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 .
Information Disclosure Statement
The references listed in the Information Disclosure Statement filed on April 14, 2026 have been considered by the examiner (see attached PTO-1449 form).
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.
Claims 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gupta et al. (U.S. Pub. No. 2012/0259945) in view of Yin et al. (U.S. Pub. No. 2017/0026713).
Regarding claim 1, Gupta et al. discloses a computer-implemented method comprising:
determining a preference of a user for a particular video playback characteristic (see paragraphs 0012-0013, 0026-007, 0051; discloses “user expectation and user tolerance level” which are a form of preference for a particular playback characteristic. For example, a user's interest in photography and desire to view a slideshow implies "user expectations for high quality images" (see paragraph 0026). The user's high-speed internet connection and a simple page request implies a "low" tolerance level, meaning a short waiting time (see paragraphs 0027, 0029));
determining, based on the determined preference of the user and for each version of a video, a return of interest (ROI), wherein each version of the video has a particular resolution and bitrate (see paragraphs 0013, 0028, 0051; the quality of service value is considered as return of interest (ROI) and is described as determining a quality of service value based on user expectations and tolerance level. This quality of service value is used to select a "modified version of the content" (see paragraphs 0013, 0030, 0052). The "modified version of the content" can be a different version of multimedia content, such as "video content" (see paragraph 0053). The modifications described include reducing the size of a photograph slideshow (see paragraph 0049) or removing it entirely (see paragraph 0052). This directly corresponds to the concept of different versions of a video with different resolutions and bitrates. The quality of service value acts as a "return of interest" that ranks the different versions of the content);
determining, based on the ROI, a version of the video to provide to a device of the user (see paragraphs 0013, 0030, 0052-0053; a modified version of the content is delivered to the user based on the quality of service value. The examples provided involve modifying or removing a photograph slideshow (see paragraphs 0049, 0052) which is a form of media content); and
providing the corresponding version of the video to the device of the user (see paragraphs 0013, 0030, 0036; deliver a modified version of the content to the user on a user device (see paragraphs 0011, 0052). The delivery of this modified content to the user's device corresponds to providing the version of the video).
However, Gupta is silent as to determining, based on the determined preference of the user and for each version of the multiple version, a return of interest (ROI); determining, based on the ROI, a version of the video from the multiple versions to provide to a device of the user.
Yin discloses determining, based on the determined preference of the user and for each version of the multiple version, a return of interest (ROI) (see paragraphs 0015, 0027-0029);
determining, based on the ROI, a version of the video from the multiple versions to provide to a device of the user (see paragraphs 0027-0029).
It would have been obvious to a skilled artisan before the effective filing date of the claimed invention to modify the system of Gupta with the teachings of Yin et al., the motivation being to maximize user-perceived Quality-of-Experience.
Regarding claim 9, claim 9 is rejected for the same reason set forth in the rejection of claim 1.
Regarding claim 17, claim 17 is rejected for the same reason set forth in the rejection of claim 1.
Regarding claims 2, 10 and 18, Gupta et al. and Yin et al. discloses everything claimed as applied above (see claims 1, 9 and 17). Gupta et al. discloses wherein the preference of the user comprises one of a video quality preference of the user (see paragraphs 0026, 0030; user expectations for high quality images may be implied based on the user's interest in photography and his desire to view a slideshow. Paragraph 0030 discloses how a user may "rather wait longer for the high quality images contained in the original content". This directly discloses a user's preference for high quality. While the example uses images, the document states that media content includes "video content" (see paragraph 0053), so the preference for high-quality images would extend to high-quality video) and
a video smoothness preference of the user (see paragraphs 0027-0028; "user tolerance level" which defines an "accepted latency time for delivered content". It explains that a user with a low tolerance level "would likely not expect to wait long for a simple page to load". "Low user tolerance level" to a "short waiting time" is discloses in paragraph 0028. A short waiting time and a low tolerance for latency are directly equivalent to a preference for "video smoothness," as it implies a desire for a buffer-free and quick-to-start playback experience).
Regarding claims 3, 11 and 19, Gupta et al. and Yin et al. discloses everything claimed as applied above (see claims 2, 10 and 18). Gupta et al. discloses wherein the providing the version of the video is associated with of a content delivery network (CDN) of a video streaming system (see paragraphs 0024, 0031-0032; the system acts as a middleware device, between the end user and the server, and intercepts requests between the two devices. This "middleware device" functions as a Content Delivery Network (CDN) by modifying and delivering content to users).
Regarding claims 5 and 13, Gupta et al. and Yin et al. discloses everything claimed as applied above (see claims 3, 11 and 19). Gupta et al. discloses wherein determining the ROI comprises: determining a resource usage penalty associated with the CDN for transcoding the video and sending the video from the system to the device of the user (see paragraphs 0024, 0031-0032, 0053; the system "modifies the cached content" (paragraph 0032) or requests a server to "send a low resolution copy of the website" (paragraph 0031) to a user to "expedite the delivery of the website" and "gain a faster delivery time due to the smaller transmission size" (paragraph 0032). This modification process is a form of transcoding, as the document explicitly states that one method of modifying media content is "transcoding the content to a lower quality" (paragraph 0053). The decision to send a lower quality, smaller file size version of the content, which requires less bandwidth and processing power from the system, is the functional equivalent of applying a penalty to higher-resource versions of the content. The system prioritizes the "quality of service value" over sending the original, higher-resource-demanding content when a user's tolerance level is low. The document's description of a "middleware device" (paragraph 0024) that caches and delivers content functions as a Content Delivery Network (CDN), as addressed in the rejection for claim 3); and
determining the ROI based on a combination of the quality score, the smoothness penalty, and the resource usage penalty (see paragraphs 0013, 0026-0028, 0031, 0053; the "quality of service value" is "based on user expectations and a user tolerance level" (see paragraphs 0013, 0028). The "user expectations" are a proxy for a quality score (paragraph 0026), and the "user tolerance level" is a proxy for a smoothness penalty (paragraph 0027). The system's decision to modify content to a "lower resolution copy" or "lower quality" to "expedite the delivery" (see paragraphs 0031, 0053), particularly when a user's tolerance is low, demonstrates that the system is balancing the user's desire for quality and smoothness with the system's ability to efficiently deliver the content. This balancing act is the functional equivalent of combining the quality score, smoothness penalty, and a resource usage penalty to determine the final quality of service value (ROI) for a particular version of the content).
Regarding claims 4, 12 and 20, Gupta et al. and Yin et al. discloses everything claimed as applied above (see claims 3, 11 and 19). Gupta et al. discloses wherein determining the ROI of a particular version of the video comprises:
determining a quality score for the version of the video based on the determined preference of the user (see paragraphs 0026; The "user expectations" define "specifications for a modified version of the content". An example is provided where a user's interest in photography and desire to view a slideshow implies "user expectations for high quality images". Paragraph 0053 discloses modifying media content by "transcoding the content to a lower quality". This demonstrates that the system determines a quality score for different versions of the content based on the user's preference for quality);
determining a smoothness penalty for the version of the video based on the determined preference of the user (see paragraphs 0027-0028, 0031-0032; The "user tolerance level" defines an "accepted latency time for delivered content" (see paragraph 0027). A low user tolerance level means the user has a "short waiting time" expectation (see paragraph 0028). The document describes an embodiment where content is modified to a "low resolution" to "expedite the delivery of the website" (see paragraph 0031) and another where a modification is made to "gain a faster delivery time due to the smaller transmission size" (see paragraph 0032). This shows that the system implicitly penalizes versions of content that would lead to a longer waiting time, which is the functional equivalent of a smoothness penalty); and
determining the ROI based on a combination of the quality score and the smoothness penalty (see paragraph 0028; determining the "quality of service value" (considered as ROI) based on a combination of user expectations and user tolerance level. The "quality of service value" is established to "match these user expectations and the user tolerance level" (see paragraph 0028). This shows that the final score is a combination of the user's quality preference (expectations) and their wait time preference (tolerance level)).
Regarding claims 6 and 14, Gupta et al. and Yin et al. discloses everything claimed as applied above (see claims 4 and 12). Gupta et al. discloses wherein determining the quality score comprises determining the quality score based on a linear function or a logarithmic function selected based on the determined user preference and characteristics of the version of the video (see paragraphs 0026, 0028, 0053; the "quality of service value" is "based on user expectations and a user tolerance level". It also states that the quality of service value "may involve any number of variables and/or relations between data" and "may be calculated according to a plurality of methods" to ensure accuracy (see paragraph 0028). Paragraph 0026 and 0053 states that the user expectations define specifications for a modified version of the content" and that "media content includes images, audio content, video content, etc. The characteristics of the content are described in examples such as a "streaming photo slideshow" and "high quality images" (see paragraph 0026). The claim requires using a "linear function or a logarithmic function" selected based on user preference and content characteristics. The '945 reference describes a system that determines a quality of service value based on multiple data points, including user profile and content characteristics. The document's disclosure that the quality of service value can be determined using a "plurality of methods" and "any number of variables and/or relations between data" inherently encompasses the use of a wide range of mathematical functions, including linear and logarithmic functions. A person of ordinary skill in the art would recognize that using a linear or logarithmic function is a well-known method for combining and weighing different variables (user preferences and content characteristics) to arrive at a single quality score).
Regarding claims 7 and 15, Gupta et al. and Yin et al. discloses everything claimed as applied above (see claims 4 and 12). Gupta et al. discloses determining the smoothness penalty comprises determining the smoothness penalty based on the determined user preference and at least one of a wait time before a first frame of the video is played back or a quantity of rebufferings or stalls of the video during a predetermined period of time (see paragraph 0027; a "user tolerance level" that "defines an accepted latency time for delivered content”. A user's tolerance level can be "very low" and that such a user "would likely not expect to wait long for a simple page to load". This "user tolerance level" is a user's preference for a short wait time and is the functional equivalent of a video smoothness preference. The system uses this preference to establish a "quality of service value" (see paragraph 0028). The method of modifying content to "expedite the delivery of the website" (paragraph 0031) or to "gain a faster delivery time" (paragraph 0032) directly addresses the "wait time" before content is delivered to the user and playback begins. Paragraphs 0002, 0012, 0024 discloses maximize user experience and minimize frustration while accessing web content).
Regarding claims 8 and 16, Gupta et al. and Yin et al. discloses everything claimed as applied above (see claims 1 and 9). Gupta et al. discloses wherein determining the preference of the user comprises determining the preference of the user based on a video playback history of the user (see paragraph 0025; user profile is established for users requesting content. This user profile can be comprised of "dynamic information" which is "obtained implicitly by observing usage patterns. The examples of this dynamic information include the user's "time of use, duration of use, frequency of used, frequently (or infrequently) accessed services. These "usage patterns" and "accessed services" are the functional equivalent of a "video playback history" when applied to video content, as disclosed in the document. The reference states that "user expectations and a user tolerance level can be implied from the user profile" (see paragraph 0026). Therefore, the preference of the user is determined based on their video playback history).
Conclusion
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NNENNA EKPO
Primary Examiner
Art Unit 2425
/NNENNA N EKPO/Primary Examiner, Art Unit 2425 July 23, 2026.
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