Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments with respect to claims 1-11 have been considered but are moot because the arguments do not apply to the new rejection made below.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 6-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chang (US 10061977) in view of Schmelzer (US 20150356121.)
Regarding claim 1, “An information processing apparatus comprising: a processor; and a memory connected to or built in the processor” Chang teaches (Fig. 1 and 3:23-44) a system with a set of executable software instructions and the corresponding hardware (e.g., memory and processor) for executing the instructions.
As to “wherein the processor acquires an image captured by a user via a handheld camera” Chang teaches (2:42-50) a social messaging application (e.g., SNAPCHAT®) executing on user's mobile computer devices that is designed to capture images taken by the device may be used with a mood detection system for determining a mood of a group. In a social messaging application, a user captures an image (e.g., a still image, animated image, video, or the like, via an image sensor of the user device); (2:51-56) image is a selfie/of the user’s face.
As to “during a target event for which a satisfaction level of the user is measured” Chang teaches (2:57-67) technical advances in facial recognition make it possible for a mood detection system such as mood detection system 160 of FIG. 1 to determine an emotion of a user using an image of the user's face. Such a mood detection system 160 may also determine a level of the emotion. For example, a happiness rating may be from 0 to 5 and the mood detection system 160 could determine that one user in an image has a happiness rating of 2 while another user in the image has a happiness rating of 4; (3:1-9) the mood detection system 160 determines an event where the users are located and assembles the messages that originate with users who are at the event. The mood detection system 160 analyzes the various faces in the images and aggregates the resulting emotions to determine an aggregate mood; (Fig. 9 and 11:58-12:2) scale of whether a user is sad/happy, bored/excited, disinterested/engaged.
As to “an event ID of the target event,” Chang teaches (4:57-67) mood detection system 160 identifies an event; (5:20-43) the event module 220 identifies an event…The request includes an event identifier, description, location, start time, duration, or other relevant information to identify the event. In response to receiving the request, the event module 220 identifies the event based on information included in the request; (5:44-50) geolocation to identify the event;
As to “derives the satisfaction level of the user with the target event based on the image” Chang teaches Chang teaches (2:57-67) technical advances in facial recognition make it possible for a mood detection system such as mood detection system 160 of FIG. 1 to determine an emotion of a user using an image of the user's face.
As to “and presents an attribute of the user and satisfaction level-related information which is related to the satisfaction level to an organizer of the target event.” Chang teaches (5:20-37) a host, producer, or other responsible entity transmits a request to monitor an event to the event module 220; (9:57-61) the mood module 260 transmits the aggregate mood level to a host for the event. The mood module 260 may also include any and/or all graphical representation of the mood level as generated by the graphic module 280; (Fig. 10 and 12:8-24) The graphic module 280 generates distinct graphical charts 1000 (that depict mood level) for each of the demographical groups.
Chang does not teach “being registered in accessory information of the image captured by the user.” However, Schmelzer teaches (¶0005) Images may also be encoded by other metadata such as an event ID, event name and description, etc. to further facilitate classification and retrieval of the images. Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the system as taught by Chang with the encoding of event ID as taught by Schmelzer for the benefit of making it easier to organize, search, retrieve, and share said images.
Regarding claim 6, “The information processing apparatus according to claim 1, wherein the processor presents information in which the satisfaction level and the attribute of the user are associated with each other, as the satisfaction level-related information.” Chang teaches (Fig. 10) demographic groups with satisfaction levels.
Regarding claim 7, “The information processing apparatus according to claim 1, wherein the processor derives the satisfaction level based on a condition related to an image-related evaluation value, which is at least any one of the number of the captured images, the number of times of reproduction of the image, or the number of posts of the image.” Chang teaches (5:37-43) identifying an event based on a threshold number of users having transmitted messages from the location of the event; (11:49-57) for each hour the social messaging system receives 100 or more messages from attendees of the event, the mood module continues to track the mood level
Regarding claim 8, “The information processing apparatus according to claim 1, wherein the processor derives the satisfaction level based on an analysis result of an expression of a person appearing in the image.” Chang teaches (2:57-3:9 and 7:59-8:20) based on facial expression.
Regarding claim 9, “The information processing apparatus according to claim 1, wherein the processor derives the satisfaction level for at least any one of an imaging location or an imaging time slot of the image in the target event.” Chang teaches (5:37-50) based on location; (Fig. 8 and 11:43-48) over a period of time of the event.
Regarding claim 10, its rejection is similar to claim 1.
Regarding claim 11, its rejection is similar to claim 1.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chang and Schmelzer in view of Fisher et al. (US 20120233000, hereinafter Fisher.)
Regarding claim 2, Chang and Schmelzer do not teach “The information processing apparatus according to claim 1 wherein the processor derives a specific attribute, which is an attribute of a user who tends to prefer the target event among the users who participate in the target event, by statistically analyzing the satisfaction level, and presents the specific attribute as the satisfaction level-related information.” However, Fisher teaches (¶0052) a method of collecting data communicated in real time from image capture devices used by a plurality of observers that focus on a person or object at an event; determining levels of interest in the person or object during the event by processing the collected data; and auctioning portions of the event to advertising bidders in real time, as the event is in progress, based upon the level of interest statistically determined from the data obtained from the plurality of image capture devices. The level of interest can also be determined from the number of images captured of a particular person or object at the event; (¶0095) The larger the number of observers at an event and the larger the sample size, the more accurate the determination(s) of relevancy, and the ability to extrapolate the relevance and level of interest to other populations such as consumers to determine demographics. For example, crowd focus can show that a particular entertainer holds more interest for a given population that can then be used for product promotions to that population. Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the system that determines a level of interest during a live event as taught by Chang and Schmelzer with the demographic targeting as taught by Fisher for the benefit of better providing content and products for the target audience.
Claim(s) 3-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chang, Schmelzer, and Fisher in view of Tischer et al. (US 20070271580, hereinafter Tischer.)
Regarding claim 3, Chang, Schmelzer, and Fisher do not teach “The information processing apparatus according to claim 2, wherein the processor performs heavier weighting in a case of deriving the specific attribute on an attribute of the user having a higher satisfaction level.” However, Tischer teaches (¶0053, Fig. 13-14) an audience member who supplies information at Block 340 may have a heightened interest in the content that is displayed on the content presentation system. This audience member's demographics may, therefore, be given greater weight than the unknown audience member; (¶0118) attentiveness involves a retinal scan to determine an interest level; (¶0104, ¶0106-¶0107, Fig. 13-14) the attentiveness of various individual audience members may be classified as being high or low, and the content presentation device may be controlled based strongly on the audience members having relatively high attentiveness and based weakly on the audience members having low attentiveness. Stated differently, the demographics and/or preferences of those audience members having relatively low attentiveness may be given little or no weight in controlling the content. In still other embodiments, the demographics of the plurality of unknown members may be weighted differently based on the individual attentiveness of the plurality of unknown audience members. Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the system that determines a level of interest during a live event as taught by Chang, Schmelzer, and Fisher with the heavier weighting as taught by Tischer for the benefit of better catering the content towards the engaged audience.
Regarding claim 4, “The information processing apparatus according to claim 2, to wherein the processor presents, in addition to the specific attribute, a set attribute, which is an attribute of the user set by the organizer in the target event, as the satisfaction level-related information.” Chang teaches (12:8-24) taking into account the user’s demographics.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chang and Schmelzer in view of Roberts et al. (US 20080155588, hereinafter Roberts.)
Regarding claim 5, “The information processing apparatus according to claim 1, wherein the processor derives a first representative satisfaction level, which represents the satisfaction levels of all the users who participate in the target event, and a second representative satisfaction level, which represents the satisfaction level of a user having a set attribute set by the organizer in the target event among the users who participate in the target event” Chang teaches (Fig. 9, 11:58-12:2, Fig. 10, 12:8-24) aggregate group sentiment and group sentiment based on demographic groups.
Chang and Schmelzer do not teach“and presents a notification prompting to change the set attribute to the organizer in a case in which the second representative satisfaction level is lower than the first representative satisfaction level, and an absolute value of a difference between the first representative satisfaction level and the second representative satisfaction level satisfies a threshold value condition set in advance.” However, Roberts teaches (¶0121) the user demographics of actual consumers of media content may be used to qualify media content attribute data (e.g., intended audience) provided by a content producer 125. In some cases, for example, the actual consumer demographic information can be given more weight than the user-provided target audience data. This can improve the accuracy of the system 100 by self-correcting user-provided data that turns out not to be accurate. For example, a content producer 125 may believe that a particular one of his media content instances is targeted to a first demographic of consumers 135, but actual requests for the media content instance may indicate that a second demographic of consumers 135 is more interested in the media content instance. With the demographic data for the actual consumers 135 of the media content instance, the content host subsystem 110 may account for actual distribution patterns and associated demographic data when matching advertising content to the media content instance. Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the system that determines a level of interest during a live event as taught by Chang and Schmelzer with the demographic correction as taught by Roberts for the benefit of better knowing the target audience thus catering future content towards the engaged audience demographic.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Gauglitz et al. (US 20170221095) – (abstract) an instance of a software application is installed which monitors the current location of the user, prompts the user to check into events present in the event database when the user enters a geofence associated with an event within the temporal window associated with the event, associates, with one of the plurality of events, media which was captured by the user while the user was checked into the one of the plurality of events and within the temporal window and geofence associated with the one of the plurality of events, and uploads the captured media to the server.
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/Frank Johnson/Primary Examiner, Art Unit 2425
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