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 .
DETAILED ACTION
This Office Action is responsive to the RCE filed on 11/11/2025. Claims 1-5, 7-13, and 15-16 is/are pending for examination.
Response to Amendment
Applicant has amended claims 1, and 9; claims 6, and 14 is/are cancelled; and claims 1-5, 7-13 and 15-16 are pending.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/11/2025 has been entered.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-5, 7-13, and 15-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 1: The term "Quality of Experience QoE" in line 9 is a relative term which renders the claim indefinite. The term "Quality of Experience QoE" is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, it’s unclear how one can predict “user’s QoE” because of its subjective nature, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Claim 9: The term "Quality of Experience QoE" in line 8 is a relative term which renders the claim indefinite. The term "Quality of Experience QoE" is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, it’s unclear how one can predict “user’s QoE” because of its subjective nature, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Claim 10: The term "biasing factor" in line 2 is a relative term which renders the claim indefinite. The term "biasing factor" is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Claim 11: The term "negative occurrences" in line 2 is a relative term which renders the claim indefinite. The term "negative occurrences" is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The dependent claims included in the statement of rejection but not specifically addressed in the body of the rejection have inherited the deficiencies of their parent claim and have not resolved the deficiencies. Therefore, they are rejected based on the same rationale as applied to their parent claims above.
Response to Arguments
Applicant's remarks, see pages 5-7, filed on 11/11/2025, with respect to Claim Objections. The Claim Objections to claims 1 and 9 as set forth in the previous Office Action is maintained.
Applicant's arguments, see pages 5-7, filed on 11/11/2025, with respect to Bouraqia have been fully considered but they are not persuasive.
16. In the Remarks, Applicant argued in substance that
(A) Regarding claim 1, applicant submits that digital applications/programs now tend to include different types of content, and can therefore be affected by throughput, latency and the like differently depending on the type of content (within an application) the user is currently reviewing (see for example, at least, paragraphs 33 and 48 of the current specification). Applicant submits that, by determining different weights for different content types provided by a single application, a more complete and accurate Quality of Experience per application can be determined. In particular, Applicant notes that the overall QoE can be based on various factors that affect each content category differently as detailed in at least paragraph 53. The various content category weights and associated QoE can be used to determine an overall application QoE. Applicant submits that this provides a technical solution not suggested or detailed in the cited art (Recited from pages 5-6 of remarks dated 11/11/2025).
Regarding (A), in response to applicant's argument that the current specification [33 and 48], discloses different types of content, and can therefore be affected by throughput, latency and the like differently depending on the type of content, and by determining different weights for different content types provided by a single application, a more complete and accurate Quality of Experience per application can be determined.
Examiner notes: although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). The claims are interpreted under the broadest reasonable interpretations, and the claims make no mention of how quality of experience is defined. The term quality of experience is subjective/relative, it’s unclear how weights of different content categories are determined based on users’ quality of experience. Thus it’s unclear how various content category weights and associated QoE can be used to determine an overall application QoE as presented in A above.
(B) Regarding claim 1, applicant states that Bouraqia teaches away by discloses aspects of video codec, resolution, content of videos, types of videos, instead of content category, and the Bouraqia does not suggest a plurality of content categories of an application traffic flow and determine QoE based on various weights at detailed in the current application.
Regarding (B), claims are interpreted under the broadest reasonable interpretations, Bouraqia does disclose types of contents of video [13342], different types of services and applications [13343], and, correlation between the PSNR and subjective quality would be decreased if the codec type of the video content changes [13344], Pair of videos are presented to the subjects to be compared and then evaluated which one of the pairs has superior quality, and Comparison Category Rating [13343-13344]. Thus Bouraqia, does discloses the claimed invention at B, see Fig 2, Bouraqia discloses the quality of experience for streaming services including comparison/rating of content category.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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) 1-5, 7-13, and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bouraqia et al. (Quality of Experience for Streaming Services: Measurements, Challenges and Insights 2020/01/09) hereinafter “Bouraqia”.
As to claim 1, Bouraqia discloses a system for determining application quality of experience at least one processor configured to execute instructions stored in a memory component wherein the instructions provide for modules (Bouraqia, Abstract [13344, & 53]) comprising: an application module configured to determine an application associated with a traffic flow (Bouraqia [pages 13342-44], discloses wherein any characteristic of a user, system, service, application, or context whose actual state or setting may have influence on the Quality of Experience for the user);
a content module configured to determine a plurality of content categories associated with the application of the traffic flow (Bouraqia [13342-43] discloses types of contents of video, different types of services and applications, and, [13343-13344] correlation between the PSNR and subjective quality would be decreased if the codec type of the video content changes, Pair of videos are presented to the subjects to be compared and then evaluated which one of the pairs has superior quality, and Comparison Category Rating, discloses wherein the quality of experience for streaming services including comparison/rating of content category);
a weighting module configured to determine a weight associated with each of the content categories associated with the application of the traffic flow, wherein determining the weight for each content category is based on a duration of use, timing of use and method of use of content and the end user’s Quality of Experience (QoE) (Bouraqia [13342 to 13346], discloses wherein the Context-related Influencing Factors: are factors that embrace any situation property to describe the user's environment, in terms of physical location and space, including movements within and transitions, temporal, social, people present or involved in the experience, economic, Costs, subscription type, or brand of the service/system, task, and technical characteristics, these factors can occur on different levels/categories, and Bouraqia further teaches the factors that influence the quality of experience/service, is that in order to evaluate the overall service quality, factors that influence the users' perception In particular the Content-related Influencing Factors the information regarding the offered content by the service or application associated, in the case of video, with video format, encoding rate, resolution, duration, motion patterns, type and contents of the video, etc. In further, Bouraqia teaches wherein the video quality metrics like the join time, the buffer ratio, the rate of buffer events, average bit-rate, and rendering quality; along with the prefetching process. Figure 2 is attached below with more details on how certain content categories/types over an application can effect an overall QoE of the traffic flow); and
a processing module configured to determine an application quality of experience score for traffic flow based on the application, content and weighting associated with each content category within the traffic flow ([pages 13343-46], discloses wherein the System-related Influencing Factors: properties and characteristics that define the technically generated quality of a service or an application, and they are associated to media capture, transmission, coding, storage, rendering, and reproduction/display, also to the communication of information itself from content production to the user, and further discloses wherein the value of the service quality, the quality of transmission, the encoded videos in various contents and sizes/categories within the stream/traffic flow for assessing the quality of experience matrix/score). However, Bouraqia is silent on reading experience score of each content. It would have been obvious to one having ordinary skill before the effective filing date of the claimed invention to determine that Bouraqia teaches a system comprising utilizing the properties and characteristics for generating influence factors that are used for determining quality of service for managing media/content transmission, storage and distribution, and additionally can predict precisely the score of the QoE based on the results from the collected dataset, as described by Bouraqia [pages 13342-43, & 45-48], Bouraqia is capable of determining the quality experience score associated with an application by determining the influence factors of an application/service and results from datasets, the motivation would be to obtain a predetermine set of factors/scores for determining traffic flow/transmission rate for an application/service and the dataset is capable of acquiring individual content/video category/type scores for determining quality of experience.
As to claim 2, Bouraqia discloses the system of claim 1 further comprising a biasing factor module configured to determine a biasing factor for the traffic flow, wherein the processing module is configured to update the application quality of experience based on the biasing factor ([pages 13342-43, 45], discloses wherein order to evaluate the overall service quality, factors that influence the users' perception should be determined beforehand, and teaches wherein the bit-rate switching mechanism is executed at the users' side in a wireless network, to elevate the quality of the user and determine the QoE metrics).
As to claim 3, Bouraqia discloses the system of claim 2 wherein the biasing factor module is configured to determine the biasing factor based on the number of negative occurrences within the traffic flow ([pages 13342-43, 45], discloses wherein order to evaluate the overall service quality, factors that influence the users' perception should be determined beforehand, and teaches wherein the QMON is a network-based approach that monitors and estimate the QoE of the transmitted video streaming).
As to claim 4, Bouraqia discloses the system of claim 1 wherein a network Quality of Experience and an end-user Quality of Experience is determined by the processing module based on the application quality of experience score ([pages 13342-43, 45-48], discloses wherein order to evaluate the overall service quality, factors that influence the users' perception should be determined beforehand, and teaches wherein the collected data is analyzed to determine the user's perception under variable network conditions, and further discloses wherein obtaining a predetermine set of factors/scores for determining traffic flow/transmission rate for an application/service and the dataset is capable of acquiring individual content/video category/type scores for determining quality of experience).
As to claim 5, Bouraqia discloses the system of claim 1 further comprising a traffic action module configured to apply policies to the traffic flow based on the quality of experience score ([pages 13343-44, 49-51], discloses wherein to derive an effective the trade-off between the network variations and dynamic videos streaming behavior, they [163] introduce a queue-based model to analyze the video buffer (GI/GI/1 queue) with pq-policy (pausing or continuing the video download) using discrete-time analysis).
As to claim 7, Bouraqia discloses the system of claim 1 wherein the weighting module is configured to adjust the weights based on a user's length of use of each content category ([pages 13343-44, 49], discloses wherein the subjective methods are conducted to obtain information on the quality of multimedia services using opinion scores, while objective methods are used to estimate the network performance using models that approximate the results of subjective quality evaluation, for weighting/defining user satisfaction in the context of real-time video streaming applications, and further teaches wherein the segment/category duration can affect the QoE of the streaming behavior).
As to claim 8, Bouraqia discloses the system of claim 1 wherein the weighting module adjusts the weights periodically based on machine learning ([pages 13343-44, 54-55], discloses wherein the Artificial intelligence and machine learning algorithms have been recently used to measure the QoE objectively or to improve it, wherein the DASH uses machine learning to set the appropriate resolution and/or bit-rate according to the channel state for continuously tracking the QoE and proactively take appropriate actions to keep good user experience by adjusting the bit-rate accordingly).
Claims 9-13, and 15-16 are corresponding method claims that recite similar limitations as of claims 1-5, and 7-8 and do not contain any additional features with respect to novelty and/or inventive steps; therefore, they are rejected under the same rationale.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See Form 892.
Correspondence Information
The examiner also requests, in response to this Office action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line no(s) in the specification and/or drawing figure(s). This will assist the examiner in prosecuting the application. When responding to this office action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections See 37 CFR 1.111(c).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Razu A Miah whose telephone number is (571)270-5433. The examiner can normally be reached on M-F, 9:30-4 EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Wing Chan can be reached on 27493. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RAZU A MIAH/Primary Examiner, Art Unit 2441