DETAILED ACTION
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 .
Claim Rejections – 35 U.S.C. § 101
35 U.S.C. § 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed
to non-statutory subject matter. The claims, 1-20 are directed to a judicial exception (i.e., law of nature, natural phenomenon, abstract idea) without providing significantly more.
Step 1
Step 1 of the subject matter eligibility analysis per MPEP § 2106.03, required the claims to be a process, machine, manufacture or a composition of matter. Claims 1-20 are directed to a process (method), machine (system), and product/article of manufacture, which are statutory categories of invention.
Step 2A
Claims 1-20 are directed to abstract ideas, as explained below.
Prong one of the Step 2A analysis requires identifying the specific limitation(s) in the claim under examination that the examiner believes recites an abstract idea, and determining whether the identified limitation(s) falls within at least one of the groupings of abstract ideas of mathematical concepts, mental processes, and certain methods of organizing human activity.
Step 2A-Prong 1
The claims recite the following limitations that are directed to abstract ideas, which can be summarized as being directed to a method, the abstract idea, of tracking and verifying otherwise anonymous website visitors to gather data on user behavior, preferences, and demographics.
Claim 1 discloses a method, comprising: A method of correlating anonymous customer information, comprising:
receiving a packet including:
customer data and customer interaction information, (following rules or
instructions, observation, evaluation, judgement, opinion),
creating an image of the customer; (following rules or instructions, observation,
evaluation, judgement, opinion),
noting the voice of the customer; (following rules or instructions,
observation, evaluation, judgement, opinion),
performing a comparison of the visual and listening with the
customer information and interaction information; (following rules or instructions, observation, evaluation, judgement, opinion), and
performing an action with the customer interaction information based on the
comparison, (following rules or instructions, observation, evaluation, judgement, opinion).
Additional limitations employ the method to identify an item viewed by
the customer, (following rules or instructions, observation, evaluation, judgement, opinion – claim 2), displaying the item, (following rules or instructions, observation, evaluation, judgement, opinion - claim 3), indicating the item to a user, (following rules or instructions, observation, evaluation, judgement, opinion – claim 4), generating a first and second understanding of data and performing a comparison, (following rules or instructions, observation, evaluation, judgement, opinion – claim 5), using a Euclidean distance to measure the comparison, (mathematical concepts, formulas or equations, mental processes, evaluation, opinion, - claim 6), where the action is based on the distance being below a threshold, (following rules or instructions, observation, evaluation, judgement, opinion – claim 7).
Each of these claimed limitations employ: organizing human activity in the form of following rules or instructions, performing mental processes including, observation, evaluation, judgement, and opinion; and applying mathematical concepts using mathematical formulas, equations, or calculations.
Claims 8-20 recite similar abstract ideas as those identified with respect to claims 1-7.
Thus, the concepts set forth in claims 1-20 recite abstract ideas.
Step 2A-Prong 2
As per MPEP § 2106.04, while the claims 1-20 recite additional limitations which are hardware or software elements such as, a sensor, from at least one of a microphone or a camera, an image, and audio recording, a display, a mobile device, a neural network, a memory storing processor executable instructions, one or more processors, an embedding, and a non-transitory machine-readable medium.
These limitations are sufficient to qualify as a practical application, (MPEP § 2106.05 (f) & (h)).
The claimed invention integrates the abstract idea of tracking and verifying otherwise anonymous website visitors to gather data on user behavior, the verification achieved through additional elements of a camera and audio recording capabilities capturing data and a neural network performing analysis and identification matching. The ordered combination of limitations adds machine driven verification through the additional sensors comparing new data with existing packet information. This adds a degree of analysis and decision in a time window narrow enough to enable the opportunity to take additional actions to better the user/customer experience.
Since the limitations in the claims 1-20 present a practical application of the exception, they translate the described invention into a patent eligible application, thus the claims are directed to statutory subject matter and are not rejected under 35 U.S.C. § 101.
Claim Rejections 35 U.S.C. §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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-4, 8-11, 15-18 are rejected under 35 U.S.C. § 103 as being taught by Chourey (US 20140074550 A1) hereafter Chourey, “Augmenting Progressive Profile States with External Data sources,” in view of Naor, (US 20120278176 A1), hereafter Naor, “Systems and Methods Utilizing Facial Recognition and Social Network Information Associated with Potential Customers,” in further view of Connolly, (US 20150350435 A1), hereafter Connolly, “System and Method for Bridging Online Customer Experience, in further view of Hurewitz, (US 20140363059A1), hereafter Hurewitz, “Retail Customer Service Interaction System and Method.”
Regarding Claim 1, A method of correlating anonymous customer information, Chourey teaches, (actions by the visitor and how those actions correlate with the interests of the visitor, [0060], the visitor may be classified as an anonymous visitor, [0044]), comprising:
receiving a packet (receiving a transmission that includes information provided by a remotely-located external data source, [Abstract]), including:
customer sensor data from at least one of a microphone or a camera, Chourey does not teach, Naor teaches, (The system 100 includes a sales engine 110 that may establish a connection with a potential customer via a remote customer device 120, [ ], the remote customer device 120 includes a camera adapted to capture an image (e.g., an image of the potential customer), [0016]), and
customer interaction information, (To facilitate selection of appropriate offers, CRM systems and applications may be used to track prior interactions with the customer, Naor, [0015]),
capturing an image of a customer; (image information associated with the online connection is captured, the image information including the potential customer's face, [0022],
Chourey and Naor are both considered to be analogous to the claimed invention because they are both in the field of customer interaction analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the anonymous customer data collection sources of Chourey with the image collection techniques of Naor to ensure the customer can be automatically identified based at least in part on the collected social network information, [ ] and customer relationship management information may also be used to identify an offer, [Abstract].
capturing an audio recording of the customer; Chourey does not teach, Connolly teaches, (if a conversation between the customer and agent is to be recorded, the call may traverse the media server so that the customer and agent may engage in a three-way conversation with the media server, and the media server may record the conversation and store the recorded conversation in a database, [0084]),
Chourey and Connolly are both considered to be analogous to the claimed invention because they are both in the field of customer interaction analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the anonymous customer data collection sources of Chourey with the audio collection techniques of Connolly to allows a single view of interactions across retail store and contact center for quality control, cause/effect analysis, performance evaluations, and the like, [0143].
performing a comparison of the image and the audio recording with the customer
sensor data; Chourey does not teach, Hurewitz teaches, (Sensors 170 may take the form of visual or infrared cameras that view different areas of the retail store space 101. Computers could analyze those images to locate individual customers 134, 135. Sophisticated algorithms on those computers could distinguish between individual customers 134, 135, using techniques such as facial recognition. [0028], a "gesture" gesture is generally considered to be a body movement that constitutes a command for a computer to perform an action. In the system 200, sensors 246 capture raw data relating to motion, heat, light, or sound, etc. created by a customer 135 or clerk 137. [ ] As used herein, a "gesture" could also include an audio capture such as a voice command, or a data input received by sensors, such as facial recognition. [0045]. The programming 750 is responsible for ensuring that the processor 710 performs several important processes on the data received from the sensors 170. In particular, programming 752 instructs the processor 710 how to track a single customer 134 based on characteristics received from the sensors 170. The ability to track the customer the customer 134 requires that the processor 710 not only detect the presence of the customer 134, but also assign unique parameters to that customer 134. These parameters allow the store sensor server to distinguish the customer 134 from other customers 135, recognize the customer 134 in the future, and compare the tracked customer 134 to customers that have been previously identified. [ ] Once the characteristics are defined by programming 752, they can be compared to characteristics 772 of profiles that already exist in the database 770. If there is a match to an existing profile, the customer 134 identified by programming 752 will be associated with that existing profile in database 770, [0065]),
Chourey and Hurewitz are both considered to be analogous to the claimed invention because they are both in the field of customer interaction analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the anonymous customer data collection sources of Chourey with the multimedia data collection techniques of Hurewitz to assist the clerk 137 in their interaction with the customer 135, and
performing an action with the customer interaction information based on the
comparison. Chourey does not teach, Naor teaches, (an offer to be provided to the potential customer may be "automatically" identified based at least in part on the collected social network information. As used herein, the term "automated" may refer to, for example, actions that can be performed with little or no human intervention. Note that the offer may be selected from a plurality of potential offers by a sales engine or by another device, [0034].
Chourey and Naor are both considered to be analogous to the claimed invention because they are both in the field of customer interaction analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the anonymous customer data collection sources of Chourey with the image collection techniques of Naor so the customer can be automatically identified based at least in part on the collected social network information, [ ] and customer relationship management information may also be used to identify an offer, [Abstract].
Regarding Claim 2, The method of claim 1, wherein the customer interaction information includes an identifier of an item viewed by the customer. Chourey teaches, (The lead management system 120 may include the interaction gathering engine 220 that monitors the behavior a visitor 158 on the website, 150 and records information about the visitor 158, [0032], a resource portfolio may be an area where highly targeted content can be saved and viewed by the visitor, and it is stored in association with the user profile of the visitor. [ ] It may also include content that is related to content that the visitor has saved and/or viewed, [0108]).
Regarding claim 3, The method of claim 2, wherein the action includes displaying the item via a display. Chourey teaches, (Featured solutions, articles, and/or marketing videos may also be dynamically displayed based on the interests and/or profile of the visitor. As the interests of a visitor are identified, the website may dynamically display content that is tagged with the interests of the visitor, [0101], and thus, the visitor may be presented with content and layouts that are of interest to the visitor without the visitor needed to take any action other than to visit the website, [0103]).
Regarding claim 4, The method of claim 2, wherein the action includes indicating the item to a user via a mobile device. Chourey does not teach, Connolly teaches, (Embodiments of the present invention are also directed to a retail application that is run on an end user device, [ ], the end user device may be a computer, laptop, table, smart phone, kiosk terminal, and/or the like, [0124], FIG. 10 is an exemplary screen shot of a GUI displayed by the retail application for recommending an upsell item to a customer based on analysis performed by the analytics module according to one embodiment of the invention. The upsell script and/or item 350a-d may be dynamically modified and pushed to the retail application in real time, [0148]).
Chourey and Connolly are both considered to be analogous to the claimed invention because they are both in the field of customer interaction analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the anonymous customer data collection sources of Chourey with the retail application of Connolly to enable real-time analytics of the CX data and recommendations to be made in real-time to the retail stores via the retail applications for optimizing performance at the retail stores, [0147].
Claims 8-11, 15-18 are rejected for reasons corresponding to claims 1-4. The addition of a system comprising a memory and one or more processors, claims 8-11, and the addition of a non-transitory machine-readable medium, claims 15-18, does not change the rational for the rejections under 35 U.S.C § 103 or the referenced prior art. Chourey teaches, computer 1002 may include one or more processors 1160 that communicate with a number of peripheral devices via a bus subsystem 1190. These peripheral devices may include user output device(s) 1130, user input device(s) 1140, communications interface 1150, and a storage subsystem, such as random-access memory (RAM) 1170 and non-volatile storage drive 1180 (e.g., disk drive, optical drive, solid state drive), which are forms of tangible computer-readable memory, [0119].
Claims 5-7, 12-14, 19-20 are rejected under 35 U.S.C. § 103 as being taught by Chourey (US 20140074550 A1) hereafter Chourey, “Augmenting Progressive Profile States with External Data sources,” in view of Naor, (US 20120278176 A1), hereafter Naor, “Systems and Methods Utilizing Facial Recognition and Social Network Information Associated with Potential Customers,” in further view of Connolly, (US 20150350435 A1), hereafter Connolly, “System and Method for Bridging Online Customer Experience, in further view of Hurewitz, (US 20140363059A1), hereafter Hurewitz, “Retail Customer Service Interaction System and Method,” in further view of Evans, (US10832062B1), hereafter Evans, “Image Embedding for Object Tracking.”
Regarding claim 5, The method of claim 1, wherein the performing the comparison includes:
generating a first embedding of the sensor data from the camera via a neural network;
generating a second embedding of the image of the customer via the neural network; and
performing a comparison between the first embedding and the second embedding.
Chourey does not teach, Evans teaches, (the object identifying and/or matching component(s) 116 may determine, based at least in part on the image embeddings 114 output from the neural network 112,an identity of one or more objects (e.g., a unique identifier for a particular object). Additionally, or alternatively, the object identifying and/or matching component(s) 116 may determine, based at least in part on the image embeddings 114 output from the neural network 112, whether an object matches another object. For example, the object identifying and/or matching component(s) 116 may determine that distances between the points associated with the image patches 120 at T1, T2, and T3 (the first point, the second point, and the third point, respectively) may satisfy a threshold distance (e.g., a distance that is close to, or equal to, zero). Furthermore, the object identifying and/or matching component(s) 116 may determine, based at least in part on the distances satisfying the threshold distance, that object detections associated with the image patches 120 at T1, T2, and T3 are associated with a same object (e.g., the other vehicle 122), Evans, [5:39-58]).
Chourey and Evans are both considered to be analogous to the claimed invention because they are both in the field of applied sensor data analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the anonymous customer data collection sources of Chourey with the embedding techniques and automated object analysis of Evans to enable object identification, matching, classification and tracking, [Abstract].
Regarding claim 6, The method of claim 5, wherein the comparison includes computing the Euclidean distance between vectors. Chourey does not teach, Evans teaches, (In some examples, the object identifying and/or matching component(s) 116 may determine that a distance between the first point and the second point may satisfy a threshold distance (e.g., a distance that is close to, or equal to, zero). Furthermore, the object identifying and/or matching component(s) 116 may determine, based at least in part on the distance satisfying the threshold distance, that object detections associated with the image patches 120 match. That is, the object identifying and/or matching component(s) 116 may determine that object detections associated with the image patches120 (produced from the image 118 captured via the first image sensor and the image 118 captured via the second image sensor) are associated with a same object (e.g., the other vehicle 122), Evans, [6:54-7:1].
Chourey and Evans are both considered to be analogous to the claimed invention because they are both in the field of applied sensor data analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the anonymous customer data collection sources of Chourey with the embedding techniques and automated object analysis of Evans to enable object identification, matching, classification and tracking, [Abstract].
Regarding claim 7, The method of claim 5, wherein the performing the action is based on the distance being below a threshold. Chourey teaches, (Crossing a threshold in the positive direction may indicate that the visitor is expressing increased interest in the website, while crossing a threshold in the negative direction may indicate that the visitor is losing interest in the website. In either case, the website may need to show content that is more targeted towards the interests of the visitor, or the website may need to show content that is more varied in order to find something that the visitor is more interested in viewing. In some embodiments, a threshold score may be determined, which when crossed, may designate the visitor as a qualified lead, i.e., a lead that is ready for more aggressive and/or direct contact with a sales department associated with the website. When the lead score of the visitor indicates a qualified lead, the WCMS may be programmed to alert the sales department, to present purchasing opportunities to the visitor, or to take any other action that may be calculated to follow up the expressed interest of the visitor with a sales opportunity, [0059]).
Claims 12-14 and 19-20 are rejected for reasons corresponding to claims 1-4. The addition of a system comprising a memory and one or more processors, claims 8-11, and the addition of a non-transitory machine-readable medium, claims 15-18, does not change the rational for the rejections under 35 U.S.C § 103 or the referenced prior art. Chourey teaches, computer 1002 may include one or more processors 1160 that communicate with a number of peripheral devices via a bus subsystem 1190. These peripheral devices may include user output device(s) 1130, user input device(s) 1140, communications interface 1150, and a storage subsystem, such as random-access memory (RAM) 1170 and non-volatile storage drive 1180 (e.g., disk drive, optical drive, solid state drive), which are forms of tangible computer-readable memory, [0119].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure or directed to the state of the art is listed on the enclosed PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL BOROWSKI whose telephone number is (703) 756-1822. The examiner can normally be reached M-F 8-4:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O’Connor can be reached on (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/MB/
Patent Examiner, Art Unit 3624
/MEHMET YESILDAG/Primary Examiner, Art Unit 3624