannot be identified, there exists a subject that effective information provision and a sales promotion cannot be performed with respect to a user.

  An object of the present invention is to provide an information processing device, an information processing method, and a program capable of providing effective information and sales promotion to a user without depending on an ID for identifying the user. To do.

In order to solve the above problems, an information processing apparatus of the present invention provides:
An acquisition means for acquiring a log of position information of the own device;
Extraction means for extracting a feature pattern of the position information log based on the position information log acquired by the acquisition means;
Identification means for identifying an individual based on the feature pattern extracted by the extraction means;
Storage means for storing in advance a feature pattern of position information of the own device;
With
The feature pattern includes at least one pattern of a moving route between moving places and moving means,
The identification means identifies an individual based on the feature pattern extracted by the extraction means and the feature pattern stored in the storage means.

  ADVANTAGE OF THE INVENTION According to this invention, effective information provision and a sales promotion can be performed with respect to a user, without depending on ID for identifying a user.

It is a block diagram which shows the main control structure of each apparatus which comprises the information processing system which concerns on this embodiment. It is a flowchart which shows an example of operation | movement of the information processing system which concerns on this embodiment. It is a figure which shows an example of the table for managing the positional information log of a terminal device. It is a conceptual diagram of the process which identifies a user based on the characteristic pattern of the positional information log of a terminal device. It is a flowchart which shows an example of the information processing of the information processing system which concerns on this embodiment. It is a figure which shows an example of the table which manages the correspondence of the feature pattern determined that a coincidence degree is more than predetermined value, and the certainty degree of user identification. It is a flowchart which shows an example of the information processing of the information processing system which concerns on this embodiment. It is a figure which shows an example of the table which manages the correspondence of the feature pattern determined that a coincidence degree is more than predetermined value, and the certainty degree of user identification.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[1. Description of configuration]
Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.
[1-1. Explanation of system configuration]
First, the configuration of the information processing system 1 according to the present embodiment will be described.
As illustrated in FIG. 1, the information processing system 1 includes a map server 10, an identification server 20 as an information processing device, an advertisement distribution server 30, and a terminal device 40 as an information terminal. . Each device constituting the information processing system 1 is connected to the communication network N. The communication network N is specifically the Internet, a telephone line network of a telecommunications carrier, a mobile phone communication network, or the like.

  The map server 10 is an information device such as a PC or WS (Work Station), and performs a predetermined operation in response to access from the terminal device 40. Specifically, when a route search request from the terminal device 40 to the destination is made, the map server 10 provides the route to the destination to the requesting terminal device 40. The map server 10 is configured by one unit, but is not limited to this, and may be configured by a plurality of devices.

  The identification server 20 is, for example, an information device such as a PC or WS, and analyzes a position information log of the terminal device 40 to extract a feature pattern, thereby identifying an individual possessing the terminal device 40. The identification server 20 is configured by one unit, but is not limited to this, and may be configured by a plurality of devices.

  The advertisement distribution server 30 is, for example, an information device such as a PC or WS, and distributes content related to advertisements and other content such as news to the terminal device 40 via the communication network N. The advertisement distribution server 30 is configured by one unit, but is not limited thereto, and may be configured by a plurality of devices.

  The terminal device 40 is a portable terminal device that is owned and used by each user, such as a smart device such as a smartphone or a tablet, or a mobile phone. The terminal device 40 includes an application (hereinafter referred to as a map application) that performs processing for displaying a map around the current location, route search to the destination, and processing for guiding the guidance route according to the search result. Installed. Further, the terminal device 40 is connected to the map server 10, the identification server 20, the advertisement distribution server 30, and the like using the communication network N (specifically, the communication line of the terminal device 40 or a wireless local area network (LAN)). Communicate with each other.

[1-2. Explanation of map server configuration]
Next, the configuration of the map server 10 will be described.
The map server 10 includes a control unit 11, an operation unit 12, a display unit 13, a storage unit 14, and a communication unit 15.

  The control unit 11 centrally controls the operation of the map server 10. Specifically, the control unit 11 is configured to include a CPU, a ROM, a RAM, and the like, and the map and the program data stored in the ROM or the storage unit 14 developed in the RAM work area and the CPU are used in cooperation with the map. Centrally control each part of the server 10.

The operation unit 12 includes, for example, a character input key, a numeric input key, a keyboard having keys associated with various functions, a pointing device such as a mouse, and the like, and receives an operation input from a user to input the operation. A corresponding operation signal is output to the control unit 11.
The display unit 13 includes a display such as an LCD (Liquid Crystal Display), for example, and displays an image based on the display control signal output from the control unit 11 on the display screen.

  The storage unit 14 is configured by, for example, an HDD (Hard Disk Drive), a semiconductor memory, and the like, and stores data such as program data and various setting data in a readable / writable manner from the control unit 11. The storage unit 14 stores map data and the like. In the map data, for example, map information covering a wide area (corresponding to a plurality of scales), road information, various symbol information such as facilities, seas, rivers, and the like are stored.

  The communication unit 15 is a communication interface having a communication IC (Integrated Circuit), a communication connector, and the like, and performs data communication via the communication network N using a predetermined communication protocol under the control of the control unit 11.

[1-3. Explanation of identification server configuration]
Next, the configuration of the identification server 20 will be described.
The identification server 20 includes a control unit 21, an operation unit 22, a display unit 23, a storage unit 24, and a communication unit 25.

  The control unit 21 centrally controls the operation of the identification server 20. Specifically, the control unit 21 includes a CPU, a ROM, a RAM, and the like. The control unit 21 identifies the program data stored in the ROM or storage unit 24 developed in the RAM work area and the CPU in cooperation. Centrally control each unit of the server 20.

The operation unit 22 includes, for example, a keyboard having a character input key, a numeric input key, and other keys associated with various functions, a pointing device such as a mouse, and the like. A corresponding operation signal is output to the control unit 21.
The display unit 23 includes a display such as an LCD, for example, and displays an image based on the display control signal output from the control unit 21 on the display screen.

  The storage unit 24 includes, for example, an HDD, a semiconductor memory, and the like, and stores data such as program data and various setting data in a readable / writable manner from the control unit 21.

  The communication unit 25 is a communication interface having a communication IC, a communication connector, and the like, and performs data communication via the communication network N using a predetermined communication protocol under the control of the control unit 21.

[1-4. Explanation of configuration of advertisement distribution server]
The advertisement distribution server 30 includes a control unit 31, an operation unit 32, a display unit 33, a storage unit 34, and a communication unit 35.

  The control unit 31 centrally controls the operation of the advertisement distribution server 30. Specifically, the control unit 31 includes a CPU, a ROM, a RAM, and the like. The program data stored in the ROM or the storage unit 34 developed in the work area of the RAM and the CPU cooperate with the advertisement. Centrally controls each part of the distribution server 30.

The operation unit 32 includes, for example, a keyboard having a character input key, a numeric input key, and other keys associated with various functions, a pointing device such as a mouse, and the like. A corresponding operation signal is output to the control unit 31.
The display unit 33 includes, for example, a display such as an LCD, and displays an image based on the display control signal output from the control unit 31 on the display screen.

  The storage unit 34 includes, for example, an HDD and a semiconductor memory, and stores data such as program data and various setting data in a readable / writable manner from the control unit 31.

  The communication unit 35 is a communication interface having a communication IC, a communication connector, and the like, and performs data communication via the communication network N using a predetermined communication protocol under the control of the control unit 31.

[1-5. Description of terminal device configuration]
Next, the configuration of the terminal device 40 will be described.
The terminal device 40 includes a control unit 41, an operation unit 42, a display unit 43, a storage unit 44, a current position detection unit 45, and a communication unit 46.

  The control unit 41 centrally controls the operation of the terminal device 40. Specifically, the control unit 41 is configured to include a CPU, a ROM, a RAM, and the like, and in cooperation with the CPU and program data stored in the ROM or storage unit 44 developed in the RAM work area, the terminal The overall control of each part of the device 40 is performed.

The operation unit 42 includes, for example, a key input unit including a home button and the like, and a touch panel formed integrally with the display unit 43. The operation unit 42 receives an operation input from a user and outputs an operation signal corresponding to the operation input. Output to the control unit 41.
The display unit 43 includes a display such as an LCD or an FPD (Flat Panel Display) using an organic EL (Electro Luminescence) element, and displays an image based on the display control signal output from the control unit 41 on the display screen. To do. For example, the display unit 43 displays various information (for example, display information such as a map screen, icons, route guidance, and the like) based on display data (map data and the like) output from the control unit 41.

  The storage unit 44 is configured by, for example, an HDD, a semiconductor memory, and the like, and stores data such as program data and various setting data in a readable / writable manner from the control unit 41.

  The current position detection unit 45 includes a GPS module and the like. The GPS module includes a GPS antenna and the like. The GPS antenna receives GPS signals transmitted from a plurality of GPS satellites launched into a low earth orbit. The GPS antenna receives GPS signals transmitted from at least three GPS satellites, detects the absolute current position (latitude, longitude) of the terminal device 40 based on the received GPS signals, and sends it to the control unit 41. Output.

  The communication unit 46 includes an antenna and a communication circuit, and performs wireless communication with an external device under the control of the control unit 41. Specifically, the communication unit 46 performs data communication via the communication network N by being relayed by the base station.

[2. Explanation of operation]
Next, a specific operation of the information processing system 1 according to the present embodiment will be described with reference to the flowchart of FIG. Specifically, a process in which the identification server 20 analyzes a position information log of the terminal device 40 to extract a feature pattern and identifies an individual who owns the terminal device 40 will be described. This process is started when the control unit 21 of the identification server 20 acquires the log of the position information of the terminal device 40 transmitted from the map server 10.

First, as a premise, a process until the control unit 21 of the identification server 20 acquires a position information log transmitted from the map server 10 will be described.
First, the control unit 41 of the terminal device 40 acquires the position information of the own device. Here, the position information includes at least the current position (latitude and longitude) detected by the current position detection unit 45 and the time when the current position is acquired.
Next, the control unit 41 transmits the acquired position information to the map server 10 via the communication unit 46.
Each process described above by the control unit 41 of the terminal device 40 is performed as one function of the map application regardless of whether or not the map application installed in the terminal device 40 is activated. These processes are periodically performed at a predetermined interval (for example, at intervals of 5 seconds), but are not limited to this, and can be changed to any interval according to the situation.

  The control unit 11 of the map server 10 manages a log of position information (position information log) transmitted from the terminal device 40 for each terminal device 40. For example, the control unit 11 stores the location information log of the terminal device 40 in the storage unit 14 in association with terminal identification information (for example, a terminal ID, an IP address, etc.) that has some continuity.

  FIG. 3 shows an example of the table T1 for managing the location information log of the terminal device 40. The table T1 has fields of a management number T11 that is a number for managing the location information log so as to be identifiable, terminal identification information T12, and location information log information T13. For example, in FIG. 3, a table T1 including a record in which terminal identification information T12 “00030450” of the terminal device 40 and position information log information T13 “position information log A” are associated with the management number T11 “1” is generated. An example is shown.

  Next, the control unit 11 of the map server 10 transmits the position information log transmitted from the terminal device 40 and stored in the storage unit 14 to the identification server 20 via the communication unit 15. The timing for transmitting the location information log is periodically performed at a predetermined interval (for example, one day interval), but is not limited to this, and can be changed to an arbitrary interval according to the situation.

Through the above processing, the control unit 21 of the identification server 20 acquires the position information log of the terminal device 40 transmitted from the map server 10. That is, the control unit 21 functions as an acquisition unit of the present invention.
Hereinafter, a process in which the identification server 20 analyzes the position information log of the terminal device 40 to extract a feature pattern and identify an individual who owns the terminal device 40 will be described.

  First, as shown in FIG. 2, the control unit 21 of the identification server 20 analyzes the position information log transmitted from the map server 10 and extracts a feature pattern of the position information log (step S101).

  An example of the feature pattern of the position information log is a pattern of staying place and time (for example, date, date, etc.). For example, it is a pattern defined by “where are you at what timing”, such as a pattern of dropping in at a restaurant in Ginza on weekday after 5.

  Another example is a pattern of at least one of a movement route between staying places and moving means (for example, walking, train, bus, etc.). For example, a pattern that uses a route that travels from point A to point B via point C, a pattern that uses a subway line from point A to point B, and the like. The moving means is estimated based on the moving route and the moving speed. For example, when moving in a park at a speed of about 4 to 5 km / h, the moving means is estimated to be “walking”. Further, if the vehicle is moving near 40-50 km / h on the road while stopping near the bus stop, the moving means is estimated to be a “bus”.

  Another example is a weekly behavior pattern. For example, there is a pattern of staying in Yurakucho XX building during the weekday daytime (at work) and staying at Tokyo Dome during the daytime (or at night) on holidays.

  Another example is a reciprocating pattern between home and work. For example, there is a pattern in which the home is a XX apartment in Nerima and the workplace is a XX building in Yurakucho. The home is estimated based on, for example, the position where the stay is the longest and stays at night or a predetermined range including the position (in the case of an apartment, etc.). The workplace is estimated based on, for example, the staying position during the daytime on weekdays. When regular visits to commercial facilities and restaurants are permitted during the round trip between home and workplace, the round trip pattern between home and workplace may include visits to commercial facilities and restaurants.

  Another example is a vibration waveform pattern depending on how to walk. The vibration waveform depending on how to walk is, for example, the walking tempo, the stride, the acceleration, and the like. The vibration waveform according to the way of walking is acquired by, for example, an acceleration sensor (not shown) provided in the terminal device 40 and transmitted from the terminal device 40 to the identification server 20 via the map server 10 at the same time as the position information or at a predetermined timing. Is done.

Another example is a long-term stay weight pattern. The long-term stay weight pattern is a pattern defined by where and how long a person stays, that is, “relative ratio of staying time during long-term stay”. For example, the weight pattern is different between a user who spends a long time resting at a nearby coffee shop and a user who spends a short time resting at a nearby coffee shop for the time spent staying at a XX building. As described above, the relative ratio of the staying time in the long-term stay may be regarded as the feature pattern.
Further, for example, a pattern of staying in the same inn A for many days on a trip (a pattern in which a relatively large amount of travel time is spent in the same inn) is relatively rare, so the weight may be increased. Further, a combination of stores staying for a relatively long time (for example, several minutes or more) may be regarded as a feature pattern.

  Next, the control unit 21 analyzes and digitizes the feature pattern of the position information log extracted in step S101, and evaluates the degree of coincidence (step S102). In the present embodiment, the degree of coincidence is represented by 0 to 100. For example, the control unit 21 digitizes the feature pattern of the position information log extracted in step S101 as it is performed by electronic fingerprint collation, and compares it with a digitized feature pattern that has already been registered. To evaluate the degree of coincidence.

  When evaluating the degree of coincidence in step S102, the specific gravity may be decreased as the number of recorded position information is larger, and the specific gravity may be increased as the number of recorded position information is smaller. Here, the “number of position information to be recorded” includes the number of position information recorded at the same timing (number of position information simultaneously recorded) and the number of position information recorded within a predetermined period (recorded information). Total number of location information). That is, places where anyone goes, such as Tokyo Station and Shibuya Station, are less valuable in personal identification, so the specific gravity is reduced, and places where other users do not go much are highly valuable in personal identification. The specific gravity is increased.

Next, the control unit 21 determines whether or not the degree of coincidence evaluated in step S102 is greater than or equal to a predetermined value (step S103). Here, the predetermined value is a value that supports the possibility that an individual matches, and is, for example, 50.
When it is determined that the degree of coincidence is equal to or greater than the predetermined value (step S103: YES), the control unit 21 proceeds to step S104.
On the other hand, when it is determined that the matching degree is less than the predetermined value (step S103: NO), the control unit 21 determines that the feature pattern does not match the already registered feature pattern, and the position information log extracted in step S101. The feature pattern is registered as a new individual (user) feature pattern (step S105). This registered content is stored in the storage unit 24 of the identification server 20.

FIG. 4 shows a conceptual diagram of processing for identifying a user based on the feature pattern of the position information log of the terminal device 40.
In the example illustrated in FIG. 4, the feature pattern A of the location information log is registered in advance as the feature pattern of the user A, the feature pattern B is the feature pattern of the user B, and the feature pattern C is registered in advance as the feature pattern of the user C. Here, when the feature pattern X is extracted in step S101, the degree of coincidence is evaluated by comparing the feature pattern X with each of the feature pattern A, feature pattern B, and feature pattern C described above. In the example shown in FIG. 4, the degree of coincidence with the feature pattern A is evaluated as 30, the degree of coincidence with the feature pattern B is 10, and the degree of coincidence with the feature pattern C is evaluated as 90. Since the degree of coincidence between the feature pattern A and the feature pattern B is less than the predetermined value 50, it is determined that the feature pattern X does not coincide with the feature pattern A and the feature pattern B. On the other hand, since the degree of coincidence with the feature pattern C exceeds a predetermined value of 50, the feature pattern X is determined to coincide with the feature pattern C, and the user of the feature pattern X is identified as the user C.

  In step S104, the control unit 21 performs the following various information processing based on the degree of coincidence evaluated in step S102.

  As an example of information processing, as shown in the flowchart of FIG. 5, the control unit 21 logs in the identified user based on the degree of coincidence evaluated in step S <b> 102 (that is, the certainty in the accuracy of personal identification). This is a process for controlling the procedure. That is, the control unit 21 functions as a login control unit of the present invention. In the processing of FIG. 5, the certainty factor is, for example, “highest” when the coincidence is 91 to 100, “high” when 81 to 90, “medium” when 71 to 80, and 70 or less. Assume that it is evaluated in four stages of “low”. Note that the certainty factor is not necessarily a configuration evaluated in four stages, and may be a configuration that is input in at least two or more stages. For example, it may be configured to be input in three stages of “high”, “medium”, and “low”.

FIG. 6 shows an example of a table T2 that manages the correspondence relationship between the feature pattern determined to have a degree of matching equal to or greater than a predetermined value in step S103 and the certainty of user identification. The table T2 is generated and updated as appropriate every time the degree of coincidence is determined to be greater than or equal to a predetermined value in step S103. The table T2 has fields of feature pattern information T21, a user T22 identified from the feature pattern, and a certainty factor T23 evaluated based on the degree of coincidence. For example, FIG. 6 illustrates an example in which a table T2 including a record in which the user T22 “user A” and the certainty factor T23 “medium” are associated with the feature pattern information T21 “pattern A” is generated. Reading from the first record of the table T2 that the certainty factor T23 that the user T22 acting on the feature pattern information T21 “pattern A” extracted in step S101 is “user A” is “medium”. it can.
Hereinafter, a process in which the control unit 21 controls the login procedure of the identified user based on the degree of coincidence evaluated in step S102 (that is, the certainty in the accuracy of personal identification) will be described.

First, as shown in FIG. 5, the control unit 21 determines whether or not the certainty factor is “highest” (step S201).
When it is determined that the certainty factor is “highest” (step S201: YES), the control unit 21 proceeds to step S202. The example shown in FIG. 6 corresponds to the case of the feature pattern information T21 “pattern D”.
On the other hand, when the control unit 21 determines that the certainty factor is not “highest” (step S201: NO), the control unit 21 proceeds to step S203.

  In step S <b> 202, the control unit 21 performs an automatic login process for the user in various services (for example, a map application and other contents) associated with the identification server 20. Thereby, since the login process of the user at the time of using the service can be omitted, the user's trouble can be saved. However, for the use of services that strongly require privacy protection, such as access to personal information and product ordering, it is recommended to require a separate password.

In step S203, the control unit 21 determines whether or not the certainty factor is “high”.
When it is determined that the certainty factor is “high” (step S203: YES), the control unit 21 proceeds to step S204. The example shown in FIG. 6 corresponds to the case of the feature pattern information T21 “pattern B”.
On the other hand, when the control unit 21 determines that the certainty factor is not “high” (step S203: NO), the control unit 21 proceeds to step S205.

  In step S204, when the user logs in, the control unit 21 requests input of a password in a state in which only a part of digits are displayed or the user's nickname is displayed. For example, to display the "AB *****" in the column of the ID or, or to display as "Ponta's (the user's nickname) Hello!". Thereby, since the user can omit the input of the ID, the user's trouble can be saved. Further, even if the user identification is wrong, only a part of the ID and the nickname are displayed, so that the privacy of the original user can be protected.

In step S205, the control unit 21 determines whether or not the certainty factor is “medium”.
When the control unit 21 determines that the certainty factor is “medium” (step S205: YES), the control unit 21 proceeds to step S206. The example shown in FIG. 6 corresponds to the case of the feature pattern information T21 “pattern A”.
On the other hand, when it is determined that the certainty factor is not “medium” (step S205: NO), the control unit 21 determines that the certainty factor is “low” and ends the process. The example shown in FIG. 6 corresponds to the case of the feature pattern information T21 “pattern C”. Note that if the certainty factor is determined to be “low”, the control unit 21 requests the input of an ID and a password as usual, because there is not a possibility that the user identification is wrong. Exit.

  In step S <b> 206, when the user logs in, the control unit 21 automatically replenishes the remainder when a part of the ID is input by the user and requests input of a password. Thereby, since the user can omit part of the input of ID, the user's trouble can be saved. In addition, even if the user's identification is wrong, since the specification requires the input of an ID and a password, the original user's privacy can be protected.

  As described above, the convenience of the user and the protection of privacy can be realized by controlling the personal login procedure based on the evaluation of the degree of coincidence of the feature patterns (the certainty of personal identification).

  Another example of information processing is a process in which the control unit 21 converts the pattern content (for example, location, time element, etc.) of the feature pattern of the location information log extracted in step S101 into a hash value. That is, the control unit 21 functions as a hash value conversion unit of the present invention. The hash value is a fixed-length value without regularity obtained from the original data by a predetermined calculation procedure. As for the hash value, the same value is always obtained from the same data, but a completely different value is obtained from even slightly different data. Further, since the hash value is irreversible and undergoes a calculation process including a loss of information amount, the original data cannot be restored from the hash value. In other words, the pattern contents (for example, the pattern in the building on the daytime on weekdays) are not handled as they are, but are converted into hash values and managed to take advantage of the characteristics of hash values as described above. Various operations are possible.

  An example of the operation method is to substitute as user identification information. For example, by converting the pattern content “go to XX store on Tuesday” into a hash value, the hash value can be used as identification information for a user having a feature pattern of “go to XX store on Tuesday”. it can.

Another example is clustering (classifying) users while hiding pattern contents. That is, the users are classified for each user having a common hash value. Note that the contents of the pattern indicated by the hash value cannot be deciphered due to the characteristics of the hash value, but it is indicated that the user group having the same hash value has some common feature pattern.
As described above, by classifying users by using hash values, it is possible to effectively provide information such as advertisement display, service provision, recommendation, and sales promotion to the classified user group.

For example, when the advertisement providing destination has a desire to “advertise to a large number of users”, the user group having a large number of users among the classified user groups via the advertisement distribution server 30 By providing an advertisement to the above, it is possible to satisfy the demand of the advertisement providing destination.
In addition, for example, by providing an advertisement to the classified user group and analyzing the user's reaction to the advertisement, the interest of the user group can be estimated. For example, when a loan advertisement is issued to a group of users via the advertisement distribution server 30, the user's reaction to the advertisement is good (for example, when many users access the advertisement site), the user The group is estimated to be a group of users who are interested in the loan. Therefore, it is possible to provide information and promote sales according to the interests of the user group, such as trying to advertise another loan to the user group or trying to advertise the bank.
Further, by analyzing the user's reaction to the advertisement, for example, it is possible to perform a process of integrating user groups having a common user reaction to the advertisement as one user group. Thereby, information provision and sales promotion can be implemented more effectively.

  In addition, when classifying a user using a hash value, you may make it classify | categorize for every user with the same hash value, and you may make it classify | categorize for every user with the same several hash value. Alternatively, for example, two hash values out of three hash values may be classified for each user.

Another example is to provide it to a partner. In general, a user can accurately grasp a position history (position information log), identify an individual by grasping the position history, or share position history information and personal information between affiliated companies. On the other hand, they have privacy concerns and resistance. However, as shown in this example, when providing user information (pattern contents) to a partner, the pattern contents can be concealed by converting the data into a hash value instead of the data of the pattern contents as they are. As a result, privacy concerns and resistance can be reduced.
In the partner, an advertisement is provided to the user group classified based on the provided hash value, and the interest of the user group is estimated by analyzing the user's reaction to the advertisement. This makes it possible to provide information and promote sales according to the interests of the user group.

As described above, by converting the pattern contents into a hash value based on the feature pattern of the location information log, information can be effectively provided to the user while reducing the privacy concerns and resistance of the user. Promotion can be carried out.
Further, by using a hash value, it is possible to classify each user who takes the same action without specifying (identifying) an individual, that is, who is sending an equivalent lifestyle. This means that taking the same action can be regarded as one attribute (demographic). Therefore, it is possible to provide common information and promote sales to the common terminal device 40 regardless of the presence or absence of personal identification.

  As another example of information processing, as shown in the flowchart of FIG. 7, the control unit 21 identifies the user identified based on the degree of coincidence determined in step S <b> 102 (that is, the certainty in the accuracy of personal identification). It is a process which controls the content (category) of the information provided with respect to. That is, the control unit 21 functions as information control means of the present invention. In the process of FIG. 7, the certainty factor is evaluated in three stages, for example, “high” when the degree of coincidence is 81 to 100, “medium” when it is 61 to 80, and “low” when it is 60 or less. Shall. Note that the certainty factor does not necessarily have to be a configuration that is evaluated in three stages, and may be a configuration that is input in at least two or more stages.

FIG. 8 shows an example of a table T3 for managing the correspondence relationship between the feature pattern determined to have a degree of matching equal to or greater than a predetermined value in step S103 and the certainty of user identification. The table T3 is generated and updated as appropriate every time it is determined in step S103 that the degree of coincidence is greater than or equal to a predetermined value. The table T3 includes fields of feature pattern information T31, a user T32 identified from the feature pattern, and a certainty factor T33. For example, FIG. 8 illustrates an example in which a table T3 including a record in which the user T32 “user A” and the certainty factor T33 “low” are associated with the feature pattern information T31 “pattern A” is generated. It can be read from the first record of the table T3 that the certainty factor T33 that the user T32 acting in the feature pattern information T31 “pattern A” extracted in step S101 is “user A” is “medium”. it can.
Hereinafter, the process in which the control unit 21 controls the content (category) of information provided to the identified user based on the degree of coincidence evaluated in step S102 (that is, the certainty in the accuracy of personal identification). Will be explained.

First, as shown in FIG. 7, the control unit 21 determines whether or not the certainty factor is “high” (step S301).
When it is determined that the certainty factor is “high” (step S301: YES), the control unit 21 proceeds to step S302. The example shown in FIG. 8 corresponds to the case of the feature pattern information T31 “Pattern B” and “Pattern D”.
On the other hand, when the control unit 21 determines that the certainty factor is not “high” (step S301: NO), the control unit 21 proceeds to step S303.

In step S302, the control unit 21 notifies the update information of the SNS content of the user who is a friend on the SNS and the user to the user's terminal device 40 via a web server (not shown) that operates the affiliated SNS. Let For example, when the identified user and the user who is a friend on SNS (Taro Yamada) updated the hill-climbing content, notification of update information “Taro Yamada has updated the hill-climbing content” is notified. Let
The process of notifying the update information of the SNS content of the user and the user who is a friend on the SNS is a process that is highly likely to cause problems such as privacy infringement if the user identification is wrong. Therefore, it is possible to avoid inconvenience by performing only in cases where the possibility that the identification of the user is wrong is small, such as when the certainty factor is evaluated as “high”.

In step S303, the control unit 21 determines whether or not the certainty factor is “medium”.
When it is determined that the certainty factor is “medium” (step S303: YES), the control unit 21 proceeds to step S304. The example shown in FIG. 8 corresponds to the case of the feature pattern information T31 “pattern A”.
On the other hand, when it is determined that the certainty factor is not “medium” (step S303: NO), the control unit 21 determines that the certainty factor is “low” and ends the process. The example shown in FIG. 8 corresponds to the case of the feature pattern information T31 “pattern C”. In addition, when it is determined that the certainty factor is “low”, the control unit 21 ends the process without providing information because there is not a high possibility that the user identification is wrong.

In step S <b> 304, the control unit 21 causes the user terminal device 40 to distribute advertisements according to the user's interests and user attributes via the advertisement distribution server 30. For example, when the identified user is interested in baseball, an advertisement related to baseball is distributed to the user.
Further, in step S304, the control unit 21 displays products that the user has browsed in the past on the display unit 43 of the user's terminal device 40 via a web server (not shown) or the like that manages the affiliated shopping site. Let For example, when the identified user has browsed the cover of the air conditioner in the past, the cover of the air conditioner is displayed on the display unit 43 of the terminal device 40 of the user.
The above process of distributing advertisements according to the user's interests and user attributes and the process of displaying products that have been browsed in the past by the user, even if the user's identification is wrong, privacy infringement, etc. This process is less likely to cause the above problem. Therefore, there is no inconvenience even in a case where there is a high possibility that the identification of the user is wrong, such as when the certainty factor is evaluated as “low”.

  As described above, by controlling the content (category) of information to be provided to the user based on the evaluation of the degree of coincidence of the feature patterns (certainty of personal identification), the user's privacy is protected and the user is protected. Can provide effective information and sales promotion.

[3. effect]
As described above, the information processing apparatus (identification server 20) according to the present embodiment is acquired by the acquisition unit (control unit 21) that acquires the position information log of the information terminal (terminal device 40) and the acquisition unit. An extraction unit (control unit 21) that extracts a feature pattern of the position information log based on the position information log, and an identification unit (control unit 21) that identifies an individual based on the feature pattern extracted by the extraction unit. .
Therefore, according to the information processing apparatus according to the present embodiment, an individual (user) possessing the terminal device 40 can be identified even when an ID for identifying the user cannot be acquired. It is possible to promote individualization of the net service, automatic login, etc. without depending on the ID for identifying the user, and to provide effective information and sales promotion to the user.

In particular, according to the information processing apparatus according to the present embodiment, the feature pattern includes a stay place and time pattern, a travel route between stay places and at least one of movement means patterns, a weekly action pattern, a home and a work place. Includes a reciprocating pattern, a vibration waveform pattern depending on how to walk, a long-term stay weight pattern, and the like.
Therefore, according to the information processing apparatus according to the present embodiment, it is possible to identify an individual according to the pattern for each pattern, so that the identification accuracy can be improved.

In addition, according to the information processing apparatus according to the present embodiment, the identifying unit analyzes the feature pattern extracted by the extracting unit, evaluates the degree of matching between the analyzed feature patterns, and identifies the individual.
Therefore, according to the information processing apparatus according to the present embodiment, it is possible to determine the degree of feature pattern matching when identifying an individual. Therefore, various types of information processing are performed according to the certainty in the accuracy of personal identification. be able to.

Further, according to the information processing apparatus according to the present embodiment, when the degree of coincidence is evaluated, the identification unit reduces the specific gravity as the number of recorded position information is larger, and the number of recorded position information is smaller. Increase the specific gravity as the location.
Therefore, according to the information processing apparatus according to the present embodiment, it is possible to attach importance to a place having high value in personal identification, and thus it is possible to improve the accuracy of personal identification.

In addition, the information processing apparatus according to the present embodiment includes login control means (control unit 21) that controls the login procedure of the identified individual based on the evaluation of the degree of coincidence by the identification means.
Therefore, according to the information processing apparatus according to the present embodiment, the strictness of the login procedure can be differentiated according to the certainty in the accuracy of personal identification, thereby improving the convenience of the user and protecting the privacy. can do.

In addition, the information processing apparatus according to the present embodiment includes information control means (control unit 21) that controls the content of information to be provided to the identified individual based on the degree of coincidence evaluation by the identification means.
Therefore, according to the information processing apparatus according to the present embodiment, the content (category) of information provided to the user can be differentiated according to the certainty in the accuracy of personal identification. It is possible to provide effective information and sales promotion to the user while protecting.

In addition, the information processing apparatus according to the present embodiment includes the hash value conversion unit (control unit 21) that converts the pattern content of the feature pattern extracted by the extraction unit into a hash value.
Therefore, according to the information processing apparatus according to the present embodiment, the pattern contents can be classified for each common user while keeping the content of the pattern confidential, so that the user's privacy concerns and resistance can be reduced while It is possible to effectively provide information and promote sales.

  As mentioned above, although concretely demonstrated based on embodiment which concerns on this invention, this invention is not limited to the said embodiment, It can change in the range which does not deviate from the summary.

[4. Modified example]
For example, in the above-described embodiment, the identification server 20 analyzes the position information log of the terminal device 40 to extract a feature pattern, and performs a process of identifying an individual possessing the terminal device 40. It is not limited to. For example, the terminal device 40 may analyze a log of position information to extract a feature pattern and perform processing for identifying an individual who owns the terminal device 40.

In this case, the user who possesses the terminal device 40 first registers the feature pattern of his / her position information in the terminal device 40 in advance. For example, the commuting route from the home to the workplace, the moving means, and the like are registered in advance as the feature pattern of the own position information. The registered feature pattern is stored in the storage unit 44. That is, the storage unit 44 functions as a storage unit of the present invention.
Next, the control unit 41 of the terminal device 40 acquires the position information of the own device. Next, the acquired position information log is analyzed, and a feature pattern of the position information log is extracted.
Next, the control unit 41 compares an extracted feature pattern of the position information log with a feature pattern registered in advance to identify an individual (user of the own device). As a feature pattern matching method, as in the embodiment, a method may be used in which the feature pattern is digitized to evaluate the degree of coincidence.

According to the above example, the terminal device 40 has the functions of the identification server 20 of the embodiment (particularly, the functions of the acquisition unit, the extraction unit, and the identification unit of the present invention). It can be realized. In this case, the terminal device 40 is an information terminal of the present invention and also functions as an information processing device.
And when the control part 41 of the terminal device 40 identifies as a user of an own apparatus as a result of collating the feature pattern of the extracted positional information log with the feature pattern registered previously, the pattern content of the feature pattern is included. The collation result is transmitted to the identification server 20 and other servers (such as the map server 10 and the advertisement distribution server 30). As a result, for example, in the various services (for example, map application and other contents) that are affiliated, the user is automatically logged in, or the pattern content is converted into a hash value and classified for each user who has a common hash value. Thus, it becomes possible to perform various information processing similar to the embodiment, such as providing information and promoting sales.

  As described above, by identifying an individual based on the extracted feature pattern and the feature pattern stored in the storage unit 44, the processing can be completed only by the terminal device 40, thereby improving the processing speed. And the operating cost of the apparatus can be reduced.

  Moreover, although the said embodiment demonstrated and demonstrated the portable terminal device which each user possesses and uses as the terminal device 40, it is not limited to this. For example, as the terminal device 40, a terminal device used by being mounted on a bicycle, a terminal device installed stationary in an automobile, or the like may be used.

  Moreover, although the map server 10, the identification server 20, and the advertisement delivery server 30 are illustrated and described as separate devices in the above embodiment, the present invention is not limited to this. That is, you may make it comprise the map server 10, the identification server 20, and the advertisement delivery server 30 as an integrated apparatus.

  Moreover, each aspect shown in this application can also be grasped | ascertained as a method, a program, etc. For the method and program categories, “means” shown in the device category is appropriately replaced with “process” or “step”, for example. In addition, the order of processes and steps is not limited to the one directly specified in the present application, and the order can be changed, or a part of processes can be collectively or changed to be executed one by one at any time.

  In addition, the detailed configuration of each device constituting the map server, the identification server, the advertisement distribution server, and the terminal device and the detailed operation of each device can be changed as appropriate without departing from the spirit of the present invention.

DESCRIPTION OF SYMBOLS 1 Information processing system 10 Map server 11 Control part 12 Operation part 13 Display part 14 Storage part 15 Communication part 20 Identification server (information processing apparatus)
21 control unit (acquisition means, extraction means, identification means, login control means, hash value conversion means, information control means)
22 operation unit 23 display unit 24 storage unit 25 communication unit 30 advertisement distribution server 31 control unit 32 operation unit 33 display unit 34 storage unit 35 communication unit 40 terminal device (information terminal)
41 Control Unit 42 Operation Unit 43 Display Unit 44 Storage Unit (Storage Unit)
45 Current position detection unit 46 Communication unit

Claims (14)

An acquisition means for acquiring a log of position information of the own device;
Extraction means for extracting a feature pattern of the position information log based on the position information log acquired by the acquisition means;
Identification means for identifying an individual based on the feature pattern extracted by the extraction means;
Storage means for storing in advance a feature pattern of position information of the own device;
With
The feature pattern includes at least one pattern of a moving route between moving places and moving means,
The information processing apparatus characterized in that the identification means identifies an individual based on the feature pattern extracted by the extraction means and the feature pattern stored in the storage means. Comprising registration means for registering in advance the feature pattern of the position information of the own device;
The storage means stores the feature pattern registered by the registration means,
The information processing apparatus according to claim 1, wherein the characteristic pattern is a commuting route from a home to a workplace and a moving unit.   The information processing apparatus according to claim 1, wherein the feature pattern includes a stay location and a time pattern.   The information processing apparatus according to claim 1, wherein the feature pattern includes a weekly action pattern.   The information processing apparatus according to claim 1, wherein the feature pattern includes a reciprocation pattern of a home and a workplace.   The information processing apparatus according to claim 1, wherein the feature pattern includes a vibration waveform pattern depending on how to walk.   The information processing apparatus according to claim 1, wherein the feature pattern includes a long-term stay weight pattern.   The said identification means analyzes the feature pattern extracted by the said extraction means, evaluates the coincidence degree of the analyzed feature pattern, and identifies an individual, The one of Claims 1-7 characterized by the above-mentioned. The information processing apparatus according to item.   The identification means, when evaluating the degree of coincidence, reduces the specific gravity in a place where the number of recorded position information is large, and increases the specific gravity in a place where the number of recorded position information is small. Item 9. The information processing apparatus according to Item 8.   The information processing apparatus according to claim 8, further comprising: a login control unit that controls a login procedure of the identified individual based on the evaluation of the degree of coincidence by the identification unit.   The information control means which controls the content of the information provided with respect to the identified individual based on the evaluation of the degree of coincidence by the identification means is provided. Information processing device.   The information processing apparatus according to claim 1, further comprising a hash value conversion unit that converts a pattern content of the feature pattern extracted by the extraction unit into a hash value. An information processing method for an information processing apparatus including a storage unit that stores in advance a feature pattern of position information of the own apparatus,
An acquisition step of acquiring a log of location information of the own device;
An extraction step for extracting a feature pattern of the location information log based on the location information log acquired in the acquisition step;
An identification step for identifying an individual based on the feature pattern extracted in the extraction step;
Including
The feature pattern includes at least one pattern of a moving route between moving places and moving means,
An information processing method characterized in that the identifying step identifies an individual based on the feature pattern extracted in the extraction step and the feature pattern stored in the storage means. A computer of an information processing apparatus comprising storage means for storing in advance a feature pattern of position information of the own apparatus
An acquisition means for acquiring a log of position information of the own device;
Extraction means for extracting a feature pattern of the position information log based on the position information log acquired by the acquisition means;
Identification means for identifying an individual based on the feature pattern extracted by the extraction means;
Function as
The feature pattern includes at least one pattern of a moving route between moving places and moving means,
The identification means identifies a person based on the feature pattern extracted by the extraction means and the feature pattern stored in the storage means.

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