JP5060978B2 - Information presentation system, program, information storage medium, and information presentation system control method - Google Patents

Description

The present invention relates to an information presentation system, a program , an information storage medium, and a control method for the information presentation system .

  In the so-called ubiquitous service, as one direction that is currently aimed at, a convenience providing service is proposed in which necessary information is provided to users anytime and anywhere. This is a service that unilaterally provides information to the user from the outside.

  However, in order for a person to live a lively and fulfilling life, a convenience-providing service that provides information to the user unilaterally from the outside is not sufficient. Inspire-type ubiquitous services that encourage awareness and encourage self-growth are desired.

  However, conventional information presentation systems have a problem that information presentation as so-called push information, in which information required by the user is provided without the user performing an intentional acquisition action, cannot be realized.

  As a solution to such a problem, an information presentation system disclosed in Patent Document 1 is known. In this system, it is possible to present information as push information by estimating a user's action by a wearable sensor and displaying information according to the action.

  However, in Patent Document 1, although information whose necessity is manifested can be presented to a user as push information without operation, information that is potentially necessary cannot be presented. It is convenient to continue presenting only the information that reveals the necessity, but it only supports the extension of daily life patterns. Awareness is hard to be born and does not lead to a fulfilling life. On the other hand, in a new experience that is unusual, it can be complicated and anxious.

  Therefore, it is desirable to provide an opportunity to change daily life patterns, and to lower the hurdles of extraordinary experiences and realize an information presentation system that can appropriately balance daily and extraordinary in daily life. It is.

Patent Document 2 discloses a system for monitoring the abnormal behavior of the elderly living alone. This system automatically detects when the elderly living alone becomes inoperable due to an abnormality. It is not intended to be an inspiring ubiquitous service that gives users awareness and encourages their own growth.
JP 2006-293535 A JP 2000-99858 A

According to some aspects of the present invention, there are provided an information presentation system, a program , an information storage medium, and an information presentation system control method that enable presentation of information as push information reflecting the user's daily life.

  The present invention determines a user's current ordinary degree based on sensor information from at least one of a behavior sensor that measures a user's behavior, a state sensor that measures a user's state, and an environment sensor that measures a user's environment. A dailyness evaluation unit that performs processing to evaluate, a familiarity evaluation unit that performs processing to evaluate the intimacy of content that is a candidate for presentation to the user, an evaluation result of dailyness in the dailyness evaluation unit, and the parent A content selection unit that performs processing for selecting content to be presented to the user by the content presenting unit from content that is candidates for presentation to the user based on the evaluation result of the familiarity in the density evaluation unit Related to information presentation system. The present invention also relates to a program that causes a computer to function as each of the above-described units, or a computer-readable information storage medium that stores the program.

  In the present invention, sensor information from at least one of a behavior sensor, a state sensor, and an environmental sensor is acquired, and the user's daily life is evaluated based on the acquired sensor information. In addition, the intimacy of content that is a candidate for presentation to the user is also evaluated. Then, based on the obtained dailyness and familiarity, the content is selected from the content that is a candidate for presentation to the user, and is presented to the user by the content presentation unit. In this way, for example, it becomes possible to select and present to the user the content of closeness corresponding to the level of the user's daily life evaluated based on the sensor information. Accordingly, it is possible to present information as push information reflecting the user's daily life. Thereby, it becomes possible to give a change or notice to the user's daily life pattern, to remove the user's complexity and anxiety in an extraordinary experience, and to present information that has never existed.

  Further, the present invention includes a content information storage unit that stores meta information associated with the content, and the closeness evaluation unit determines the closeness of the user with respect to the content based on the meta information associated with the content. You may evaluate.

  In this way, the content meta-information can be shared between users by personalizing only the intimacy assessment, using collective intelligence, or utilizing something constructed by a third party. Can do. Accordingly, it is possible to simplify the learning effort and improve usability, simplify the evaluation process of intimacy, and realize various evaluation processes of intimacy by using various meta information.

  Further, the present invention includes a familiarity information storage unit that stores information on familiarity with respect to a content category, wherein the content information storage unit stores content category information as the meta information, and the familiarity evaluation unit includes The content category information that is a candidate for presentation is read from the content information storage unit, and the familiarity information for the read category information is read from the familiarity information storage unit. The density may be evaluated.

  In this way, based on the content category information read from the content information storage unit, the familiarity associated with the category information is read from the familiarity information storage unit, so that the content intimacy can be determined. Can be evaluated. Therefore, even when the amount of content information is large, the intimacy of the content can be evaluated efficiently. In addition, this categorization can be performed automatically and statistically by mathematically analyzing the user and usage status.

  In the present invention, the content selection unit may select a content that is evaluated as having a lower familiarity as the user's daily life is evaluated as being higher.

  In this way, it is possible to provide low-intimate content that is not usually touched to users who live daily, so it is possible to give the user a change or new awareness. .

  In the present invention, the content selection unit may select a content that is evaluated as having a higher familiarity as the user's everydayness is evaluated as being lower.

  In this way, users who are experiencing an unusual experience can be provided with highly familiar content that they are familiar with, so it is possible to eliminate the complexity and anxiety of the user in an unusual experience. become.

  In the present invention, the closeness evaluation unit evaluates the closeness of the content based on the closeness of the user with respect to the content and the closeness of others other than the user with respect to the content, and the content selection unit The content to be presented to the user may be selected from the content that is the candidate for presentation based on the familiarity of the content evaluated based on the familiarity of the user and others.

  In this way, since the intimacy of the content is evaluated based not only on the intimacy of the user but also on the intimacy of the other person other than the user, it is possible to give the user a new discovery based on the intimacy of the other person. It becomes possible.

  The present invention further includes a situation estimation unit that estimates a user's situation based on the acquired sensor information, and the dailyness evaluation unit is configured to determine whether or not the user's situation is estimated based on the user's situation estimated by the situation estimation unit. You may evaluate the degree of daily life.

  In this way, since the user's actual situation can be estimated based on various sensor information and the user's ordinary degree can be evaluated, a more accurate and appropriate daily degree evaluation process can be realized.

  The present invention further includes a history information storage unit that stores history information of a user's situation estimated by the situation estimation unit, wherein the dailyness evaluation unit stores a history of the user's situation stored in the history information storage unit You may evaluate a user's everydayness by performing the comparison process of information and the information of the user's present condition estimated by the said condition estimation part.

  In this way, since it is possible to evaluate the ordinary degree reflecting the past situation history of the user, it is possible to realize a more accurate and appropriate everyday degree evaluation process.

  In the present invention, the closeness evaluation unit may evaluate the closeness of content related to at least the current location of the user estimated by the situation estimation unit among the content that is a candidate for presentation to the user. Good.

  In this way, it is possible to evaluate the intimacy of the content related to the user's current location and select the content, and thus it is possible to present appropriate content according to the user's current location.

  The present invention further includes a primary candidate content extraction unit that extracts content that is a primary candidate from content that is a presentation candidate based on the current location of the user estimated by the situation estimation unit, The content selection unit selects content to be presented to the user from the primary candidate content extracted by the primary candidate content extraction unit, based on the evaluation result of dailyness and the evaluation result of familiarity May be.

  In this way, it is not necessary to select content information from all content information based on familiarity and everydayness, and the number of content that can be selected can be reduced. The load of selection processing based on density and dailyness can be reduced.

  In the present invention, the situation estimation unit includes a situation identification unit and a situation prediction unit, and the dailyness evaluation unit includes the user situation predicted by the situation prediction unit and the user identified by the situation identification unit. The user's daily life may be evaluated by performing a comparison process with the actual situation.

  In this way, since the dailyness can be evaluated by detecting the difference between the predicted user situation and the actual user situation, a more appropriate dailyness evaluation process can be realized.

  In the present invention, the daily life evaluation unit evaluates the daily life of the user based on at least first situation information among a plurality of pieces of situation information representing the user's situation, and the closeness evaluation unit includes the first degree of familiarity. The content selection unit evaluates the familiarity of the user with respect to the content related to the first status information, and the content selection unit determines the content related to the first status information based on the evaluation result of the ordinary degree and the evaluation result of the familiarity You may select the content shown with respect to a user by a content presentation part.

  According to the present invention, when the user's dailyness is evaluated based on the first situation information of the plurality of situation information of the user, the content is selected from the contents related to the first situation information. Is selected and presented to the user. Accordingly, since the content corresponding to the first status information that has influenced the evaluation of the dailyness among the plurality of status information can be provided to the user, more appropriate content can be provided.

  In the present invention, a user who uses a history information storage unit that stores information on a user's situation history estimated by the situation estimation unit and a first subsystem of an integrated system that includes a plurality of subsystems is provided. An event determination unit for determining the occurrence of an available event indicating that the second subsystem is newly available, and when the available event occurs, the first subsystem History information update that further updates the status history information that has been updated with the sensor information from the first sensor that is the sensor, based on the sensor information from the second sensor that is the sensor of the second subsystem. May also be included.

  According to the present invention, the user's situation history is stored in the history information storage means as situation history information. When an available event of the second subsystem occurs, the information on the user's situation history is updated based on the sensor information from the second sensor of the second subsystem. In this way, the status history information updated in the first subsystem can be continuously updated based on the sensor information from the second sensor in the second subsystem, and a plurality of sub-systems can be updated. A control system suitable for an integrated system can be provided.

  In the present invention, the closeness evaluation unit may evaluate the closeness of the user with respect to the content based on information on the past behavior history of the user related to the content that is a candidate for presentation.

  In this way, it is possible to realize content intimacy evaluation processing that reflects a user's past action history.

  Hereinafter, this embodiment will be described. In addition, this embodiment demonstrated below does not unduly limit the content of this invention described in the claim. In addition, all the configurations described in the present embodiment are not necessarily essential configuration requirements of the present invention.

1. Acquisition of sensor information In this embodiment, in order to realize an inspire ubiquitous service, a behavior sensor (behavior measurement unit), a state sensor (state measurement unit), and an environment sensor (environmental measurement) that measure user behavior, state, and environment. Sensor information from the computer). Then, based on the acquired sensor information (user status information estimated from the sensor information), the current ordinary degree (unusual degree) of the user is evaluated. First, the sensor information acquisition method will be described.

  In FIG. 1, a user (user) has a portable electronic device 100 (mobile gateway). In addition, a wearable display 140 (mobile display) is mounted as a mobile control target device in the vicinity of one eye of the head. Furthermore, various sensors are worn on the body as wearable sensors (mobile sensors). Specifically, indoor / outdoor sensor 510, ambient temperature sensor 511, ambient humidity sensor 512, ambient light intensity sensor 513, arm-mounted motion measurement sensor 520, pulse (heart rate) sensor 521, body temperature sensor 522, peripheral skin temperature sensor 523, sweat sensor 524, foot pressure sensor 530, speech / mastication sensor 540, GPS (Global Position System) sensor 550 provided in portable electronic device 100, facial color sensor 560 provided in wearable display 140, pupil size sensor 561 Etc. are attached. A mobile subsystem is configured by the portable electronic device 100, a mobile control target device such as the wearable display 140, a wearable sensor, and the like.

  The portable electronic device 100 (mobile computer) is a portable information terminal such as a PDA (Personal Digital Assistant) or a notebook PC. For example, a processor (CPU), a memory, an operation panel, a communication device, a display (sub-display), or the like. Is provided. The portable electronic device 100 has, for example, a function of collecting sensor information from sensors, a function of performing arithmetic processing based on the collected sensor information, and control (display control) of a control target device (such as a wearable display) based on a calculation result. Etc.), a function of retrieving information from an external database, a function of communicating with the outside, and the like. The portable electronic device 100 may be a device that is also used as a mobile phone, a wristwatch, a portable audio, or the like.

  The wearable display 140 (information presentation unit in a broad sense) is mounted in the vicinity of one eye of the user and is set so that the size of the display unit is smaller than the size of the pupil. Function as. Information presentation to the user may be performed using headphones, a vibrator, or the like. In addition to the wearable display 140, various devices such as a wristwatch, a mobile phone, or a portable audio can be assumed as the mobile control target device (information presentation unit).

  The indoor / outdoor sensor 510 is a sensor that detects whether the user is indoors or outdoors. For example, the user irradiates ultrasonic waves and measures the time until the ultrasonic waves are reflected back from the ceiling or the like. However, the indoor / outdoor sensor 510 is not limited to the ultrasonic method, and may be an active light method, passive ultraviolet method, passive infrared method, or passive noise method sensor.

  The ambient temperature sensor 511 measures the ambient temperature using, for example, a thermistor, a radiation thermometer, a thermocouple, or the like. The ambient humidity sensor 512 measures the ambient humidity using, for example, the change in electrical resistance due to humidity. The ambient light intensity sensor 513 measures the ambient light intensity using, for example, a photoelectric element.

  The arm-mounted motion measurement sensor 520 measures the movement of the user's arm with an acceleration sensor or an angular acceleration sensor. By using the motion measurement sensor 520 and the foot pressure sensor 530, it is possible to more accurately measure the user's daily motion and walking state. The pulse (heart rate) sensor 521 is attached to the wrist, finger, or ear, and measures, for example, changes in blood flow associated with pulsation by changes in infrared light transmittance and reflectance. The body temperature sensor 522 and the peripheral skin temperature sensor 523 measure the user's body temperature and peripheral skin temperature using a thermistor, a radiation thermometer, a thermocouple, and the like. The perspiration sensor 524 measures the perspiration of the skin based on, for example, a change in the surface resistance of the skin. The foot pressure sensor 530 detects the pressure distribution of the sole on the shoe, and measures and determines the user's standing state, sitting state, walking state, and the like.

  The utterance / mastication sensor 540 is an earphone-type sensor for measuring the possibility that the user is speaking (conversation) or mastication (meal), and a bone conduction microphone is included in the body. Built-in external sound microphone. The bone conduction microphone detects a body sound which is a vibration generated from the body during speech and mastication and propagating through the body. The external sound microphone detects sound that is vibration that is conducted outside the body in response to an utterance and external sound including environmental noise. Then, by comparing the power of the sound captured by the bone conduction microphone and the external sound microphone in unit time, etc., the utterance possibility and mastication possibility are measured.

  The GPS sensor 550 is a sensor that detects the position (location) of the user. Instead of the GPS sensor 550, a location information service of a mobile phone or location information of a wireless LAN in the vicinity may be used. The face color sensor 560, for example, arranges an optical sensor near the face, and measures the face color by comparing the light intensity after passing through a plurality of optical bandpass filters. The pupil size sensor 561, for example, places a camera near the pupil and analyzes the camera signal to measure the size of the pupil.

  In FIG. 1, sensor information is acquired by a mobile subsystem including a portable electronic device 100, a wearable sensor, and the like. However, as described later, sensor information is acquired by an integrated system including a plurality of subsystems. And the user's situation (behavior history) may be estimated.

2. First System Configuration FIG. 2 shows a first system configuration example of the present embodiment. In FIG. 2, the information presentation system (information providing system) of the present embodiment is realized by, for example, the processing unit 102 of the portable electronic device 100.

  A portable electronic device 100 possessed by a user includes a processing unit 102, a storage unit 120, an information storage medium 130, and a communication unit 138.

  The processing unit 102 performs various processes necessary for the operation of the portable electronic device 100 based on operation information from an operation unit (not shown), sensor information acquired from the wearable sensor 150, and the like. The function of the processing unit 102 can be realized by hardware such as various processors (CPU, etc.), ASIC (gate array, etc.), a program stored in the information storage medium 130 (optical disc, IC card, HDD, etc.), and the like.

  The processing unit 102 includes a sensor information acquisition unit 104, a situation estimation unit 106, a dailyness evaluation unit 110, a closeness evaluation unit 112, and a content selection unit 114. Various modifications may be made such as omitting some of these components (for example, the sensor information acquisition unit and the situation estimation unit) or adding other components.

  The sensor information acquisition unit 104 acquires sensor information from the wearable sensor 150 (sensor in a broad sense). Specifically, the wearable sensor 150 is a behavior sensor that measures user behavior (walking, conversation, meal, limb movement, emotional expression, sleep, etc.), user status (fatigue, tension, hunger, mental status, body The sensor information acquisition unit 104 includes at least one of a state sensor that measures a state or an event that has occurred to the user, and an environmental sensor that measures the user's environment (location, brightness, temperature, humidity, etc.). Acquires sensor information from these sensors.

  The sensor may be the sensor device itself, or may be a sensor device including a control unit, a communication unit, and the like in addition to the sensor device. The sensor information may be sensor primary information obtained directly from the sensor, or sensor secondary information obtained by processing (information processing) the sensor primary information.

  The situation estimation unit 106 (situation identification unit) estimates (identifies) the user's situation (at least one of the user's behavior, state, and environment) based on the sensor information acquired by the sensor information acquisition unit 104. Perform the process. Specifically, multiplication processing or addition processing of the acquired sensor information is performed to realize various calculation processing for sensor information filtering processing (selection processing) or analysis processing. And the situation identification process which is a process which estimates a user's present condition is performed. Alternatively, a situation prediction process that is a process for estimating the future situation of the user is performed.

For example, as shown in the following formula (1), digitized measurement values X _j of a plurality of sensor information from a plurality of sensors and respective coefficients are stored in a coefficient storage unit (not shown), and a two-dimensional matrix ( A product-sum operation with a coefficient A _ij represented by a matrix) is performed. Then, as shown in the following equation (2), the result of the product-sum operation is calculated as an n-dimensional vector Y _i using multidimensional coordinates. Note that i is the i coordinate in the n-dimensional space, and j is a number assigned to each sensor.

  Filtering processing that removes unnecessary sensor information from the acquired sensor information, and user behavior, state, and environment (TPO information) by performing arithmetic processing such as the above formulas (1) and (2) Analytical processing for estimation based on information can be realized. For example, if the coefficient A multiplied by the measured value X of the pulse (heart rate), the amount of sweat, and the body temperature is set to a value larger than the coefficient for the measured value of other sensor information, the above formulas (1) and (2 The numerical value Y calculated in () represents the “excitability” that is the user's state. In addition, by setting the coefficient multiplied by the measured value X of the utterance amount and the coefficient multiplied by the measured value X of the foot pressure to appropriate values, the user's behavior can sit and talk. It is possible to estimate whether the user is talking, walking, talking quietly, sleeping, or the like.

  By estimating the user's situation in this way, time information (year, month, week, day, time, etc.), user location information (position, affiliation area, distance, etc.) and user status information (mind / body) TPO (Time Place Occasion) information that is at least one of a state, an event that has occurred to the user, and the like can be obtained. The TPO information may be acquired based on sensor information from the sensor, or may be acquired based on schedule data (schedule information), download data from the Internet, or the like.

  The everyday degree evaluation unit 110 performs an evaluation process of the daily degree (unusual degree) of the user. For example, the current ordinary degree of the user is evaluated (determined) based on the acquired sensor information. Specifically, when the situation estimation unit 106 estimates the user's situation (for example, current location) based on the acquired sensor information, whether the user's current situation is an everyday situation or an extraordinary situation. Judgment is made, and the degree of daily life is evaluated. For example, by comparing the information on the user's situation history (for example, the situation history of the user's location) with the information on the estimated current situation of the user (eg, the current location), the user's current daily life level can be determined. Can be evaluated. Moreover, a user's present ordinary degree can be evaluated by performing the comparison process of a user's action estimated and a user's actual action. The dailyness is a parameter that represents the degree of everydayness of the user's current situation (normal, common, mediocre), for example, in comparison with the user's past situation history. Also, the process for evaluating the user's daily level and the process for evaluating the extraordinary level (unusual, abnormal level) can be treated as equivalent processes.

  The intimacy evaluation unit 112 performs intimacy evaluation processing. For example, the familiarity of content that is a candidate for presentation to the user is evaluated (determined). Specifically, among the contents that are candidates for presentation to the user, the intimacy of the content related to at least the current situation (location) of the user estimated by the situation estimation unit 106 is evaluated. For example, the user's intimacy with respect to the content can be evaluated based on the information of the user's past behavior history regarding the content that is the candidate for presentation. Further, it is possible to evaluate a user's intimacy with respect to content based on meta information such as a category associated with the content. Alternatively, the closeness of the content may be evaluated based on the closeness of the user with respect to the content and the closeness (popularity) of others other than the user with respect to the content. In addition, familiarity (familiar), for example, the degree of intimacy (intimate, familiar, well-known, well-used) the user (or others) for the content It is a parameter to represent.

  The content selection unit 114 performs content selection processing. Specifically, the presentation to the user is based on the evaluation result of the ordinary degree (daily degree information) in the daily degree evaluation unit 110 and the evaluation result (intimacy information) of the familiarity in the familiarity evaluation unit 112. The content to be presented to the user is selected (determined) from the candidate content by the content presentation unit such as the wearable display 140. For example, when it is evaluated that the user's daily life is high (when it is evaluated that the situation is normal), content that is evaluated as having a low familiarity (content familiar) Unused content, content that you do not normally use). That is, as the dailyness of the user is higher, a content with a lower familiarity is selected. In addition, when the user's daily life is evaluated to be low (when it is evaluated as an abnormal situation), the content that is evaluated as having a high familiarity (content that is familiar, Select the content that you always use. In other words, the less familiar the user is, the more familiar content is selected. The content may be selected based on the familiarity of the content evaluated based on the familiarity of the user and others with respect to the content.

  The storage unit 120 serves as a work area for the processing unit 102, the communication unit 138, and the like, and functions thereof can be realized by a memory such as a RAM or an HDD (hard disk drive). The storage unit 120 includes a content information storage unit 122 and a familiarity information storage unit 124.

  The content information storage unit 122 (content database) stores content information such as text (characters, sentences), images, video, music, audio, or various data. This content may be generated in real time, or may be downloaded from the outside via the communication unit 138, for example. The content information storage unit 122 can store meta information (additional information) associated with the content.

  The familiarity information storage unit 124 stores familiarity information. More specifically, for example, information on familiarity with respect to a content category is stored. Alternatively, information on the intimacy (popularity) of others other than the user is also stored.

  The information storage medium 130 (a computer-readable medium) stores programs, data, and the like, and its function can be realized by an optical disk (CD, DVD) or the like. The processing unit 102 performs various processes of the present embodiment based on a program (data) stored in the information storage medium 130. That is, in the information storage medium 130, a program for causing a computer (an apparatus including an operation unit, a processing unit, a storage unit, and an output unit) to function as each unit of the present embodiment (a program for causing the computer to execute processing of each unit). Is memorized.

  Next, an operation example of the present embodiment will be described using the flowchart of FIG.

  First, content information is read (extracted) from the content information storage unit 122 (content database), or content is generated in real time, thereby preparing (preparing) content that is a candidate for presentation to the user (step S1). Then, the familiarity of the content is evaluated with reference to the familiarity information storage unit 124 (familiarity database) based on meta information or the like associated (corresponding) to the content in advance (step S2).

  Next, the sensor information acquisition part 104 acquires the sensor information from a behavior sensor, a state sensor, or an environment sensor (step S3). Then, the everydayness evaluation unit 110 evaluates the current everydayness of the user based on the user's situation (past situation and its transition situation) estimated (identified) by the sensor information (step S4).

  Next, the content selection unit 114 selects an appropriate content to be presented to the user from the content that is a candidate for presentation based on the familiarity of the obtained content and the dailyness of the user (step S5). Then, the selected content is presented (provided and displayed) to the user by an information presenting unit such as the wearable display 140 (step S6).

  Next, another operation example of the present embodiment will be described with reference to the flowchart of FIG.

  First, the sensor information acquisition unit 104 acquires sensor information from a behavior sensor, a state sensor, or an environment sensor (step S21). Then, the situation estimation unit 106 estimates the user's situation based on the sensor information, and the everydayness evaluation unit 110 evaluates the user's everydayness based on the user's situation (step S22).

  Next, the content selection unit 114 extracts content as a presentation candidate from the content information storage unit 122 based on the user's TPO (Time Place Occasion) information and the familiarity determined by the function of dailyness (step S23). Then, the content to be presented to the user is selected from the content to be presented (step S24), and the selected content is presented to the user by the information presentation unit such as the wearable display 140 (step S25). Specifically, other meta information such as the distance from the current location, required time, and budget is also used to rank the contents, and the contents are displayed on the wearable display 140 according to the ranking. As described above, in the operation example of FIG. 4, the content is extracted after the estimation of the user situation.

3. Second System Configuration Example FIG. 5 shows a second system configuration example of the present embodiment. In the system of FIG. 5, a server 200 that is an external server, a local server (home server), or the like is provided. The portable electronic device 100 and the server 200 are communicatively connected via, for example, the Internet or a wireless LAN. In FIG. 5, the information presentation system of this embodiment is mainly realized by the processing unit 202 of the server 200. Note that the processing of the information presentation system may be realized by distributed processing of the server 200 and the portable electronic device 100.

  In FIG. 5, the sensor information acquisition unit 104 of the portable electronic device 100 acquires sensor information from the behavior sensor, the state sensor, or the environment sensor of the wearable sensor 150. Moreover, the situation estimation part 106 estimates a user's condition based on the acquired sensor information. Then, sensor information and user status information are transmitted to the server 200 by the communication unit 138, and the server 200 receives the information via the communication unit 238.

  Then, the dailyness evaluation unit 210 of the server 200 evaluates the current dailyness of the user based on the received sensor information and situation information. The familiarity evaluation unit 212 also evaluates the familiarity of content that is a candidate for presentation to the user. Specifically, content information is read from the content information storage unit 222, and the familiarity is evaluated with reference to the familiarity information stored in the familiarity information storage unit 224.

  The content selection unit 214 selects content to be presented to the user from the content that is a candidate for presentation to the user, based on the obtained dailyness and familiarity. Then, the information of the selected content is transmitted to the portable electronic device 100 via the communication unit 238. Then, the portable electronic device 100 receives content information via the communication unit 138 and presents (displays) the received content information to the user using the wearable display 140.

  According to the second system configuration example of FIG. 5, the dailyness evaluation process and the familiarity evaluation process can be centralized and processed in the server 200. Thereby, the processing load in the portable electronic device 100 can be reduced, and the processing can be made efficient. In addition, since the content information and the familiarity information are stored in the large-capacity storage unit 220 of the server 200, it is not necessary to store the information on all the contents that are candidates for presentation in the storage unit 120 of the portable electronic device 100. A variety of contents can be prepared on the server 200 side and provided to the user.

4). Specific Operation Example Next, a specific operation example of the present embodiment will be described with reference to FIGS. In the following, an example in which the first system configuration of FIG. 2 is used will be described, but the same operation is performed when the second system configuration of FIG. 5 is used. In the following, a case where content is extracted before estimation of a user situation as in the operation example of FIG. 3 will be described as an example. However, after estimation of a user situation as in the operation example of FIG. Content may be extracted.

  FIG. 6A and FIG. 6B are examples in the case where lunch guidance is given to a user who normally walks in the neighborhood of Shinjuku, the workplace, around noon on weekdays. In this case, store A1 (hamburger), store B1 (gyudonya), store C1 (dinner), store D1 (Chinese), store E1 (Italian) Guidance information of the store F1 (curry shop) and the store G1 (French) that has never entered is extracted from the content information storage unit 122 (222) as content information that is a candidate for presentation.

  FIG. 9 shows an example of content information stored in the content information storage unit 122. In FIG. 9, meta information such as category, region (latitude and longitude), and popularity is stored in association with the contents of each store.

  FIG. 10 shows an example of familiarity information stored in the familiarity information storage unit 124. In FIG. 10, the closeness of the user is stored in association with the category (genre). The intimacy (popularity) of others other than the user may be stored in association with the category.

  As shown in FIG. 10, in the familiarity information storage unit 124, the familiarity of the hamburger shop, the beef bowl restaurant, and the set meal shop category is 5 and the Chinese and Italian categories that do not go so often. For, the intimacy is 3. In addition, the intimacy is 1 for the curry and french categories that have never been entered.

  In the content information of FIG. 9, the category (meta information) of the store A1 is described as a hamburger shop, and in the familiarity information of FIG. 10, the user's familiarity with the hamburger shop category is 5. Therefore, the intimacy of the store A1 is 5. Similarly, the categories of the stores B1 and C1 are beef restaurant and set restaurant, and the closeness of the category is 5, so the closeness of the stores B1 and C1 is 5. Further, since the stores D1 and E1 are Chinese and Italian, the intimacy is 3, and since the stores F1 and G1 are curry restaurants and French, the intimacy is 1.

  As described above, in the present embodiment, the content information storage unit 122 stores content category information as meta information as shown in FIG. 9, and the familiarity information storage unit 124 stores content categories as shown in FIG. Store intimacy information for. Then, the familiarity evaluation unit 112 reads out information on the content category that is a candidate for presentation from the content information storage unit 122. Then, the familiarity information for the read category information is read from the familiarity information storage unit 124 to evaluate the familiarity of the user with respect to the content.

  The situation estimation unit 106 senses and estimates (identifies) the situation of the user who is walking in the neighborhood of his / her office around noon on weekdays based on sensor information from behavioral, state, and environmental sensors. The dailyness evaluation unit 110 recognizes that the estimated situation is a normal situation of the user based on the past situation stored in the storage unit 120, and evaluates the everydayness as 5.

  In order to appropriately balance daily life and extraordinary life, the content selection unit 114 operates, for example, to preferentially select content for which the addition result of dailyness and intimacy is almost constant. Here, since each of the five-level evaluations, the guidance information of the curry store F1 and the French store G1 with closeness of 1 is selected as the content corresponding to the user's daily life level = 5 so that the addition result is 6. I will do it.

  Then, the guide information of the selected stores F1 and G1 is presented to the user by the wearable sensor display 140 that is an information presentation unit. Specifically, as shown in FIG. 6 (B), a display indicating that a store of a category different from usual is used for a change of mood, and a curry restaurant with low intimacy for the user as a candidate store for lunch. The display recommending the store F1 and the French store G1 is performed.

  That is, the situation of the user in FIG. Thus, when it is evaluated that the ordinary degree is high, the information of the content evaluated that the familiarity is low is presented. In this way, it is possible to create a new awareness, discovery, and excitement by creating an opportunity to change the daily life that somehow behaves without thinking, and accepting this and experiencing new experiences by the user. Can be expected.

  FIG. 7A and FIG. 7B are examples when lunch guidance is given to a user walking in Osaka, which is a business trip destination, around noon on weekdays.

  In this case, store A2 (hamburger), store B2 (gyudonya), store C2 (meal restaurant), store D2 (Chinese food), store E2 (Italian), local popular store F2 (curry restaurant), Guidance information such as the store G2 (French) and the store H2 (Takoyaki restaurant) popular with travelers to Osaka is extracted as content information that is a candidate for presentation.

  Also, the hamburgers, beef bowls, and set meals that I always go to have a familiarity of 5 as shown in Fig. 10, Chinese and Italian who don't go very much have a familiarity of 3, and entered Curry restaurants, French restaurants, and takoyaki restaurants have no intimacy.

  And since the categories of stores A2, B2, and C2 are hamburger restaurants, beef bowl restaurants, and set meal restaurants, their familiarity is 5. In addition, since the categories of the stores D2 and E2 are Chinese and Italian, the intimacy is 3, and the categories of the stores F2, G2, and H2 are curry, french, and takoyaki, so the intimacy is 1.

  The situation estimation unit 106 senses and estimates a user situation such as walking in Osaka around noon on weekdays based on the sensor information. The daily life evaluation unit 110, based on the past situation stored in the storage unit 120, is not the user's usual situation, but belongs to the same city category as the usual situation of Shinjuku (similarly Recognizing that he / she has encountered such a situation several times) In this way, the everydayness of the place and the everydayness of the category may be handled separately.

  For example, the content selection unit 114 operates so as to more preferentially select content for which the addition result of dailyness and intimacy is substantially constant. Accordingly, as the content corresponding to the user's daily life level = 3, the guide information of the Chinese store D2 and the Italian store E2 whose intimacy is 3 is selected.

Here, if you add (+2) to the familiarity (popularity) not only for yourself but also for many other people as an evaluation, it is a popular curry shop F2 in local and travelers to Osaka. The popular Takoyaki shop H2 also becomes familiarity 3, and when these guidance information is also selected, the guide information of the selected shops D2, E2, F2, and H2 is the wearable sensor display 140, which is an information presentation unit. Is presented to the user. Specifically, as shown in FIG. 7 (B), since it came to Osaka with a lot of attention, it displays that it will introduce popular shops to locals and travelers, and as a candidate for lunch, a Chinese shop D2, In addition to recommending the Italian store E2, the display also recommends the locally popular curry store F2 and the takoyaki store H2 popular with travelers.

  That is, the situation of the user in FIG. 7A is about the middle of everyday and extraordinary, and in such a situation, the information of the content that is evaluated to be moderate about the familiarity is presented. In this way, in situations where the experience is not everyday but relatively similar, it is possible to create an opportunity for a unique experience that is difficult to experience in daily life. You can expect new experiences, discoveries, and excitement through the experience. In addition, it is possible to respond to the user's feeling that "I have come so far ...".

  FIG. 8A and FIG. 8B are examples in the case where lunch guidance is given to a user who is walking in a countryside overseas business trip destination around noon on weekdays.

  In this case, guide information such as the store A3 (hamburger store), the store D3 (Chinese restaurant), the store E3 (Italian), and the store F3 (curry store) is extracted as the content information that is a candidate for presentation.

  In addition, the hamburger shop that I always go to has an intimacy of 5 as shown in Fig. 10, Chinese and Italian who don't go so much have an intimacy of 3, and curry shops that I have never entered are intimacy. Is 1. Therefore, the intimacy of the store A3 which is a hamburger shop is 5, the intimacy of the shops D3 and E3 which are Chinese and Italian is 3, and the intimacy of the shop F3 which is a curry shop is 1.

Based on the sensor information, the situation estimation unit 106 senses and estimates the user's situation such as walking in a countryside town around noon on weekdays. The dailyness evaluation unit 110 recognizes that the user has not encountered a similar situation in the past from the past situation, and evaluates the dailyity as 1. Content selection unit 114, for example, operates so as to preferentially select content for which the addition result of dailyness and intimacy becomes substantially constant. Therefore, the hamburger shop A3 having a familiarity of 5 is selected as the content corresponding to the user's dailyness = 1.

  Then, the guide information of the selected store A3 is presented to the user by the wearable sensor display 140. Specifically, as shown in FIG. 8 (B), a display that introduces a safe shop because it is the first overseas country town, and a display that recommends a hamburger shop A3 as a candidate for lunch is displayed. Do.

  That is, the situation of the user in FIG. 8A is an extraordinary situation, and in such a situation, information of content that is evaluated as having a high degree of closeness is presented in order to reassure the user. In this way, in an uneasy situation that is not everyday and does not have a similar experience, information that leads to a situation that is relatively experienced in daily life is presented and the user accepts it. This can be expected to create a sense of security.

5. Detailed Configuration Example FIG. 11 shows a detailed system configuration example of the present embodiment. In FIG. 11, the processing unit 102 includes a sensor information acquisition unit 104, a situation estimation unit 106, a dailyness evaluation unit 110, a closeness evaluation unit 112, a primary candidate content extraction unit 113, a content selection unit 114, an event determination unit 116, and a history. An information update unit 118 is included. The situation estimation unit 106 includes a situation identification unit 107 and a situation prediction unit 108. Note that some of these components may be omitted, or other components may be added. Similarly to FIG. 4, some functions of the processing unit 102 of FIG. 11 (for example, the situation prediction unit, the dailyness evaluation unit, the closeness evaluation unit, the primary candidate content selection unit, the content selection unit, etc.) are performed on the server side. It may be realized.

  The situation identification unit 107 performs a situation identification process for the user. Specifically, the actual (current) situation of the user is identified (estimated) based on sensor information from the sensor.

  The situation prediction unit 108 (behavior prediction unit) performs a process of predicting the user's situation (behavior). Specifically, the future situation of the user is predicted. For example, the user's future situation is predicted based on information on the user's past situation history (such as the user's behavior history). For example, the personal model information storage unit 128 stores information on the user's personal model. This personal model information can be updated based on the past situation history information of the user identified by the situation identification unit 107. The situation prediction unit 108 predicts the future situation of the user based on the information of the personal model stored in the personal model information storage unit 128.

  The dailyness evaluation unit 110 performs a comparison process between the user situation (behavior) predicted by the situation prediction unit 108 and the actual situation (behavior) of the user identified by the situation identification unit 107. Evaluate your current daily life.

  The primary candidate content extraction unit 113 performs content extraction processing as a primary candidate. Specifically, based on the current location of the user identified by the situation identification unit 107, the content that is the primary candidate is extracted from the content that is the presentation candidate. The content selection unit 114 then presents the content presented to the user from the primary candidate content extracted by the primary candidate content extraction unit 113 based on the evaluation result of the ordinary degree and the evaluation result of the familiarity Select.

  The event determination unit 116 performs various event determination processes. Specifically, a user who has used the first subsystem (for example, a mobile subsystem) can now use the second subsystem (for example, a home subsystem or an in-house subsystem). The occurrence of an available event indicating that is determined. For example, a sensor available event that allows a user whose situation history information (behavior history information) is updated by sensor information from sensors in the first subsystem to use a second sensor that is a sensor in the second subsystem. The occurrence of (sensor accessible event, sensor information obtainable event) is determined. Alternatively, the occurrence of a device available event (device accessible event, device controllable event) that makes the second control target device that is the control target device of the second subsystem available is determined. Alternatively, it is determined whether an unusable event that disables the use of the second subsystem (second sensor, second control target device) occurs. For example, the event determination unit 116 can determine that an available event has occurred when the user approaches (moves) the location of the second subsystem. Alternatively, when information transfer is performed wirelessly, occurrence of an available event can be determined by detecting wireless strength. Alternatively, it can be used when a device of the first subsystem (for example, a portable electronic device) is connected to a cradle that can be used by the second subsystem (a cradle installed at the location of the second subsystem). It can be determined that an event has occurred.

  Then, when an available event occurs, the history information update unit 118 acquires sensor information from the second sensor of the second subsystem, and updates the user status history information based on the acquired sensor information. To do. That is, based on the sensor information from the second sensor that is the sensor of the second subsystem, the status history information that has been updated with the sensor information from the first sensor that is the sensor of the first subsystem, Update further.

  The updated status history information is stored in the history information storage unit 126. The situation history information (situation log) is information about at least one of the user's action, state, and environment estimated by the situation estimation unit 106 based on sensor information from at least one of the behavior sensor, the state sensor, and the environment sensor. It is history information.

  Next, the detailed operation of this embodiment will be described with reference to the flowchart of FIG.

  First, the sensor information acquisition unit 104 acquires sensor information from a behavior sensor, a state sensor, and an environment sensor (step S11). Then, the situation estimation unit 106 estimates the current location (current situation) of the user based on the acquired sensor information or the like (for example, location information from a GPS sensor, location information service or location information from a wireless LAN). (Step S12). For example, the location of the user is identified as Shinjuku in FIG. 6 (A), identified as Osaka in FIG. 7 (A), and identified as an overseas country town in FIG. 8 (A).

  Next, the primary candidate content extraction unit 113 extracts the content that is the primary candidate from the content information storage unit 122 based on the identified current location (current situation) (step S13). For example, in FIG. 6A, since the current location of the user is Shinjuku, the guidance information of the stores A1 to G1 in Shinjuku is extracted as content. Similarly, in FIGS. 7A and 8A, since the user's current location is Osaka, an overseas country town, the guidance information of Osaka stores A2-H2 and overseas country town stores A3-F3. Is extracted as content.

  Next, the familiarity evaluation unit 112 evaluates the familiarity of the primary candidate content that is content related to the user's current location (current situation) (step S14).

  For example, in FIG. 6A, the intimacy of stores A1 to G1, which are contents related to Shinjuku, which is the user's current location, is evaluated, and the intimacy of stores A1, B1, and C1 is evaluated to be 5, and store D1 , E1 has a closeness of 3 and stores F1 and G1 have a closeness of 1. Similarly, in FIG. 7A, the intimacy of stores A2 to H2, which are contents related to Osaka, which is the user's current location, is evaluated. In FIG. The intimacy of stores A3 to F3, which are contents related to the town, is evaluated.

  Next, the status history information regarding the user's current location (current status) and the user's current location information (current status information) are compared to evaluate the user's everydayness ( Step S15).

  For example, in FIG. 6A, it is determined from the user's situation history that the user is often in Shinjuku, where he is working, and the current location of the user is Shinjuku. Be evaluated. In FIG. 7A, from the user's situation history, it is determined that the user is not so often in the business trip destination Osaka, but is often in the same city category, and the current location of the user is Since it is Osaka, the user's daily life is judged to be medium. Also, in FIG. 8A, it is determined from the user's situation history that the user is rarely in an overseas countryside business destination or in a similar city category, and the current location of the user is Since it is an overseas country town, it is determined that the daily life of the user is extremely low.

  Next, the content selection unit 114 selects a content to be presented to the user from the primary candidate content based on the familiarity of the content obtained in step S14 and the user's everydayness obtained in step S15. Select (step S16). Then, the selected content is presented to the user by an information presentation unit such as the wearable display 140 (step S17).

  For example, in FIG. 6B, stores F1 and G1 are selected from the primary candidates stores A1 to G1, and the guidance information is displayed. In FIG. 7B, stores D2, E2, F2, and H2 are selected from the primary candidate stores A2 to H2, and the guidance information is displayed. In FIG. 8B, the store A3 is selected from the primary candidates stores A3 to F3, and the guidance information is displayed.

  As described above, in the present embodiment, at least user location information is acquired for identifying the user situation, and the primary candidate content is extracted based on the acquired location information.

  That is, if content information is selected from all content information (for example, store information around the world) based on familiarity and everydayness, the processing load becomes very heavy.

  In this regard, as in this embodiment, if the estimated location information of the user is effectively used and content information related to the location is first extracted, the number of content items that can be selected can be reduced. The load of selection processing based on intimacy and everydayness can be greatly reduced.

6). Evaluation of Everydayness Next, details of the dailyness evaluation process will be described. In FIG. 13, the situation identification unit 107 identifies (estimates) the situation of the user's action, state, environment, and the like based on the sensor information of the action, state, and environment. Then, the history information (log information) of the obtained user situation is accumulated in the history information storage unit 126. Then, by analyzing the accumulated situation history information, the user's personal hobbies / preferences and behavioral trends are constructed as a personal model and stored in the personal model information storage unit 128 (personal model database).

Note that a probabilistic model can be used as the individual model, and an example of such a probabilistic model is a hidden Markov model. In this hidden Markov model (HMM), the system assumes that the parameter is an unknown Markov process and estimates the unknown parameter from observable information. That is, the HMM has a probability that a certain system has an internal state that transitions according to a Markov process and estimates the state transition inside the system from the appearance probability distribution of the symbol when it is considered that a symbol corresponding to each state is output stochastically. It is a model. Only the sequence of symbols can be observed from the outside, and the situation prediction unit 108 called “hidden” because the internal state transition cannot be observed directly, the situation prediction unit 108 is based on this personal model information (situation history information). Predict the behavior (situation in the broad sense). The situation identifying unit 107 identifies the actual action of the user. Then, the dailyness evaluation unit 110 determines the degree to which the identified user's actual behavior matches the user's behavior predicted based on the immediately preceding situation and the personal model. Assess degree.

  Next, the dailyness evaluation method will be specifically described with reference to FIGS. 14 (A) to 14 (D). FIG. 14A is an example of a user's weekday situation history (action history). The user gets up at 7:30 on weekdays, has breakfast at 8 o'clock, leaves his home at 8:30, and gets on the train at station A near his home at 8:45. The situation prediction unit 108 predicts a user's next action from such a user's situation history.

  Then, for example, from the situation history in FIG. 14A, the situation prediction unit 108 predicts that the user is most likely to go to the company in the next action as shown in FIG. 14B. When the actual action of the user identified by the situation identification unit 107 is an action to go to the company, the everydayness evaluation unit 110 evaluates that the everydayness of the user is high. On the other hand, if the user returns home immediately due to an emergency situation or the like, and the actual action of the identified user is returning home, the degree of daily life is low, and it is evaluated that it is unusual.

  FIG. 14C shows an example of a user's holiday situation history. The user gets up at 8:30 on a holiday, has breakfast at 9:00, and leaves the house by car at 9:30. The situation prediction unit 108 predicts a user's next action from such a user's situation history.

  14C, for example, the situation prediction unit 108 predicts that the user is most likely to go to the tennis school H in the next action as shown in FIG. 14D. When the actual action of the user identified by the situation identification unit 107 is an action to go to the tennis school H, the everydayness evaluation unit 110 evaluates that the everydayness of the user is high. On the other hand, when driving to a sightseeing spot K far from the city center, the degree of daily life is low, and it is evaluated that it is unusual.

  In the present embodiment, the everydayness evaluation unit 110 evaluates the dailyness of the user based on at least first situation information among a plurality of situation information (situation parameters, element parameters) representing the situation of the user, for example. In this case, the familiarity evaluation unit 112 evaluates the user's familiarity with the content related to the first situation information. And the content selection part 114 selects the content shown with respect to a user from the content relevant to 1st condition information based on the evaluation result of a usualness degree, and the evaluation result of closeness.

  Here, the situation information is information representing the user situation such as the user's location, time, and user behavior. For example, when the first situation information is information on the location of the user, the everydayness evaluation unit 110 evaluates the everydayness of the user based on the information on the location of the user. Then, the intimacy evaluation unit 112 evaluates the intimacy of the user with respect to the store information, which is the content related to the user's location, as described with reference to FIGS. 6 (A) to 8 (B). And the content selection part 114 selects the content shown with respect to a user from the content relevant to the information of a user's place based on a usualness degree and familiarity.

  As the situation information (first situation information) to be evaluated for the user's daily life, various things can be assumed in addition to the information on the user's place. May be information on the person who is talking, information on the user's tension, and the like.

  For example, it is assumed that the situation information to be evaluated for dailyness is information on a TV program that the user watches. In this case, when the user is watching a TV program in the usual category (genre), the user's daily life is evaluated as being high, and when watching a TV program in a category that is not normally seen, Assess that the degree is low (the degree of unusualness is high). Specifically, the channel selected by the user is identified, and the content of the TV program being broadcast on that channel is extracted by various services to determine the content of the TV program that the user is watching. Assess degree.

  And when evaluating a user's everydayness based on the information (1st condition information) of the television program which the user is watching in this way, the familiarity of the content relevant to the information of a television program is evaluated. Then, the content is selected based on the evaluated dailyness and intimacy and presented to the user.

  For example, if the user is watching an ordinary program (for example, baseball) and is evaluated as having a high degree of everydayness, a content such as a telop screen that prompts the user to view a program (for example, a drama) in a category that is intimate to the user Is displayed on the television screen, which is an information presentation unit. In this way, it is possible to create an opportunity to change the audition of the television program that was selected without thinking.

  On the other hand, if a user rarely watches a television program of a genre (for example, a horror movie) and is evaluated as having a low level of everydayness, a television program (for example, a music program) of a category that is intimate and safe for the user. ) Select a content such as a telop screen that teaches the channel and display it on the TV screen. In this way, it is possible to give a sense of security to a user who has watched an unusual television program by teaching the usual television program channel.

  Further, it is assumed that the situation information to be evaluated for dailyness is information on a person with whom the user is talking. In this case, when the user is talking with a person who is always meeting, the user is evaluated as having a high degree of everydayness, and when the user is speaking with a person who rarely meets, the user is evaluated as having a low degree of everydayness. Specifically, the location of the first user and the location of the second user are detected using a GPS sensor or the like, and when these locations match and an utterance is detected, the first user It is determined that the user 2 is meeting and talking. And the frequency information with which the 1st user talks with the 2nd user is acquired from the 1st and 2nd user's identification information and the 1st and 2nd user's situation history information, and based on this frequency information For the first user, it is determined whether or not it is routine to talk with the second user.

  And when evaluating a user's everydayness based on the information of the person who the user is talking in this way, the familiarity about the content relevant to the information of the person who is talking is evaluated, for example. Then, the content is selected based on the evaluated dailyness and intimacy, and presented to the user.

  In addition, when evaluating everydayness, it is desirable to evaluate each of 5W1H (Who, What, When, Where, Why, How). For example, assume that the user's company location is Shinjuku. In this case, if the user is in Shinjuku on weekdays, it is evaluated that the ordinary degree is high, but if the user is in Shinjuku on a holiday, it is evaluated that the ordinary degree is low. That is, even if the place is the same, if the time and date are different, the evaluation result of the ordinary degree will be different. In addition, if the first and second users who are colleagues of the company meet at the company on weekdays, it is evaluated that the ordinary degree is high, but if they meet at a place other than the company on a holiday, the ordinary degree is Rated low. In other words, even if the person is the same, if the time and place are different, the evaluation result of the ordinary degree will be different.

7). Intimacy Evaluation Next, the details of the familiarity evaluation process will be described. In FIG. 15A, the closeness evaluation unit 112 evaluates the closeness of the user with respect to the content based on the past action history information of the user related to the content that is the candidate for presentation.

  Specifically, the intimacy evaluation unit 112 refers to the user's behavior history in the history information storage unit 126 to determine the past experience of the behavior related to the content of the candidate content, and this is the latest Evaluate intimacy including whether or not there was. For example, the user's intimacy regarding the contents of the hamburger shop is evaluated in consideration of the frequency of the user having visited the hamburger shop in the past and the frequency of the recent visit to the hamburger shop.

  In this way, the user's familiarity with respect to the content can be evaluated by effectively utilizing the user's situation history used for the evaluation of the user's daily life.

  In FIG. 15B, the situation identification unit 107 identifies the user situation based on the sensor information, and the history information of the user situation is accumulated in the history information storage unit 126. Then, by analyzing the situation history information, a personal model of the user is constructed and stored in the personal model information storage unit 128.

  The situation prediction unit 108 predicts the user's next action (situation) based on the information of the personal model. Then, the closeness evaluation unit 112 evaluates the closeness of the presentation candidate content based on the occurrence probability of the presentation candidate content with respect to the predicted user behavior.

  For example, it is assumed that when a user goes to Shinjuku on a holiday, the predicted probability of taking an action of going to a hamburger shop is high, but when going to Shinjuku on weekdays, the predicted probability of taking an action of going to a hamburger shop is low. Then, when the user goes to Shinjuku on a holiday, the intimacy of the hamburger shop, which is the candidate content, is evaluated highly, whereas when the user goes to Shinjuku on weekdays, the intimacy of the hamburger shop is evaluated to be low. Is done. As described above, in FIG. 15B, the familiarity of the content changes according to the predicted user behavior. Accordingly, it is possible to evaluate the intimacy that further reflects the user's hobbies and preferences.

8). Integrated System As described above, in this embodiment, the user's daily life is evaluated based on the user's situation history. For example, in FIG. 13, the user's daily life is evaluated by predicting the user's behavior based on the situation history and comparing it with the actual behavior. 15A and 15B, the closeness of the presentation candidate content is evaluated based on the user's situation history, the user's behavior predicted from the situation history, and the like.

  In this case, the user does not always wear the wearable sensor 150 or the wearable display 140. When the user goes home or gets in the car, the wearable sensor 150 or the wearable display 140 may be removed. is assumed. Therefore, if the status history information is updated only by the wearable sensor 150 or the information is presented only by the wearable display 140, the continuity of information update and information presentation is not maintained, and the convenience for the user is hindered.

  Therefore, in FIG. 16, the update of the user status history information and the information presentation to the user are realized by the integrated system.

  The integrated system shown in FIG. 16 includes a plurality of subsystems such as a mobile subsystem, a home subsystem, or an in-vehicle subsystem. The subsystems are not limited to these, and various subsystems having sensors and control target devices such as in-company subsystems, in-store subsystems, and vehicles (trains, airplanes) subsystems other than cars can be assumed.

  The mobile subsystem includes a wearable sensor such as the portable electronic device 100, a wearable display 140 that is a mobile control target device, and an indoor / outdoor sensor 510.

  The home subsystem is a home control target device, for example, a home display such as a TV monitor or a PC monitor, a home AV device such as an audio device or an optical disk player, a robot such as a dog, cat, or humanoid, or a room temperature. It has an air conditioner that adjusts the lighting and lighting that adjusts the brightness. In addition to this, as home control target devices, various devices such as home appliances such as game machines, vacuum cleaners, rice cookers, refrigerators, microwave ovens, and security devices can be assumed.

  In addition, the home subsystem is a home sensor, for example, an environmental sensor that measures the temperature, humidity, light intensity, noise, user conversation, meal, etc. in the home, a robot-mounted sensor built into the robot, And a human detection sensor installed in a door, a urine test sensor installed in a toilet, and the like. In addition to this, various sensors such as a security sensor (security sensor, heat / smoke / gas sensor, etc.), an earthquake sensor, a power consumption measurement sensor, a pollen sensor, and the like can be assumed as the home sensor. These home control target devices and home sensors constitute a home subsystem (second subsystem in a broad sense).

  The in-vehicle subsystem includes car navigation systems (navigation devices) that provide road guidance, car AV equipment such as audio equipment and optical disk players, and air conditioners that adjust the temperature inside the car as in-vehicle control target equipment. Other in-vehicle control devices include safety devices such as airbags, seat adjustment devices, car door locking / unlocking devices using smart entry systems, communication devices, in-vehicle devices, etc. Various devices such as a computer can be assumed.

  The in-vehicle subsystem is also used as an in-vehicle sensor such as a driving state sensor that measures the speed of a vehicle, a moving distance, an operation state sensor that measures a user's driving operation and device operation, an in-vehicle temperature, humidity, luminous intensity, It has an environmental sensor that measures conversation and the like. In addition to this, various sensors such as a crime prevention sensor, a human detection sensor, and a pollen sensor can be assumed as the in-vehicle sensor. An in-vehicle subsystem (third subsystem in a broad sense) is configured by these in-vehicle control target devices and in-vehicle sensors.

  In the integrated system of FIG. 16, when the user is outdoors (in a mobile environment), sensor information (including sensor secondary information) is acquired (collected) from the wearable sensor (mobile sensor) of the mobile subsystem. Then, the user's situation history information is updated based on the acquired sensor information. The mobile control target device is controlled based on the situation history information and the like.

  On the other hand, when the user is at home (in a home environment), sensor information from the home sensor of the home subsystem is acquired, and the status history information is updated based on the acquired sensor information. That is, the status history information updated in the mobile environment is seamlessly updated even when the home environment is transferred. The home control target device is controlled based on the situation history information and the like.

  In addition, when the user is in the vehicle (in the case of an in-vehicle environment), sensor information from the in-vehicle sensor of the in-vehicle subsystem is acquired, and the status history information is updated based on the acquired sensor information. That is, the status history information updated in the mobile environment or the home environment is seamlessly updated even when the in-vehicle environment is transferred. In addition, the in-vehicle control target device is controlled based on the situation history information and the like.

  For example, when a user arrives at home or moves into a vehicle, the user is likely to remove a wearable sensor (such as an indoor / outdoor sensor) or a mobile control target device (such as a wearable display). Also in such a case, according to the integrated system of FIG. 16, sensor information can be acquired using a home sensor or an in-vehicle sensor instead of a wearable sensor, so that seamless status history information can be updated. For example, for meals when going out and meals at home, it is possible to keep a history of meal times, meal times, etc., and cumulative calculation of energy consumption and stress based on internal and external behavioral status and heart rate status Processing is also possible.

  In addition, instead of the mobile control target device, the home control target device and the in-vehicle control target device can be controlled, and the convenience for the user can be improved. For example, instead of a wearable display with a small display area, information on the content selected based on the status history information is displayed (presented) on a home display or car navigation display with a large display area, or a control target that could not be controlled in a mobile environment Equipment (for example, air conditioner, lighting, car navigation system, etc.) can be controlled, and convenience can be improved.

  Next, the operation of the integrated system will be described with reference to FIGS. 17 (A) and 17 (B). FIG. 17A is a flowchart relating to the update of status history information. Here, a user who uses the first subsystem (a user whose user information has been updated based on sensor information from the first sensor that is a sensor of the first subsystem) is the second subsystem. A case where the state is shifted to a state where the (second sensor) can be used will be described as an example.

  First, the event determination unit 116 of FIG. 11 determines whether or not the second subsystem (second sensor) can be used (step S61). For example, when the user moves to the location of the second subsystem, the second subsystem becomes available. If the sensor becomes available, a sensor (second sensor) that can be used in the second subsystem is selected (step S62).

  Next, the sensor information acquisition unit 104 acquires sensor information from the selected sensor (step S63). Then, the history information update unit 118 updates the situation history information based on the acquired sensor information, and stores the updated situation history information in the history information storage unit 126 (step S64). If it is determined in step S61 that the use of the second subsystem is not yet possible, the situation history information is updated based on the sensor information from the first sensor that is a sensor of the first subsystem. Will continue.

  FIG. 17B is a flowchart regarding control processing of the control target device. Here, a user who uses the first subsystem (a user who is controlling the first control target, which is the control target device of the first subsystem), is the second subsystem (second The case of shifting to a state in which the control target device) can be used will be described as an example.

  First, the event determining unit 116 determines whether or not the second subsystem (second control target device) can be used (step S71). Then, when it becomes available, an available control target device is selected (step S72).

  Next, the situation history information is read from the history information storage unit 126 (step S73). Then, based on the read status history information, output information to the selected control target device is selected (step S74), and the selected output information is output to the control target device to control the control target device. Starts (step S75). If it is determined in step S71 that the second subsystem cannot be used yet, the control of the control target device (first control target device) of the first subsystem is continued.

  For example, in FIG. 17A, if a sensor corresponding to the user's TPO information is selected, a different sensor can be selected depending on the location, time, and situation. Therefore, the meaning of the sensor information can be made different depending on the location, time, and situation of the sensor information, and more intelligent sensor information acquisition processing can be realized. In addition, by selecting an appropriate sensor according to the location, time, and situation, it is possible to appropriately update the situation history information.

  In sensor selection for acquiring sensor information for TPO determination, a sensor effective for TPO determination or a sensor capable of detecting a change in TPO may be selected. For example, in an indoor area, an acceleration sensor that is an effective sensor for indoor position determination (TPO determination) is selected. However, with only the acceleration sensor, it is impossible to detect that the GPS sensor can be used from the indoor to the outdoor, and the sensor cannot be reselected. Therefore, in this case, it is desirable to select an indoor / outdoor sensor.

  For example, in a home subsystem, when a user is in the living room, a light intensity sensor or an air temperature sensor is selected for lighting control or air conditioning control. On the other hand, when the user is in the toilet, the urinalysis sensor is selected in order to create the history information of the user's health condition. When the user approaches the robot, the robot-mounted sensor is selected in order to make the robot correspond to the user or to update the history information of the user's action using the robot. Also, during daytime hours, an air temperature sensor is selected for air-conditioning control, and during night hours, a body temperature sensor is selected to measure the user's body temperature during sleep and create user's health status history information. Or select security sensors for security. In addition, when the user is in a busy situation, the light intensity sensor is selected for lighting control to relax the user. When the user is in a spare situation, for robot control to eliminate the user's spare time, Select a robot-mounted sensor.

  In FIG. 17B, if a control target device is selected according to the user's TPO information, a different control target device can be selected according to location, time, and situation, and a more intelligent device. Control can be realized.

  For example, in the home subsystem, when the user is in the living room or in the time zone when the user is waking up, a control target device such as a home display, an AV device, or a robot is selected to eliminate the user's time. Alternatively, when the user approaches the home display, the AV device, or the robot, the device that the user has approached is selected. On the other hand, when the user is in the bedroom or in the night time, a control target device such as an air conditioner or lighting is selected in order to realize a comfortable sleep of the user. In a situation where the user is not energetic, a robot is selected to energize the user, and in a situation where the user is busy, a home AV device is selected to play music for relaxing the user.

9. Situation History Information Next, a specific example of update processing of situation history information of a user and situation history information will be described. FIG. 18 is a flowchart illustrating an example of the status history information update process.

  First, the sensor information acquisition unit 104 acquires sensor information (step S81). Next, the situation estimation unit 106 performs calculation processing such as filtering and analysis of the acquired sensor information (step S82), and estimates the situation (TPO) of the user's behavior, state, environment, and the like based on the calculation result (step S82). Step S83). Then, the history information update unit 118 stores the estimated user status history in the history information storage unit 126 in association with the date and time (year, month, week, day, time), etc., and updates the status history information ( Step S84).

  FIG. 19 schematically shows a specific example of the situation history information. The situation history information in FIG. 19 has a data structure in which a situation history such as user behavior is associated with a time zone, a time, and the like. For example, the user departs from home at 8 o'clock, walks from his home to the station in the time zone from 8 o'clock to 8:20, and arrives at the nearest station A at 8:20. And, from 8:20 to 8:45, I got on the train, got off at the nearest B station of the company at 8:45, arrived at the company at 9:00, and started work. During the time zone from 10:00 to 11:00, meetings are held with members in the company, and lunch is served from 12:00 to 13:00.

  As described above, in FIG. 19, the situation history information is constructed by associating the situation history such as the user's behavior estimated by the sensor information or the like with the time zone, the time, or the like.

  In FIG. 19, measurement values such as a user's utterance amount, a meal amount, a pulse rate, and a sweat amount, which are measured by a sensor or the like, are also associated with the time zone and the time. For example, in the time zone from 8:00 to 8:20, the user is walking from the home to the station A, but the walking amount at this time is measured by the sensor and is associated with the time zone from 8:00 to 8:20. It is done. In this case, for example, measurement values of sensor information other than the walking amount such as walking speed and sweating amount may be further associated. By doing so, it becomes possible to grasp the user's momentum and the like in this time zone.

  In the time zone from 10 o'clock to 11 o'clock, the user is having a meeting with a colleague, and the amount of speech, etc. at this time is measured by a sensor and correlated with the time zone from 10 o'clock to 11 o'clock. In this case, for example, measurement values of sensor information such as a voice state and a pulse may be further associated. By doing so, it becomes possible to grasp the user's conversation volume, degree of tension, and the like during this time period.

  In the time zone from 20:45 to 21:45 or from 22:00 to 23:00, the user is playing a game or watching TV, but the pulse, sweating amount, etc. at this time are in these time zones. Associated. By doing so, it becomes possible to grasp the degree of excitement of the user in these time zones.

  In the time zone from 23:30, the user is sleeping, but a change in the user's body temperature at this time is associated with this time zone. By doing so, it becomes possible to grasp the health condition of the user during sleep.

  Note that the situation history information is not limited to the form as shown in FIG. 19. For example, the situation history information can be modified without associating the situation history such as the user's behavior with the date and time.

  For example, in FIG. 20A, the mental state parameter of the user is calculated according to a predetermined arithmetic expression based on the utterance amount, the voice state, the pulse rate, the perspiration amount, etc., which are measured values of the sensor information. For example, if the utterance amount is large, the mental state parameter also becomes high, indicating that the user's mental state is good. In addition, based on a walking amount, walking speed, body temperature, and the like, which are measurement values of sensor information, a user body condition (health state) parameter (exercise amount parameter) is calculated according to a predetermined calculation formula. For example, if the amount of walking is large, the body condition parameter also increases, indicating that the user's body condition is good.

  As shown in FIG. 20B, the user's mental state and body state parameters (state parameters in a broad sense) can be displayed on a wearable display, home display, or car navigation display by visualizing them using a bar graph or the like. . Therefore, according to the present embodiment, for example, with respect to the home display in the home environment and the car navigation display in the in-vehicle environment using the situation history information such as the mental state and body state parameters updated in the mobile environment, FIG. The parameter can be visualized and displayed as in B). Alternatively, the robot in the home environment can be controlled based on the mental state and body state parameters updated in the mobile environment to encourage the user or to allow the robot to perform an operation that advises the user. Alternatively, in the in-vehicle environment, navigation according to the parameters of the user's mental state and physical state and music can be played.

  In addition, when a user moves between multiple subsystems (mobile, home, in-vehicle, etc.), sensor information from sensors available in each subsystem is acquired, and the user's mental state, physical state, etc. It is also possible to update state parameters continuously and seamlessly.

  Although the present embodiment has been described in detail as described above, it will be easily understood by those skilled in the art that many modifications can be made without departing from the novel matters and effects of the present invention. Accordingly, all such modifications are intended to be included in the scope of the present invention. For example, a term (wearable display, wearable sensor, etc.) described together with a different term (information presentation unit, sensor, etc.) in a broader sense or the same meaning at least once in the specification or drawing is used anywhere in the specification or drawing. Can be replaced by its different terms. Further, the configuration and operation of the information presentation system, the portable electronic device, and the server are not limited to those described in this embodiment, and various modifications can be made.

Explanatory drawing of the acquisition method of sensor information. The 1st system configuration example of this embodiment. The flowchart for demonstrating the operation example of this embodiment. The flowchart for demonstrating the other operation example of this embodiment. The 2nd system configuration example of this embodiment. FIG. 6A and FIG. 6B are explanatory diagrams of specific operations of this embodiment. FIG. 7A and FIG. 7B are explanatory diagrams of specific operations of the present embodiment. FIG. 8A and FIG. 8B are explanatory diagrams of specific operations of this embodiment. An example of content information. An example of familiarity information. 2 is a detailed system configuration example of the present embodiment. The flowchart for demonstrating the detailed operation | movement of this embodiment. Explanatory drawing of the evaluation method of everydayness. FIG. 14A to FIG. 14D are explanatory diagrams of a dailyness evaluation method. FIG. 15A and FIG. 15B are explanatory diagrams of an evaluation method of intimacy. Illustration of an integrated system of multiple subsystems 17A and 17B are flowcharts for explaining the operation of the integrated system. The flowchart of the update process of a user's condition history information. Explanatory drawing of a user's condition history information. 20A and 20B are explanatory diagrams of the user's situation history information.

Explanation of symbols

100 portable electronic device, 102 processing unit, 104 sensor information acquisition unit,
106 situation estimation unit, 107 situation identification unit, 108 situation prediction unit,
110 daily life evaluation unit, 112 familiarity evaluation unit, 113 primary candidate content extraction unit,
114 content selection unit, 116 event determination unit, 118 history information update unit,
120 storage units, 122 content information storage units, 124 intimacy information storage units,
126 history information storage unit, 128 personal model information storage unit, 130 information storage medium,
138 communication unit, 140 wearable display, 150 wearable sensor,
200 servers, 202 processing units, 210 daily life evaluation units, 212 intimacy evaluation units,
214 content selection unit, 220 storage unit, 222 content information storage unit,
224 Intimacy information storage unit

Claims (18)

A process for evaluating a user's current daily life based on sensor information from at least one of a behavior sensor that measures a user's behavior, a state sensor that measures a user's state, and an environment sensor that measures a user's environment. There line, and daily evaluation unit for obtaining information of daily degree is a parameter representing the degree of daily degrees about the current status of the user,
There line processing to evaluate the closeness of presenting candidates to become content to the user, and closeness evaluation unit for obtaining information of closeness is a parameter representing the degree of closeness of the user for the content,
And everyday of the information which is the evaluation result of daily density at the daily value evaluation unit, on the basis of the familiarity of the information which is the evaluation result of the closeness in the closeness evaluation unit, the presentation candidates to the user A content selection unit that performs processing for selecting content to be presented to the user by the content presentation unit;
Based on the acquired sensor information, a situation estimation unit that estimates a user situation;
A primary candidate content extraction unit that extracts content that is a primary candidate from content that is a presentation candidate based on the current location of the user estimated by the situation estimation unit;
Including
The daily life evaluation unit
Based on the user's situation estimated by the situation estimation unit, the user's dailyness is evaluated,
The content selection unit
Based on the dailyness information, which is the evaluation result of the dailyness level, and the familiarity information, which is the evaluation result of the familiarity level, the content is extracted from the primary candidate content extracted by the primary candidate content extraction unit. An information presentation system , wherein content to be presented is selected . In claim 1,
  The primary candidate content extraction unit
  The content related to the current location of the user estimated by the situation estimation unit is extracted as the primary candidate content,
  The intimacy evaluation unit
  An information presentation system for evaluating a closeness of content of a primary candidate that is content related to a user's current location. In claim 1 or 2,
  When the situation estimation unit estimates that the current location of the user is the first location,
  The primary candidate content extraction unit
  Content related to the first location is extracted as primary candidate content;
  The intimacy evaluation unit
  Assessing intimacy for content associated with the first location;
  The daily life evaluation unit
  Assessing the user's everydayness about the first location;
  When the situation estimation unit estimates that the current location of the user is the second location,
  The primary candidate content extraction unit
  Content related to the second location is extracted as primary candidate content;
  The intimacy evaluation unit
  Assessing intimacy for content associated with the second location;
  The daily life evaluation unit
  The information presentation system characterized by evaluating a user's everydayness about the 2nd place. In any one of Claims 1 thru | or 3 ,
Including a history information storage unit that stores history information of a user's situation estimated by the situation estimation unit;
The daily life evaluation unit
Evaluating the user's daily life by performing a comparison process between the history information of the user's situation stored in the history information storage unit and the current situation information of the user estimated by the situation estimation unit; Characteristic information presentation system. In any one of Claims 1 thru | or 4 ,
The situation estimation unit includes a situation identification unit and a situation prediction unit,
The daily life evaluation unit
An information presentation system for evaluating a user's daily life by performing a comparison process between a user situation predicted by the situation prediction unit and an actual situation of the user identified by the situation identification unit . In any one of Claims 1 thru | or 5 ,
The daily life evaluation unit
Evaluating the user's dailyness based on at least the first situation information among a plurality of situation information representing the user's situation,
The intimacy evaluation unit
Assessing user intimacy for content related to the first status information;
The content selection unit
Information for selecting content to be presented to a user by a content presentation unit from content related to the first situation information based on an evaluation result of dailyness and an evaluation result of familiarity Presentation system. In any one of Claims 1 thru | or 6 .
A history information storage unit that stores information on a user's situation history estimated by the situation estimation unit;
A user who has used the first subsystem of the integrated system composed of a plurality of subsystems determines the occurrence of an available event indicating that the user can use the second subsystem. An event determination unit to perform,
A first sensor that is a sensor of the first subsystem when the available event occurs
A history information update unit that further updates the status history information updated by the sensor information from the second sensor based on the sensor information from the second sensor that is the sensor of the second subsystem. An information presentation system characterized by In any one of Claims 1 thru | or 7,
  A content information storage unit for storing meta-information associated with the content;
  A closeness information storage unit for storing closeness information;
  Including
  The content information storage unit
  Storing content category information as the meta information;
  The intimacy information storage unit
  Store intimacy information for content categories,
  The intimacy evaluation unit
  The content category information to be presented is read from the content information storage unit, and the familiarity information for the read category information is read from the familiarity information storage unit, so that the user's familiarity with the content An information presentation system characterized by evaluating A process for evaluating a user's current daily life based on sensor information from at least one of a behavior sensor that measures a user's behavior, a state sensor that measures a user's state, and an environment sensor that measures a user's environment. There line, and daily evaluation unit for obtaining information of daily degree is a parameter representing the degree of daily degrees about the current status of the user,
There line processing to evaluate the closeness of presenting candidates to become content to the user, and closeness evaluation unit for obtaining information of closeness is a parameter representing the degree of closeness of the user for the content,
And everyday of the information which is the evaluation result of daily density at the daily value evaluation unit, on the basis of the familiarity of the information which is the evaluation result of the closeness in the closeness evaluation unit, the presentation candidates to the user A content selection unit that performs processing for selecting content to be presented to the user by the content presentation unit;
A content information storage unit for storing meta-information associated with the content;
A closeness information storage unit for storing closeness information;
Including
The content information storage unit
Storing content category information as the meta information;
The intimacy information storage unit
Store intimacy information for content categories,
The intimacy evaluation unit
The content category information to be presented is read from the content information storage unit, and the familiarity information for the read category information is read from the familiarity information storage unit, so that the user's familiarity with the content An information presentation system characterized by evaluating In any one of Claims 1 thru | or 9 ,
The content selection unit
The information presentation system characterized by selecting the content evaluated as having low familiarity as the user's daily life is evaluated as being high. In any one of Claims 1 thru | or 9 ,
The content selection unit
The information presentation system characterized by selecting the content evaluated as having a high familiarity as the user's everydayness is evaluated as low. In any one of Claims 1 thru | or 11 ,
The intimacy evaluation unit
Evaluate content intimacy based on the user ’s intimacy for the content and the intimacy of others other than the user for the content,
The content selection unit
An information presentation system, wherein content to be presented to a user is selected from content that is a candidate for presentation based on the familiarity of the content evaluated based on the familiarity of the user and others with respect to the content. In any one of Claims 1 to 12 ,
The intimacy evaluation unit
An information presentation system for evaluating a user's intimacy with respect to content based on information on past behavior history of the user related to the content as a presentation candidate. A process for evaluating a user's current daily life based on sensor information from at least one of a behavior sensor that measures a user's behavior, a state sensor that measures a user's state, and an environment sensor that measures a user's environment. There line, and daily evaluation unit for obtaining information of daily degree is a parameter representing the degree of daily degrees about the current status of the user,
There line processing to evaluate the closeness of presenting candidates to become content to the user, and closeness evaluation unit for obtaining information of closeness is a parameter representing the degree of closeness of the user for the content,
And everyday of the information which is the evaluation result of daily density at the daily value evaluation unit, on the basis of the familiarity of the information which is the evaluation result of the closeness in the closeness evaluation unit, the presentation candidates to the user A content selection unit that performs processing for selecting content to be presented to the user by the content presentation unit;
Based on the acquired sensor information, a situation estimation unit that estimates a user situation;
Based on the current location of the user estimated by the situation estimation unit, as a primary candidate content extraction unit that extracts the content as the primary candidate from the content as the presentation candidate,
Make the computer work ,
The daily life evaluation unit
Based on the user's situation estimated by the situation estimation unit, the user's dailyness is evaluated,
The content selection unit
Based on the dailyness information, which is the evaluation result of the dailyness level, and the familiarity information, which is the evaluation result of the familiarity level, the content is extracted from the primary candidate content extracted by the primary candidate content extraction unit. A program for selecting content to be presented to a program. A process for evaluating a user's current daily life based on sensor information from at least one of a behavior sensor that measures a user's behavior, a state sensor that measures a user's state, and an environment sensor that measures a user's environment. There line, and daily evaluation unit for obtaining information of daily degree is a parameter representing the degree of daily degrees about the current status of the user,
There line processing to evaluate the closeness of presenting candidates to become content to the user, and closeness evaluation unit for obtaining information of closeness is a parameter representing the degree of closeness of the user for the content,
And everyday of the information which is the evaluation result of daily density at the daily value evaluation unit, on the basis of the familiarity of the information which is the evaluation result of the closeness in the closeness evaluation unit, the presentation candidates to the user A content selection unit that performs processing for selecting content to be presented to the user by the content presentation unit;
A content information storage unit for storing meta-information associated with the content;
As an intimacy information storage unit for storing intimacy information,
Make the computer work ,
The content information storage unit
Storing content category information as the meta information;
The intimacy information storage unit
Store intimacy information for content categories,
The intimacy evaluation unit
The content category information to be presented is read from the content information storage unit, and the familiarity information for the read category information is read from the familiarity information storage unit, so that the user's familiarity with the content A program characterized by evaluating A computer-readable information storage medium, wherein the program according to claim 14 or 15 is stored. A process for evaluating a user's current daily life based on sensor information from at least one of a behavior sensor that measures a user's behavior, a state sensor that measures a user's state, and an environment sensor that measures a user's environment. To obtain dailyness information, which is a parameter representing the degree of everydayness of the user's current situation,
  Perform processing to evaluate the intimacy of the content that is a candidate for presentation to the user, and obtain intimacy information that is a parameter indicating the degree of intimacy of the user for the content,
  Based on the dailyness information that is the evaluation result of the dailyness level and the familiarity information that is the evaluation result of the familiarity level, the content presenting unit presents the content that is a candidate for presentation to the user to the user. Process to select the content to be
  Based on the acquired sensor information, the user's situation is estimated,
  Based on the current location of the user estimated as the user's situation, the content that is the primary candidate is extracted from the content that is the presentation candidate,
  Based on the estimated user situation, evaluate the user ’s daily life,
  A content to be presented to the user is selected from the extracted contents of the primary candidate based on the dailyness information that is the evaluation result of the dailyness and the familiarity information that is the evaluation result of the familiarity. That information presentation system control method. A process for evaluating a user's current daily life based on sensor information from at least one of a behavior sensor that measures a user's behavior, a state sensor that measures a user's state, and an environment sensor that measures a user's environment. To obtain dailyness information, which is a parameter representing the degree of everydayness of the user's current situation,
  Perform processing to evaluate the intimacy of the content that is a candidate for presentation to the user, and obtain intimacy information that is a parameter indicating the degree of intimacy of the user for the content,
  Based on the dailyness information that is the evaluation result of the dailyness level and the familiarity information that is the evaluation result of the familiarity level, the content presenting unit presents the content that is a candidate for presentation to the user to the user. Process to select the content to be
  Store content category information as meta information associated with the content in the content information storage unit,
  Store the intimacy information for the content category in the intimacy information storage unit,
  The content category information to be presented is read from the content information storage unit, and the familiarity information for the read category information is read from the familiarity information storage unit, so that the user's familiarity with the content A method for controlling an information presentation system, characterized in that

Images