JP6767440B2 - Information processing equipment, information processing methods and information processing programs - Google Patents

Description

Embodiments of the present invention relate to information processing devices, information processing methods and information processing programs.

In recent years, information distribution via the Internet has been actively carried out. For example, there is known a technique of arranging and displaying advertising contents such as still images, moving images, and texts related to a company or a product at a predetermined position on a web page. By the way, a technique is known in which a user having a communication terminal can easily find a target product.

Japanese Unexamined Patent Publication No. 2003-166847

However, with the above-mentioned conventional technique, it is not always possible to specify the action performed by the user in the facility with high accuracy. For example, in the above-mentioned prior art, navigation information from the current position to the display position of the product is generated from the comparison between the current position information and the display position information, and the generated navigation information is displayed on the terminal.

Then, in order to enable navigation in the above-mentioned conventional technology, it is necessary to install a plurality of transmitting units for transmitting identification information to the communication terminal in the store, and depending on the installation location, the information can be accurately transmitted from the transmitting unit. It is not always possible to obtain it. Therefore, in the above-mentioned conventional technique, it is not always possible to accurately identify the action taken by the user in the situation where the positioning of the user in the facility (indoor) cannot be performed.

The present application has been made in view of the above, and an object of the present application is to provide an information processing device, an information processing method, and an information processing program capable of specifying an action performed by a user in a facility with high accuracy. ..

The information processing apparatus according to the present application indicates the position of the user in the facility based on the characteristics of a predetermined space in the facility in a state where the position of the user cannot be positioned based on an external signal from outside the facility. It is characterized by having an acquisition unit for acquiring position information and a specific unit for specifying an action performed by the user in the facility based on the position information acquired by the acquisition unit.

According to one aspect of the embodiment, there is an effect that the action performed by the user in the facility can be specified with high accuracy.

FIG. 1 is a diagram showing an example of the first information processing according to the embodiment. FIG. 2 is a diagram showing an example of the second information processing according to the embodiment. FIG. 3 is a diagram showing a configuration example of the information processing device according to the embodiment. FIG. 4 is a diagram showing an example of the behavior information storage unit according to the embodiment. FIG. 5 is a diagram showing an example of a model information storage unit according to the embodiment. FIG. 6 is a diagram showing an example of the magnetic information storage unit according to the embodiment. FIG. 7 is a flowchart showing an example of the first information processing according to the embodiment. FIG. 8 is a flowchart showing an example of the second information processing according to the embodiment. FIG. 9 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device.

Hereinafter, an information processing apparatus, an information processing method, and a mode for carrying out an information processing program (hereinafter, referred to as “the embodiment”) according to the present application will be described with reference to the drawings. Note that this embodiment does not limit the information processing apparatus, information processing method, and information processing program according to the present application. Further, in the following embodiments, the same parts are designated by the same reference numerals, and duplicate description is omitted.

[1. Outline of the first information processing]
First, with reference to FIG. 1, the outline of the first information processing among the information processing according to the embodiment is shown. FIG. 1 is a diagram showing an example of the first information processing according to the embodiment. The first information processing is performed by the information processing apparatus 100.

The first information processing will be described in detail later, but the action performed by the user is specified and specified among the stepwise actions leading up to the predetermined action based on the position information indicating the position of the user. The advertising effectiveness is judged based on the actions taken.

Further, the information processing system according to the embodiment includes a terminal device 10 and an information processing device 100. Further, the first information processing is performed by the information processing device 100 shown in FIG. For example, the information processing device 100 is realized by one or more devices such as a server device and a cloud system, and is connected to a terminal device 10 used by a user via a network such as a mobile communication network or a wireless LAN (Local Area Network). It is an information processing device that can communicate.

The terminal device 10 is an information processing device used by the user. The terminal device 10 is, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. In addition, the terminal device 10 displays various contents such as advertising contents.

Here, the premise that the first information processing is performed by the information processing apparatus 100 will be described. For example, an advertiser advertises its products, services, human resources, etc. by providing various forms of advertising content. The forms of advertising content include Internet advertisements, TV commercials, traffic advertisements, outdoor advertisements using signboards and signage, and distribution leaflets.

For example, an advertiser attempts to enhance advertising effectiveness by providing various forms of advertising content by uploading advertising content to an advertising distributor and paying advertising expenses. In addition, the ad distributor is better for the advertiser by feeding back the visualized data to the advertiser by visualizing how much the submitted ad content actually affected the user. Use it as a material for studying advertising methods.

However, it is not easy to visualize how much the advertising content actually affected the user and how much the advertising content directly affected the advertiser's business KPI. For example, it is possible to monitor the subsequent behavior of users who come into contact with Internet advertisements on the Internet (online), but the behavior of users is not limited to online behavior, that is, behavior in the real world, that is, There is also offline action. As a result, for example, what kind of actions a user who comes into contact with the advertising content takes in stages offline will eventually lead to conversion related to the advertising content, and what kind of behavior offline will lead to the conversion of the advertising content. It is not easy to visualize whether it is influenced by.

That is, it is not easy to judge or evaluate the influence of the advertising content from the side of the user's stepwise behavior. For this reason, in the present embodiment, among the stepwise actions, the advertising effect is measured using the user's time and location information for each action at each stage. As an example, elements (anchors) for acquiring time and position in relation to advertising content are installed in advance in the real space of each place. Anchor can be understood as an offline version of a cookie for online behavior tracking, and its position is to identify the current location and cut out the state of the moment. In the present embodiment, the anchor is a beacon and a script incorporated in the advertising content, but it does not necessarily have to be a beacon. For example, the anchor may be various sensors (eg, magnetic sensor, optical sensor, etc.).

Beacons, which are anchors, are, for example, information processing devices that deliver advertising content, stations, roads (electric poles beside roads), and predetermined locations (for example, common areas such as corridors) in facilities related to advertising content (for example, actual stores). , Product shelves, etc.), etc., which are elements that are installed anywhere. Then, in the present embodiment, the user's action is time and position information for each action at each stage among the stepwise actions directly or indirectly related to the predetermined advertising content by the anchor alone or the interaction between the anchors. Identify from the perspective of. Specifically, in the present embodiment, a stepwise action from ad creative submission to conversion is defined, and the ad effectiveness is measured using time and location information throughout all phases of the stepwise action. In the following embodiments, stepwise actions or actions at each stage may be referred to as "funnel".

Then, based on the above premise, the information processing apparatus 100 according to the embodiment performs the first information processing shown in FIG. Specifically, the information processing device 100 acquires position information indicating the user's position, and based on the acquired position information, identifies an action performed by the user among stepwise actions leading up to a predetermined action. To do. Then, the information processing device 100 determines the advertising effect based on the specified action.

More specifically, the information processing device 100 is a stepwise action from the user's contact with the predetermined advertising content to the conversion related to the advertising content as a stepwise action leading to the predetermined action. Among the actions, identify the action performed by the user. Further, the information processing device 100 is a probability output by inputting position information and time information to a model generated based on a stepwise action leading up to a predetermined action, and the predetermined action is performed. Based on the probability that the user performs the stepwise action up to that point, the action performed by the user is specified among the stepwise actions up to the predetermined action.

Hereinafter, an example of the first information processing according to the embodiment will be described with reference to FIG. Although FIG. 1 shows an example in which only the position information is input to the model, the time information is also actually input.

First, the overall picture of FIG. 1 will be briefly described. First, it is assumed that the user U1 has the terminal device 10 and starts moving after contacting the advertisement content AD1 (viewing the advertisement content AD1). Further, the advertising content AD1 is an advertising content that advertises the product PD1. In addition, the product PD1 is sold at the shop SH1, which is an actual store. Therefore, the shop SH1 can be said to be a store related to the advertising content AD1.

Further, it is assumed that beacons are installed in each area and place from the home HP1 which is the home of the user U1 to the shop SH1. In the example of FIG. 1, the area AR1 including the home HP1, the area AR2 including the station ST1, the area AR3 including the facility BL, the area AR4 including the shop SH1, the entrance G of the shop SH1, and the predetermined sales area AR5 in the shop SH1. Beacons are installed on the product shelves M1, the product shelves M2, and the cash register M3 where they are placed.

In such a state, the information processing apparatus 100 first defines a stepwise action (funnel) (step S11). By installing beacons in various places as described above, the information processing device 100 appropriately acquires the behavior information indicating the user's behavior, which is the behavior information detected by the beacon, from the beacon and the behavior information storage unit 121. It can be stored in (Fig. 4). Therefore, the information processing device 100 performs machine learning based on the behavior information stored in the behavior information storage unit 121, and the behavior tendency obtained by machine learning (for example, deep learning) is used as one funnel. Define. More specifically, the information processing apparatus 100 extracts a series of related behavioral tendencies from the behavioral tendencies obtained by machine learning, and defines each of the extracted behavioral tendencies as one funnel.

Although an example in which the information processing device 100 defines the funnel by machine learning is shown here, the information processing device 100 may define the funnel by using an arbitrary method. Further, the funnel is not defined by the information processing apparatus 100, but may be hypothetically defined manually. In such a case, a funnel defined manually is input to the information processing apparatus 100.

In the example of FIG. 1, the information processing device 100 defines the following seven funnels as stepwise actions from the contact of the user U1 with the advertisement content AD1 to the purchase (conversion) of the product PD1. To do. Specifically, the information processing device 100 includes a funnel F1 showing a stepwise action such as "leaving the home HP1 and heading for the station ST1", a funnel F2 showing a stepwise action such as "waiting for a train at the station ST1", and " Funnel F3 showing gradual behavior such as "Come in front of facility BL", Funnel F4 showing gradual behavior such as "Come to shop SH1", and gradual behavior such as "Come in front of product shelf M1" It is assumed that the funnel F41, the funnel F42 indicating a stepwise action such as "come before the product shelf M2", and the funnel F43 indicating a stepwise action such as "come before the cash register M3" are defined.

Subsequently, the information processing apparatus 100 generates a prediction model for each funnel defined in step S11 (step S12). Previously, the information processing device 100 explained that the funnel is defined by machine learning, but the information processing device 100 can generate a prediction model by machine learning at this time. In the example of FIG. 1, the information processing apparatus 100 includes model M1 as a prediction model corresponding to funnel F1, model M2 corresponding to funnel F2, model M3 corresponding to funnel F3, model M4 corresponding to funnel F4, and funnel F41. The corresponding model M41, the prediction model M42 corresponding to the funnel F42, and the model M43 corresponding to the funnel F43 are generated, respectively.

Taking the model M1 corresponding to the funnel F1 as an example, when the position information indicating the current position of the user and the time information indicating the time when the user is present at the current position are input, the model M1 is "home" at this time. It is a model that outputs the probability that the user is performing an action such as "exiting HP1 and heading for station ST1". The information processing device 100 generates such a model by machine learning about the behavior information stored in the behavior information storage unit 121 and acquiring the behavior tendency. Therefore, the prediction model generated by the information processing apparatus 100 is a model that predicts the user's behavior at the position and the time based on the position and the time of the user.

In such a state, the information processing apparatus 100 acquires the position information indicating the current position of the user U1 and the time information indicating the time when the user U1 is at the current position (step S13). At this time, it is assumed that the user U1 is at the position PT1 beyond the home HP1. Further, in the example of FIG. 1, the position PT1 is included in the area AR1. Therefore, the beacon in the area AR1 detects the position information "PT1" of the user U1 and the time information at this time. Therefore, in such an example, the information processing apparatus 100 acquires the position information "PT1" and the time information at this time from the beacon in the area AR1. Hereinafter, the time information will be omitted.

Further, it is assumed that the user U1 has moved from the position PT1 to the position PT2 where the station ST1 is located. In such a case, the information processing apparatus 100 acquires the position information "PT2" from the beacon in the area AR2. Further, it is assumed that the user U1 has moved from the position PT2 to the position PT3 in front of the facility BL. In such a case, the information processing apparatus 100 acquires the position information "PT3" from the beacon in the area AR3. Further, it is assumed that the user U1 has moved from the position PT3 to the position PT4 at the entrance G of the shop SH1. In such a case, the information processing apparatus 100 acquires the position information "PT4" from the beacon in the area AR4.

After that, it is assumed that the user U1 enters the shop SH1 and reaches the sales area AR5. Further, it is assumed that the user U1 has come to the position PT41 in front of the product shelf M1. In such a case, the information processing device 100 acquires the position information "PT41" from the beacon installed on the product shelf M1. Further, it is assumed that the user U1 has come to the position PT42 in front of the product shelf M2. In such a case, the information processing device 100 acquires the position information "PT42" from the beacon installed on the product shelf M2. Further, it is assumed that the user U1 comes before the cash register M3. In such a case, the information processing apparatus 100 acquires the position information "PT43" from the beacon installed in the cash register M3.

Next, the information processing device 100 identifies the behavior of the user U1 based on the probability output by inputting the position information and the time information into the prediction model (step S14). For example, the information processing apparatus 100 inputs position information into each of the seven prediction models shown in FIG. 1, and if the highest probability among the output probabilities is a predetermined probability (for example, 80%) or more, the highest probability is obtained. The behavior of the user U1 is specified based on the funnel corresponding to the prediction model that outputs a high probability. For example, the information processing device 100 calculates seven probabilities by inputting the position information "PT1" into each of the seven prediction models. For example, the information processing apparatus 100 has a probability "90%" from the model M1, a probability "75%" from the model M2, a probability "50%" from the model M3, a probability "20%" from the model M4, and a probability "5" from the model M41. % ”, The probability“ 5% ”is calculated from the model M42, and the probability“ 5% ”is calculated from the model M43.

Then, in the information processing device 100, since the model M1 that outputs the probability "90%" (predetermined probability 80% or more) corresponds to the funnel F1, the user U1 leaves the home HP1 and the station ST1 at the position PT1. Identify that you were doing something like "towards". More specifically, since the user U1 is premised on contacting the advertisement content AD1, the information processing device 100 tells the user U1 to "exit the home HP1 (to cover the product PD1) at the station ST1" at the position PT1. Identify that you were doing something like "going". Although the time information has been omitted, in each prediction model, the shorter the time from the contact with the advertisement content AD1 to the arrival at the position PT1, the higher the probability is calculated. For example, if the user U1 is at the position PT1 5 minutes after contacting the advertisement content AD1, even if the probability "90%" is calculated from the model M1, 24 hours after the contact with the advertisement content AD1. When the user U1 is present at the position PT1, the probability "10%" may be calculated from the model M1.

By the way, in the above example, the information processing apparatus 100 shows an example in which the position information "PT1" is input to each of the seven prediction models, but other position information (position information PT2, PT3, PT4, PT41, PT42, PT43). ), The behavior of the user U1 is specified in the same manner. Then, the information processing device 100 determines the advertising effect based on the specified action (step S15).

Here, for example, if an action showing a probability of "80%" or more is specified from each prediction model (Pattern 1), the user U1 first purchases the product PD1 by contacting the advertisement content AD1. Leave your home HP1 and head for station ST1, then "wait for the train at station ST1", then "stop at facility BL", then "arrive in front of shop SH1", then "products in shop SH1" It can be identified that the stepwise action of "browsing the product on the shelf M1", then "browsing the product on the product shelf M2 in the shop SH1", and finally "purchasing the product on the cash register M3" was performed. For example, if the product PD1 is displayed on the product shelf M1 or M2, it can be confirmed that the user U1 has certainly purchased the product PD1.

In such a case, the information processing apparatus 100 determines that the user U1 purchases (converts) the product PD1 because of the contact with the advertising content AD1, for example, the advertising effect of the advertising content AD1 is "high". .. The information processing device 100 may express the advertising effect by a predetermined index value. Further, the information processing device 100 can determine that the user U1 takes the above-mentioned stepwise action due to the influence of the advertisement content AD1. Although only the user U1 is illustrated in FIG. 1, for example, when the same stepwise behavior is specified for other users, the information processing device 100 is affected by the advertisement content AD1 and the user is as described above. It can also be determined that they tend to take gradual actions. For example, the information processing device 100 may determine that it tends to drop in at the facility BL before purchasing the product PD1.

On the other hand, for example, it is assumed that the behaviors showing a probability of "80%" or more are identified from the models M1 and M2, but the behaviors cannot be identified because the other models calculate only a low probability of about 10% ( Pattern 2). In such a case, it can be predicted that the user U1 does not go to buy the product PD1 even if he / she comes into contact with the advertisement content AD1, but just heads for the station ST1. Therefore, in such a case, the information processing apparatus 100 determines that the advertising effect of the advertising content AD1 is "low".

Finally, the information processing device 100 notifies (feedback) the advertiser the advertising effect determined in step S15 (step S16). In the example of FIG. 1, the information processing device 100 notifies the advertiser of the advertising content AD1 of the advertising effect. For example, in the case of the above pattern 1, the information processing apparatus 100 notifies the advertising effect "high" and the tendency information indicating the tendency. As a result, the advertiser can devise an advertising strategy, for example, by placing a signboard advertisement near the facility BL, further advertising effect can be expected.

Further, for example, in the case of the above pattern 2, the information processing device 100 notifies that the user U1 has headed to the station ST1 together with the advertising effect "low". In this case, the advertiser can devise an advertising strategy that if the advertising content AD1 is posted at the station ST1, the product PD1 can be sent to the shop SH1 to buy it.

By the way, the first information processing according to the embodiment has been described so far. As described with reference to FIG. 1, the information processing apparatus 100 acquires position information indicating the position of the user, and based on the acquired position information, the user performs a stepwise action up to a predetermined action. Identify behavior. Then, the information processing device 100 determines the advertising effect based on the specified action.

As a result, the information processing device 100 can determine with high accuracy how much the advertising content has affected the user. Specifically, the information processing device 100 can determine with high accuracy how much the advertising content has influenced the user's offline behavior. In addition, the information processing device 100 interrupts the stepwise action when and where the user takes an action due to the contact with the advertisement content to finally reach the conversion, or even if the user comes into contact with the advertisement content. Since it is possible to determine whether or not to do so, it is possible to make the advertiser effectively develop the advertising force.

[2. Outline of the second information processing]
Next, with reference to FIG. 2, the outline of the second information processing among the information processing according to the embodiment is shown. FIG. 2 is a diagram showing an example of the second information processing according to the embodiment. The second information processing is also performed by the information processing device 100.

The second information processing will be described in detail later, but the position information acquired based on the characteristics of a predetermined space in the facility in a state where the position positioning of the user cannot be performed based on the external signal from outside the facility. Based on, the action taken by the user in the facility is specified.

Here, the premise that the second information processing is performed by the information processing apparatus 100 will be described. For example, for FMCG (Fast Moving Consumer Goods), an important theme in market-scale advertising is considered to be measuring advertising effectiveness. For example, an FMCG maker has one of the advertising effects of whether or not a user has come (touched) the product shelf on which the company's FMCG is placed in a physical store in a state where the advertisement content related to the company's FMCG is hit. It is defined as an index.

However, it may be difficult to accurately detect the user's behavior such as whether or not the user has come to the product shelf. For example, by using the position information acquired by the GPS function of the terminal device 10 (an example of an outpatient signal from outside the facility), it is possible to determine whether or not the user has visited the store where the target FMCG is sold. .. However, in the store (inside the facility), the GPS signal is blocked by the building, so there is a problem that the GPS function cannot be effectively used. Specifically, there is a problem that it becomes impossible to detect where the user is in the store. Then, it becomes difficult to identify the user's behavior in the store.

Therefore, a method of installing a beacon at a predetermined location in the store (for example, a common area such as a corridor, a product shelf, etc.) and acquiring the user's position information in the store based on the information acquired by the beacon is considered. Be done. However, since many beacons are required, there is a problem in the cost of installation. In addition, if many beacons are installed, the operation becomes difficult, and as a result, the operation of each beacon becomes complicated. Further, when the operation becomes complicated, it is naturally difficult to acquire highly accurate position information, and there is also a problem that the accuracy of the beacon itself is not high in the first place. For this reason, even if GPS does not function effectively in a store, a method using a beacon may not be realistic.

Based on such a premise, the second information processing utilizes geomagnetic positioning by geomagnetism instead of beacon. That is, based on the above assumptions, the information processing apparatus 100 according to the embodiment performs the second information processing shown in FIG. Specifically, the information processing device 100 is capable of positioning the user based on an external signal from outside the facility, and the position of the user in the facility is based on the characteristics of a predetermined space in the facility. Acquires the position information indicating. Then, the information processing device 100 identifies the action taken by the user in the facility based on the acquired position information.

Specifically, the information processing apparatus 100 acquires position information based on the magnetic characteristics distributed in the predetermined space as the characteristics of the predetermined space in the facility. More specifically, the information processing apparatus 100 is based on a change pattern in which the magnetism distributed in a predetermined space changes according to the presence of an object in the predetermined space, as a feature of magnetism distributed in the predetermined space. And get the location information.

Hereinafter, an example of the second information processing according to the embodiment will be described with reference to FIG. In addition, in FIG. 1, when acquiring the position information of the user of the area AR5 in the shop SH1 (an example of a facility), the information processing device 100 obtains the position information of the user detected by the beacon installed in the area AR5. An example of acquisition is shown. Therefore, in FIG. 2, similarly, the area AR5 in the shop SH1 will be described as an example. However, as explained in the premise, since there are various problems in utilizing the beacon, the information processing device 100 acquires the position information by using the geomagnetic positioning instead of the beacon, and the action of the user U1 based on this position information. To identify.

As shown in FIG. 2, in the area AR5, the aisle RD1 passes through in a mesh pattern, and along the aisle RD1, there is an area of a product shelf on which the products of each company (manufacturer) are displayed. In the example of FIG. 2, in the area AR5, the product shelves X1 on which the products of C1 are displayed are placed in the area AR51, and the products of C2 are placed in the areas AR52 and C3. Area AR53 where the product shelves X3 on which the products are displayed are placed, areas AR54 where the product shelves X4 where the products of C4 companies are displayed are placed, and areas AR55 and C6 where the product shelves X5 where the products of C5 companies are displayed are placed. There is an area AR56 where the product shelves X6 on which the products are displayed are placed.

Further, in the example of FIG. 2, the area AR5 also has an area in which the product shelves M1 and M2 described in FIG. 1 are placed and an area in which the cash register M3 is placed.

In such a state, a predetermined investigator (for example, an employee of a management company that manages the information processing apparatus 100) first investigates the state of the geomagnetism in the area AR5 and obtains magnetic data. (Step S21). For example, by walking around the passage RD1 using an investigator and a predetermined measuring instrument, the state of the geomagnetism in the passage RD1 is investigated and magnetic data is obtained.

Next, the investigator creates a magnetic map based on the magnetic data (step S22). As shown in FIG. 2, the magnetic map is shown as a heat map according to the intensity of the geomagnetism. In the example of FIG. 2, the investigator creates the magnetic map MA1 corresponding to the passage RD1. In addition, such a magnetic map may be created by the information processing apparatus 100. In such a case, the information processing apparatus 100 creates the magnetic map MA1 by analyzing the magnetic data obtained in step S21. Further, the information processing apparatus 100 stores the created magnetic map MA1 in the magnetic information storage unit 123.

The magnetic pattern of the geomagnetism changes indoors under the influence of structures forming buildings and objects placed indoors. Therefore, it can be said that the magnetic pattern in the area AR5 is a pattern peculiar to the area AR5. Therefore, the magnetic pattern in the area AR5 can be understood as an example of a spatial feature such as the area AR5, more specifically, a magnetic feature distributed in the area AR5.

Then, it is assumed that the user U1 walks around in the area AR5. The terminal device 10 has a geomagnetic sensor, and the geomagnetic sensor acquires the geomagnetism around the user U1 as the user U1 walks around (step S23). For example, the geomagnetic sensor acquires the geomagnetism of the user U1 at the current location each time the user U1 moves. In other words, the geomagnetic sensor measures or detects the geomagnetism around the user U1. Further, the terminal device 10 transmits the measurement result data indicating the magnetism acquired by the geomagnetic sensor to the information processing device 100 (step S24).

The information processing device 100 calculates a change pattern in which the geomagnetism changes in the area AR5 based on the measurement result data acquired from the terminal device 10, that is, the geomagnetism (intensity) that changes according to the movement of the user U1 (step S25). ). Then, the information processing apparatus 100 acquires the position information indicating the current location of the user U1 based on the calculated change pattern (step S26). For example, the information processing apparatus 100 identifies a time-series change in the geomagnetism by matching the change pattern with the magnetic map MA1. Then, the information processing apparatus 100 acquires (identifies) the position information of the user U1 by estimating the transition route of the user U1 based on the specified time-series change.

Next, the information processing apparatus 100 identifies the action performed by the user U1 in the area AR5 based on the position information of the user U1 acquired in step S26 (step S27). In such an example, it is assumed that the information processing apparatus 100 has specified that the user U1 has performed an action such as coming in front of the product shelf X2 and then coming in front of the product shelf X1. More specifically, it is assumed that the information processing apparatus 100 has specified that the user U1 has performed an action such as browsing the product on the product shelf X1 after browsing the product on the product shelf X2.

Here, it is assumed that the user U1 is in contact with the advertising content of the advertiser C1 company (for example, browsing the advertising content of the C1 company on the terminal device 10) before coming to the shop SH1. Further, it is assumed that Company C1 requests the information processing device 100 (or the business owner who manages the information processing device 100) to measure the advertising effectiveness of its own advertising content. Alternatively, it is assumed that Company C1 has submitted its own advertising content to the information processing device 100 (or the business owner who manages the information processing device 100).

In such a case, the information processing apparatus 100 determines whether or not the user U1 has performed a predetermined action based on the action specified in step S27 (step S28). Specifically, the information processing apparatus 100 determines whether or not the user U1 has come in front of the product shelf X1. According to the above example, the information processing apparatus 100 determines that the user U1 has come in front of the product shelf X1. The user U1 is in contact with the advertising content of the C1 company by the time the product of the C1 company is placed on the product shelf X1. Therefore, it is highly possible that the user U1 has come to the product shelf X1 on which the product of the C1 company is placed due to the influence of the contact with the advertising content of the company C1.

For this reason, the information processing apparatus 100 determines that the advertising effect of the advertising content of the C1 company is "high", and feeds back the determination result to the C1 company.

So far, the second information processing according to the embodiment has been described. As described with reference to FIG. 2, the information processing device 100 is said to be inside the facility based on the characteristics of a predetermined space in the facility in a state where the user cannot be positioned based on an external signal from outside the facility. Acquires position information indicating the user's position. Then, the information processing device 100 identifies the action taken by the user in the facility based on the acquired position information. As a result, the information processing device 100 can identify the action taken by the user with high accuracy in a situation where the positioning of the user cannot be performed.

Further, since the information processing device 100 can determine the advertising effect based on the user's behavior, the advertising effect can be fed back to the advertiser to help the advertiser in the advertising strategy.

[3. Information processing device configuration]
Next, the information processing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram showing a configuration example of the information processing apparatus 100 according to the embodiment. As shown in FIG. 3, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

(About communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. Then, the communication unit 110 is connected to the network N by wire or wirelessly, and transmits / receives information to / from, for example, the terminal device 10.

(About storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 120 includes a behavior information storage unit 121, a model information storage unit 122, and a magnetic information storage unit 123.

(About the behavior information storage unit 121)
The behavior information storage unit 121 stores behavior information indicating the behavior of the user. For example, the behavior information storage unit 121 stores the behavior information detected by the beacon. Here, FIG. 4 shows an example of the behavior information storage unit 121 according to the embodiment. In the example of FIG. 4, the action information storage unit 121 has items such as "user ID", "area", and "behavior information".

The "user ID" indicates identification information that identifies the user or the user's terminal device 10. "Area" indicates an area where an object (building part) or the like on which a beacon is installed exists. In the example of FIG. 4, a conceptual symbol such as "PDA11" is used as information indicating the area, but the area is indicated by an address such as latitude and longitude or XX to XX chome. The "behavior information" is the behavior information detected by the beacon and indicates the behavior information indicating the behavior of the user. In the example of FIG. 4, a conceptual symbol such as "ADA11" is used as the action information, but the action information has a time and a position such as "July 21, 2017, 15:00, A station". Indicated by identifiable text.

That is, in the example of FIG. 4, the user (user U11) identified by the user ID "U11" is performing the action indicated by the action information "ADA11" by the beacon existing in the position area indicated by "PDA11". Show that.

(About model information storage unit 122)
The model information storage unit 122 stores the prediction model (prediction model generated by the information processing device 100) described with reference to FIG. Here, FIG. 5 shows an example of the model information storage unit 122 according to the embodiment. In the example of FIG. 5, the model information storage unit 122 has items such as “funnel”, “model ID”, and “model”.

A "funnel" indicates a step-by-step action. For example, a "funnel" indicates a step-by-step action from ad creative submission to conversion. The "model ID" indicates identification information that identifies the prediction model. “Model” indicates a prediction model generated by the information processing apparatus 100. Further, the "model" indicates a model in which the position information and the time information are input and the probability that the user is performing the corresponding "funnel" at the position indicated by the position information is output. Further, in the example of FIG. 5, a conceptual symbol such as "MDA1" is used as the "model", but the "model" is actually represented by a mathematical formula.

That is, in the example of FIG. 5, when the position information indicating the current position of the user and the time information indicating the time when the user is present at the current position are input, the user performs an action such as "leaving home" at this time. An example is shown in which a model M1 that outputs the probability performed by is generated.

(About magnetic information storage unit 123)
The magnetic information storage unit 123 stores a magnetic map generated from the geomagnetism of a predetermined area in the facility. As shown in FIG. 2, in the present embodiment, the facility is a predetermined store. Here, FIG. 6 shows an example of the magnetic information storage unit 123 according to the embodiment. In the example of FIG. 6, the magnetic information storage unit 123 has items such as “store ID”, “area”, and “magnetic map data”.

The "store ID" indicates identification information that identifies the store. “Area” indicates an area in the store identified by the “store ID”. "Magnetic map data" indicates magnetic map data indicating the state (intensity) of the geomagnetism of the corresponding area.

That is, the example of FIG. 6 shows an example in which the magnetic map MA1 is generated based on the geomagnetism in the “area AR5” which is the area in the store identified by the store ID “SH1”.

(About other storage parts)
Further, although not shown, the information processing apparatus 100 may further have the following storage units. For example, the information processing device 100 has a storage unit that stores advertisement contents submitted by an advertiser, and a storage unit that stores which manufacturer's products are placed on which product shelves in which area of the store. May have.

(About control unit 130)
Returning to FIG. 3, in the control unit 130, various programs stored in the storage device inside the information processing device 100 are executed by the CPU (Central Processing Unit), the MPU (Micro Processing Unit), etc. using the RAM as the work area. It is realized by. Further, the control unit 130 is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 3, the control unit 130 includes a model generation unit 131, a first acquisition unit 132, a first specific unit 133, an effect determination unit 134, a second acquisition unit 135, and a second specific unit 136. It has an action determination unit 137 and a notification unit 138, and realizes or executes an information processing function or action described below. The internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 3, and may be another configuration as long as it is a configuration for performing information processing described later. Further, the connection relationship of each processing unit included in the control unit 130 is not limited to the connection relationship shown in FIG. 3, and may be another connection relationship.

(About model generator 131)
The model generation unit 131 generates a prediction model. Specifically, the model generation unit 131 inputs the user's position information and time information, and the user performs a corresponding funnel (stepwise action, action at each stage) at the position indicated by the position information. Generate a model that outputs the probability of being present. That is, the model generation unit 131 generates a prediction model that predicts which action to perform among the stepwise actions. For example, the model generation unit 131 first defines a funnel, and for each defined funnel, generates a prediction model that outputs the probability that the user will perform the action indicated by the funnel.

In the example of FIG. 1, the model generation unit 131 performs machine learning based on the behavior information stored in the behavior information storage unit 121, and the behavior tendency obtained by machine learning (for example, deep learning) is used as one funnel. Define. More specifically, the model generation unit 131 extracts a series of related behavioral tendencies from the behavioral tendencies obtained by machine learning, and defines each of the extracted behavioral tendencies as one funnel. In addition, the model generation unit 131 generates a prediction model for each funnel by machine learning that defines the funnel.

For example, the model generation unit 131 machine-learns about the behavior information stored in the behavior information storage unit 121 and acquires the behavior tendency. Then, when the position information indicating the current position of the user and the time information indicating the time when the user is present at the current position are input, the model generation unit 131 "leaves the home HP1 and heads for the station ST1" at this time. A model M1 that outputs the probability that the user is performing an action such as (FIG. 1, funnel F1) is generated.

The model generation unit 131 outputs a prediction model that outputs what kind of stepwise action is being performed and with what probability when position information and time information are input, that is, a stepwise action and its action. You may generate a prediction model that outputs the probability. Further, the model generation unit 131 may generate a prediction model for each user. For example, the model generation unit 131 may generate a prediction model for each user.

(About the first acquisition unit 132)
The first acquisition unit 132 acquires position information indicating the position of the user. For example, the first acquisition unit 132 acquires the position information indicating the current position of the user as the position information. In addition, the first acquisition unit 132 acquires time information indicating the time when the user is at the position indicated by the position information. For example, the first acquisition unit 132 acquires position information and time information based on detection information which is information detected by a sensor installed at a predetermined position.

In the example of FIG. 1, beacons as anchors are installed in various places. Therefore, the first acquisition unit 132 appropriately acquires the action information and the time information detected by the beacon from the beacon. In addition, the first acquisition unit 132 stores the acquired action information and time information in the action information storage unit 121.

(About the first specific part 133)
Based on the position information and the time information acquired by the first acquisition unit 132, the first specific unit 133 identifies an action performed by the user among the stepwise actions leading up to a predetermined action. For example, in the first specific unit 133, as a stepwise action leading up to a predetermined action, among the stepwise actions from the user contacting the predetermined advertising content to the conversion related to the advertising content. , Identify the action the user takes.

For example, the first specific unit 133 is a probability output by inputting position information and time information to a prediction model generated based on a stepwise action leading up to a predetermined action, and is a predetermined probability. Based on the probability that the user performs a stepwise action leading up to an action, the action performed by the user is specified among the stepwise actions leading up to a predetermined action. Specifically, the first specific unit 133 is a probability output by inputting position information and time information to a model generated for each stepwise action up to a predetermined action as a prediction model. Then, based on the probability that the user performs the stepwise action, the action performed by the user is specified among the stepwise actions leading up to the predetermined action.

In the example of FIG. 1, the first specific unit 133 inputs position information into each of the seven prediction models shown in FIG. 1, and the highest probability among the output probabilities is a predetermined probability (for example, 80%) or more. If there is, the behavior of the user U1 is specified based on the funnel corresponding to the prediction model that outputs the highest probability.

In addition, the first specific unit 133, as a stepwise action leading to a predetermined action, from the time when the user comes into contact with the predetermined advertisement content until the information related to the advertisement content is transmitted by any means. Of the stepwise actions of, the action performed by the user may be specified. The arbitrary means is, for example, an SNS (Social Networking Service).

(About effect judgment unit 134)
The effect determination unit 134 determines the advertising effect based on the action specified by the first specific unit 133. For example, the effect determination unit 134 determines the relationship between the action specified by the first specific unit 133 and the advertisement content that the user has contacted as an advertisement effect. In addition, the effect determination unit 134 determines the influence of the advertising content that the user has contacted on the action specified by the first specific unit 133 as an advertising effect.

For example, the effect determination unit 134 performs the action determined by the first specific unit 133 because the user has contacted the advertisement content as described in FIG. 1 as a relationship between the action specified by the first specific unit 133 and the advertisement content that the user has contacted. Judge (identify) the action taken by the user regardless of the action taken or the contact with the advertising content.

(About the second acquisition unit 135)
The second acquisition unit 135 is based on the characteristics of a predetermined space in the facility in a state where the positioning of the user in the facility cannot be performed based on an outpatient signal from outside the facility. Acquire position information indicating the position. Specifically, the second acquisition unit 135 acquires position information based on the characteristics of the geomagnetism distributed in the predetermined space as the characteristics of the predetermined space in the facility. For example, the second acquisition unit 135 is based on a change pattern in which the geomagnetism distributed in the predetermined space changes according to the presence of an object in the predetermined space as a feature of the magnetism distributed in the predetermined space. Get location information.

In the example of FIG. 2, the second acquisition unit 135 changes the geomagnetism in the area AR5 based on the measurement result data acquired from the terminal device 10, that is, the geomagnetism (intensity) that changes according to the movement of the user U1. Calculate the pattern. Then, the second acquisition unit 135 acquires the position information indicating the current location of the user U1 based on the calculated change pattern. For example, the second acquisition unit 135 identifies the time-series change of the geomagnetism by matching the change pattern with the magnetic map MA1. Then, the second acquisition unit 135 acquires (identifies) the position information of the user U1 by estimating the transition route of the user U1 based on the specified time-series change.

(About the second specific part 136)
The second specific unit 136 identifies the action taken by the user in the facility based on the position information acquired by the second acquisition unit 135. In the example of FIG. 2, the second specific unit 136 identifies the action performed by the user U1 in the area AR5 based on the position information of the user U1 acquired by the second acquisition unit 135.

(About behavior judgment unit 137)
The action determination unit 137 determines whether or not the user has performed a predetermined action in the facility based on the action specified by the second specific unit 136. For example, the action determination unit 137 determines whether or not the user has visited an area in which a transaction target (for example, a product) is provided in a predetermined space as a predetermined action. Further, for example, the action determination unit 137 determines, as a predetermined action, whether or not the user has visited a display shelf (for example, a product shelf) on which a transaction target is displayed in a predetermined space.

In the example of FIG. 2, the information processing device 100 accepts the submission of the advertisement content from the company C1 to determine whether or not the user U1 has come in front of the product shelf X1 on which the products of the company C1 are displayed. To do.

(About notification unit 138)
The notification unit 138 notifies (feeds back) the advertising effect determined by the effect determination unit 134 to the advertiser. In addition, the notification unit 138 notifies (feeds back) the determination result determined by the effect determination unit 134 and the advertising effect based on the determination result.

[4. Processing procedure (1)]
Hereinafter, the contents of the control processing executed and realized by each processing unit of the information processing apparatus 100 according to the embodiment will be described with reference to the flowchart shown in FIG. FIG. 7 is a flowchart showing an example of the first information processing according to the embodiment. Since the first information processing has already been described with reference to FIG. 1, the example of FIG. 1 will be used as appropriate.

First, the model generation unit 131 determines whether or not it is the timing to generate the prediction model (step S101). For example, the model generation unit 131 determines whether or not sufficient information is stored in the behavior information storage unit 121, and if it is stored (step S101; Yes), it is the timing to generate the prediction model. Is determined, and the funnel is defined as described in FIG. 1 (step S102). On the other hand, when the behavior information storage unit 121 does not accumulate sufficient information (step S101; No), the model generation unit 131 determines that it is not the timing to generate the prediction model, and determines that it is not the timing to generate the prediction model. Wait until it becomes. Further, the model generation unit 131 generates a prediction model for each funnel defined in step S102 (step S103).

Next, the first acquisition unit 132 acquires the position information indicating the (current) position of the user and the time information indicating the time at such a position (step S104). For example, the first acquisition unit 132 acquires the position information and the time information detected by the beacons in each place from the beacons.

Next, the first specific unit 133 is the probability output by inputting the position information and the time information to the prediction model generated by the model generation unit 131, and reaches a predetermined action. Based on the probability that the user performs a stepwise action, among the stepwise actions leading up to a predetermined action, the action performed by the user is specified (step S105). Then, the effect determination unit 134 determines the advertising effect based on the action specified by the first specific unit 133 (step S106). Then, the notification unit 138 notifies the advertiser of the determined advertising effect (step S107).

The model generation unit 131 performs reinforcement learning by further applying not only the behavior information stored in the behavior information storage unit 121 but also the behavior information indicating the behavior specified by the first specific unit 133. Can generate funnel definitions and prediction models. As a result, the model generation unit 131 can generate a more accurate prediction model.

[5. Processing procedure (2)]
Hereinafter, the contents of the control processing executed and realized by each processing unit of the information processing apparatus 100 according to the embodiment will be described with reference to the flowchart shown in FIG. FIG. 8 is a flowchart showing an example of the second information processing according to the embodiment. Since the second information processing has already been described with reference to FIG. 2, the example of FIG. 2 will be used as appropriate. In the example of FIG. 8, it is assumed that the information processing device 100 already has the magnetic map data in the magnetic information storage unit 123.

First, the second acquisition unit 135 determines whether or not the measurement result data (magnetic data) indicating the intensity of the geomagnetism measured by the terminal device 10 of the user U1 can be acquired from the terminal device 10 in the area AR5 (step). S201). Next, the second acquisition unit 135 calculates a change pattern in which the geomagnetism changes in the area AR5 based on the measurement result data (step S202). Next, the second acquisition unit 135 acquires the position information of the user U1 by matching the change pattern with the magnetic map (step S203). For example, the second acquisition unit 135 acquires the position information of the user U1 by specifying the geomagnetic time-series change by matching and estimating the transition route of the user U1 based on the specified time-series change.

Next, the second specific unit 136 identifies the action performed by the user in the area AR5 based on the position information acquired by the second acquisition unit 135 (step S204). Then, the action determination unit 137 determines whether or not the user has performed a predetermined action in the area AR5 based on the action specified by the second specific unit 136 (step S205). Then, the notification unit 138 notifies the advertiser of the action determined by the action determination unit 137 (step S206).

[6. Modification example]
The information processing apparatus 100 according to the above embodiment may be implemented in various different forms other than the above embodiment. Therefore, another embodiment of the information processing apparatus 100 will be described below.

[6-1. Attribute information〕
In the above embodiment, the first specific unit 133 specifies an action performed by the user among the stepwise actions leading up to a predetermined action based on the position information and the time information acquired by the first acquisition unit 132. An example is shown. However, the first specific unit 133 may specify an action according to the predetermined attribute information as an action to be performed by the user among the stepwise actions leading to the predetermined action. Such predetermined attribute information includes, for example, the attribute information of the user itself (for example, age, gender, etc.), the attribute information of the advertising content that the user has contacted, the transaction target indicated by the advertising content that the user has contacted (for example, a product or service, etc.). ) Attribute information. Of course, the predetermined attribute information is not limited to these.

In such a case, the model generation unit 131 is a stepwise action up to a predetermined action when not only the position information and the time information but also the above-mentioned attribute information is input, and the input position. A prediction model that outputs the probability that the user will perform a stepwise action according to information, time information, and attribute information will be generated.

As a result, the information processing device 100 according to the embodiment can determine with higher accuracy how much the advertising content has affected the user. Further, the information processing device 100 can identify a tendency according to an attribute, for example, when a user of the attribute information "male" comes into contact with an advertisement content of a certain attribute, he / she stops at a certain facility and then heads for the shop SH1. Therefore, it is possible to force the advertiser to carry out a more advanced advertising strategy.

[6-2. Advertising contact]
In addition, the first specific unit 133 refers to the advertising content that the user comes into contact with in the stepwise action leading up to the predetermined action as the action performed by the user among the stepwise actions leading up to the predetermined action. Identify the corresponding behavior.

In the example of FIG. 1, the user U1 first contacts the advertisement content AD1 on the terminal device 10, but corresponds to the advertisement content AD1 on the route until reaching the shop SH1 or on the train (for example). Further contact with (related) physical advertising (eg, signboards, etc.) may occur. Whether or not a person has come into contact with such a physical advertisement can be obtained, for example, by a beacon. Then, because the user first contacts the advertising content AD1 and then contacts the advertising content related to the advertising content AD1, the user goes to the target shop and leads to conversion, or by then, to a specific facility. There may be a tendency to stop by. The first specific unit 133 identifies an action in response to contact with the advertising content at such a plurality of stages. In such a case, the model generation unit 131 generates a prediction model corresponding to the physical advertisement.

As a result, the information processing device 100 according to the embodiment can give the advertiser, for example, a material for determining in what place in the city it is preferable to put out a signboard advertisement or the like.

[6-3. Position acquisition with sound waves (1)]
In the above embodiment, the second acquisition unit 135 is based on a change pattern in which the geomagnetism distributed in a predetermined space changes according to the presence of an object in the predetermined space as a feature of the magnetism distributed in the predetermined space. An example of acquiring location information is shown. However, the second acquisition unit 135 may acquire position information based on the inaudible sounds distributed in the predetermined space as a feature of the predetermined space in the facility. Specifically, the second acquisition unit 135 is positioned based on the grid corresponding to the frequency detected by the user's terminal device 10 among the grids generated by the inaudible sounds of different frequencies in a predetermined space. Get information. This point will be described with reference to the example of FIG.

For example, a plurality of speakers (for example, directional speakers) that output inaudible sounds (for example, 20 kHz band) are installed in the area AR5. Such speakers output inaudible sounds having different wavelengths (frequency), and are installed along the wall of the area AR5 or the like so as to go around the area AR5, for example. When each speaker outputs an inaudible sound in such a state, a grid with different inaudible sounds is generated in the area AR5. Therefore, in the area AR5, a plurality of points where inaudible sounds having different wavelengths intersect will occur. At this point, sound wave interference occurs, resulting in the generation of inherent inaudible sounds. Then, it is assumed that the information processing device 100 has information in advance indicating at which position in the area AR5 the unique inaudible sound is generated.

Since the microphone built in the terminal device 10 of the user U1 can collect the inaudible sound, the voice data indicating the collected inaudible sound is transmitted to the information processing device 100. Here, the second acquisition unit 135 analyzes the voice data received from the terminal device 10, and for example, when the voice data indicates a unique inaudible sound, the position where the unique inaudible sound is generated is determined. Acquired as the position of user U1.

Thereby, the information processing device 100 according to the embodiment can identify the action performed by the user in the facility with high accuracy even in a situation where the geomagnetic positioning cannot be performed in the facility, for example.

[6-4. Position acquisition with sound waves (2)]
Further, the second acquisition unit 135 acquires position information based on the timing when the terminal device of the user detects the inaudible sound output while the output device installed in the predetermined space operates periodically. This point will be described with reference to the example of FIG.

For example, one speaker (for example, a directional speaker) for outputting an inaudible sound (for example, 20 kHz band) is installed at both ends (both corners) of the area AR5. These speakers are set to act automatically and periodically. For example, the speaker portion is set to swing its head at a constant speed. As an example, one speaker faces east at "14:00:00", swings counterclockwise as time passes, and faces north at "14:00:02". , And so on. In addition, the other speaker turns north at "14:00:00", swings counterclockwise as time passes, and turns west at "14:00:00". It is a thing.

Then, the microphone of the terminal device 10 of the user U1 collects the inaudible sounds output from the two speakers that move in a fixed manner as described above, and collects the collected inaudible sounds and when the sounds are collected. The voice data indicating the time information is transmitted to the information processing device 100. Assuming that the information processing device 100 can know when and in which direction the two speakers are facing, the second acquisition unit 135 can obtain time information based on the time information received from the terminal device 10. It is possible to identify in which direction each speaker was outputting inaudible sound at the indicated time. Therefore, the second acquisition unit 135 can acquire the position of the intersection formed in the area AR5 as the position of the user U1, which is the intersection of the directions corresponding to each speaker.

Further, for example, when there is one speaker, the second acquisition unit 135 cannot specify the intersection, but presumes that the user U1 is on the extension line of the direction corresponding to the one speaker. be able to. Then, since the second acquisition unit 135 can estimate where on the extension line the inaudible sound is collected based on the volume indicated by the voice data, the estimated position is acquired as the position of the user U1. can do.

Thereby, the information processing device 100 according to the embodiment can identify the action performed by the user in the facility with high accuracy even in a situation where the geomagnetic positioning cannot be performed in the facility, for example.

[6-5. Position acquisition with light (1)]
In addition, the second acquisition unit 135 acquires position information based on the invisible light distributed in the predetermined space as a feature of the predetermined space in the facility. Specifically, the second acquisition unit 135 provides position information based on the grid corresponding to the wavelength detected by the user's terminal device 10 among the grids generated by invisible light having different wavelengths in a predetermined space. To get. This is an invisible light version of the example described in "Modification 6-3" above.

For example, in the area AR5, a plurality of output devices (light sources) for outputting invisible light (for example, infrared rays or ultraviolet rays) are installed. Such output devices output invisible light having different wavelengths, and are installed along the wall of the area AR5 or the like so as to make one round of the area AR5, for example. When each output device outputs invisible light in such a state, a grid of invisible light having different wavelengths is generated in the area AR5. Therefore, in the area AR5, a plurality of intersections where invisible light of different wavelengths intersect will occur. At this intersection, light interference occurs, resulting in the generation of invisible light of a unique wavelength. Then, it is assumed that the information processing apparatus 100 has information in advance indicating at which position in the area AR5 the unique invisible light is generated.

Since the sensor built in the terminal device 10 of the user U1 can detect the invisible light, the optical data indicating the detected invisible light is transmitted to the information processing device 100. Here, the second acquisition unit 135 analyzes the optical data received from the terminal device 10, and for example, when the optical data shows invisible light having a unique wavelength, invisible light having the unique wavelength is generated. The position is acquired as the position of the user U1.

Thereby, the information processing device 100 according to the embodiment can identify the action performed by the user in the facility with high accuracy even in a situation where the geomagnetic positioning cannot be performed in the facility, for example.

[6-6. Position acquisition with light (2)]
Further, the second acquisition unit 135 acquires position information based on the timing at which the user's terminal device 10 detects invisible light output while the output device installed in a predetermined space operates periodically. This is an invisible light version of the example described in "Modifications 6-4" above.

For example, one output device that outputs invisible light (for example, infrared rays or ultraviolet rays) is installed at both ends (both corners) of the area AR5. These output devices are set to automatically and cyclically behave. For example, the output part is set to swing its head at a constant speed. As an example, one output device faces east at "14:00:00", swings counterclockwise as time passes, and turns north at "14:00:02". It is suitable. The other output device faces north at "14:00:00", swings counterclockwise according to the passage of time, and faces west at "14:00:02". And so on.

Then, the sensor of the terminal device 10 of the user U1 detects the invisible light output from the two output devices having the predetermined movements as described above, and the detected invisible light and the time information at the time of detection. The optical data indicating the above is transmitted to the information processing apparatus 100. Assuming that the information processing device 100 can know when and in which direction the two output devices are facing, the second acquisition unit 135 will perform time information based on the time information received from the terminal device 10. It is possible to specify in which direction each output device was outputting invisible light at the time indicated by. Therefore, the second acquisition unit 135 can acquire the position of the intersection formed in the area AR5 as the position of the user U1, which is the intersection of the directions corresponding to each output device.

Further, for example, when there is one output device, the second acquisition unit 135 cannot specify the intersection, but if the user U1 is on an extension of the direction corresponding to the one output device, You can guess. Then, the second acquisition unit 135 can estimate where invisible light is detected on the extension line based on the intensity indicated by the optical data, so that the estimated position is acquired as the position of the user U1. Can be done.

Thereby, the information processing device 100 according to the embodiment can identify the action performed by the user in the facility with high accuracy even in a situation where the geomagnetic positioning cannot be performed in the facility, for example.

[7. Hardware configuration]
Further, the information processing apparatus 100 according to each of the above-described embodiments is realized by, for example, a computer 1000 having a configuration as shown in FIG. Hereinafter, the information processing device 100 will be described as an example. FIG. 9 is a hardware configuration diagram showing an example of a computer 1000 that realizes the functions of the information processing device 100. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400, and controls each part. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started, a program that depends on the hardware of the computer 1000, and the like.

The HDD 1400 stores a program executed by the CPU 1100, data used by such a program, and the like. The communication interface 1500 receives data from another device via the communication network 50 and sends it to the CPU 1100, and transmits the data generated by the CPU 1100 to the other device via the communication network 50.

The CPU 1100 controls an output device such as a display or a printer, and an input device such as a keyboard or a mouse via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. Further, the CPU 1100 outputs the generated data to the output device via the input / output interface 1600.

The media interface 1700 reads a program or data stored in the recording medium 1800 and provides the program or data to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable Disk), a magneto-optical recording medium such as MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. And so on.

For example, when the computer 1000 functions as the information processing device 100 according to the embodiment, the CPU 1100 of the computer 1000 realizes the function of the control unit 130 by executing the program loaded on the RAM 1200. Further, the data in the storage unit 120 is stored in the HDD 1400. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, these programs may be acquired from another device via the communication network 50.

[8. Others]
Of the processes described in each of the above embodiments, all or part of the processes described as being automatically performed can be performed manually, or all the processes described as being performed manually. Alternatively, a part can be automatically performed by a known method. In addition, the processing procedure, specific name, and information including various data and parameters shown in the above document and drawings can be arbitrarily changed unless otherwise specified.

Further, each component of each of the illustrated devices is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of them may be functionally or physically distributed / physically in arbitrary units according to various loads and usage conditions. It can be integrated and configured.

In addition, the above-described embodiments can be appropriately combined as long as the processing contents do not contradict each other.

The embodiments of the present application have been described in detail with reference to some drawings, but these are examples, and various modifications are made based on the knowledge of those skilled in the art, including the embodiments described in the disclosure column of the invention. It is possible to practice the present invention in other improved forms.

Further, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the acquisition unit can be read as an acquisition means or an acquisition circuit.

10 Terminal device 100 Information processing device 121 Behavior information storage unit 122 Model information storage unit 123 Magnetic information storage unit 131 Model generation unit 132 First acquisition unit 133 First specific unit 134 Effect judgment unit 135 Second acquisition unit 136 Second specific unit 137 Action Judgment Department 138 Notification Department

Claims (14)

With an acquisition unit that acquires position information indicating the position of the user in the facility based on the characteristics of a predetermined space in the facility in a state where the position of the user cannot be positioned based on an outpatient signal from outside the facility. ,
Users in contact to a Jo Tokoro of advertising content, after contact with the advertisement content, of stepwise action went until performing a predetermined action associated with the advertisement content in the facility, the advertisement content The first specific part that identifies the action to be performed this time by the user to be processed in contact with
Based on the position information acquired by the acquisition unit, the second specific unit that specifies the action performed by the user in the facility, and
The influence determined based on the behavioral tendency obtained from the behavior specified for each user to be processed by the first specific unit, and the influence of the advertising content on the stepwise behavior is the advertising content. When it is determined that the user has performed the predetermined action based on the action specified by the second specific unit while notifying the submission source of the advertisement content as the advertising effect of the above, the user Information processing characterized by having a notification unit that notifies the submission source of the advertisement content of information indicating the advertisement effect of the advertisement content, which is an advertisement effect determined based on the predetermined action. apparatus. The acquisition unit, a characteristic of a given space in the facility, based on the geomagnetism features distributed in the predetermined space, the information processing according to claim 1, characterized in that acquires the position information apparatus. The acquisition unit is characterized by the magnetism distributed in the predetermined space, based on a change pattern in which the geomagnetism distributed in the predetermined space changes according to the presence of an object in the predetermined space. The information processing apparatus according to claim 1 or 2 , wherein the information processing apparatus is characterized by acquiring information. Any one of claims 1 to 3 , wherein the acquisition unit acquires the position information based on the inaudible sound distributed in the predetermined space as a feature of the predetermined space in the facility. The information processing device according to one. The acquisition unit is based on a grid corresponding to a frequency detected by the user's terminal device among the grids generated by the non-audible sounds having different frequencies in a predetermined space. The information processing apparatus according to claim 4 , wherein the information processing apparatus is characterized by acquiring position information. The acquisition unit acquires the position information based on the timing when the terminal device of the user detects the inaudible sound output by the output device installed in the predetermined space while operating periodically. The information processing apparatus according to claim 4 or 5 . Any one of claims 1 to 6 , wherein the acquisition unit acquires the position information based on the invisible light distributed in the predetermined space as a feature of the predetermined space in the facility. The information processing device described in 1. The acquisition unit receives the position information based on the grid corresponding to the wavelength detected by the terminal device of the user among the grids generated by the invisible light having different wavelengths in a predetermined space. The information processing apparatus according to claim 7 , wherein the information processing apparatus is obtained. The acquisition unit is characterized in that the position information is acquired based on the timing when the terminal device of the user detects the invisible light output while the output device installed in the predetermined space operates periodically. The information processing device according to claim 7 or 8 . Any of claims 1 to 9 , further comprising a determination unit for determining whether or not the user has performed a predetermined action in the facility based on the action performed by the user in the facility. The information processing device according to one. The information according to claim 10 , wherein the determination unit determines, as the predetermined action, whether or not the user has visited an area where the transaction target is provided in the predetermined space. Processing equipment. According to claim 10 or 11 , the determination unit determines, as the predetermined action, whether or not the user has visited a display shelf on which a transaction target is displayed in the predetermined space. The information processing device described. It is an information processing method executed by an information processing device.
An acquisition step of acquiring position information indicating the position of the user in the facility based on the characteristics of a predetermined space in the facility in a state where the position of the user cannot be positioned based on an outpatient signal from outside the facility. ,
Users in contact to a Jo Tokoro of advertising content, after contact with the advertisement content, of stepwise action went until performing a predetermined action associated with the advertisement content in the facility, the advertisement content The first specific step to specify the action to be performed this time by the user to be processed in contact with
Based on the position information acquired by the acquisition step, the second specific step of specifying the action performed by the user in the facility, and
The influence determined based on the behavioral tendency obtained from the behavior specified for each user to be processed by the first specific step, and the influence of the advertising content on the stepwise behavior is the advertising content. When it is determined that the user has performed the predetermined action based on the action specified by the second specific step while notifying the submission source of the advertisement content as the advertising effect of the above, the user An information processing method including a notification step of notifying an advertising source of the advertising content of information indicating the advertising effect of the advertising content, which is an advertising effect determined based on the predetermined action. .. An acquisition procedure for acquiring position information indicating the position of the user in the facility based on the characteristics of a predetermined space in the facility in a state where the position of the user cannot be positioned based on an outpatient signal from outside the facility. ,
Users in contact to a Jo Tokoro of advertising content, after contact with the advertisement content, of stepwise action went until performing a predetermined action associated with the advertisement content in the facility, the advertisement content The first specific procedure to identify the action to be performed this time by the processing target user who came into contact with
Based on the position information acquired by the acquisition procedure, the second specific procedure for specifying the action performed by the user in the facility and the second specific procedure.
The influence determined based on the behavioral tendency obtained from the behavior specified for each user to be processed by the first specific procedure, and the influence of the advertising content on the stepwise behavior is the advertising content. When it is determined that the user has performed the predetermined action based on the action specified by the second specific procedure while notifying the submission source of the advertisement content as the advertising effect of the above, the user The feature is that the computer executes a notification procedure of notifying the submission source of the advertising content of the advertising effect determined based on the predetermined action and indicating the advertising effect of the advertising content. Information processing program.