DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 06/08/2026 has been entered.
Response to Arguments
Applicant's arguments with respect to the rejections of claims 34-51 and 53 have been considered but are moot in view of new grounds of rejection.
Response to Amendment
Double Patenting
4. Claims 34-35, 38-45, and 48-51 and 53 are rejected under the judicially created doctrine of obviousness-type double patenting as being unpatentable over claims 1-18 of U.S. Patent No. 11,276,434 in view of Chen et al. (US Publication 2016/0029106) and further in view of Liu et al. (US Patent 11,694,726) and Tian et al. (English Translation of Chinese Publication CN110347872 2019).
Claim 34 of the instant application comprises elements that are not patentably distinct from claim 1 of patent no. 11,276,434, except for:
receiving a request from a user to interact with a content platform, wherein the user is associated with a user profile on the content platform;
automatically initiating a process for generating a personalized trailer of a video content item, the process comprising:
retrieving preferences of the user profile stored in a user profile database;
selecting a subset of segments of the plurality of segments having metadata that matches one or more of the retrieved preferences;
transmitting the personalized trailer of the video content item for display to a device of the use.
Chen discloses:
retrieving preferences of the user profile stored in a user profile database (Chen, para. 0034, receiving user input for selecting parameters for generating pictorial summary of the video; parameters can be fixed, i.e., stored in a file or database, and not required selection by a user; para’s 0039-0042, parameters used in scene weighting may include a name of a primary character “James Bond”, a list of highlight actions or objects (for example, the user may principally be interested in the car chases in a movie), parameters used in evaluating pictures in the video, such as, for example, parameters selecting a measure of picture quality, and/or parameters used in selecting pictures from a scene for inclusion in the pictorial summary, such as, for example, a number of pictures to be selected per shot. to emphasize in the weighting; para’s 0148-0151, accessing and retrieving one or more parameters from a configuration guide that includes one or more parameters for configuring a pictorial summary of a video; generating, for the video, a pictorial summary based on the accessed/retrieved parameter In at least one implementation, wherein the pictorial summary conforms to “matches” one or more accessed parameters from the configuration guide);
selecting a subset of segments of the plurality of segments having metadata that matches one or more of the retrieved preferences (Chen, para’s 0148-0151, accessing and retrieving one or more parameters from a configuration guide that includes one or more parameters for configuring a pictorial summary of a video; generating, for the video, a pictorial summary based on the accessed/retrieved parameter In at least one implementation, wherein the pictorial summary conforms to “matches” one or more accessed parameters from the configuration guide; para’s 0188-0197, at least one evaluation and selection system includes the functions of evaluating pictures in a video and selecting certain pictures, based on the evaluations, to include in a pictorial summary; identifying different levels of importance (weights) to a scene (or other portion of a video) by considering one or more features such as, for example, the scene position within a video, the appearance frequency of main characters, the length of the scene, and the level/amount of highlighted actions or objects in the scene, considering factors related to how “interesting” a scene, a shot, or a picture is, when determining a weight or ranking, such as, for example, by considering the presence of highlight actions/words and the presence of main characters, and/or using one or more of the following factors in a hierarchical process that analyzes scenes, shots, and individual pictures in generating a pictorial summary: (i) favoring the start scene and the end scene, (ii) the appearance frequency of the main characters, (iii) the length of the scene, (iv) the level of highlighted actions or objects in the scene, or (v) an “appealing quality” factor for a picture);
transmitting the personalized trailer of the video content item for display to a device of the user (Chen, para. 0100, providing the highlight video “trailer” to the user who provides user input as parameter).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Chen’s features into the invention of patent no. 11,276,434 for enhancing user’s playback experience by providing user a video trailer comprising content that matches user profile.
Patent No. 11,276,434 in view of Chen does not explicitly disclose:
automatically initiating a process for generating a personalized trailer of a video content item;
retrieving, from a data structure, data indicative of a template specifying a preferred order of segments for trailers of video content; determining an order of the selected subset of segments based at least in part on the preferred order of segments specified by the template; and generating the personalized trailer of the video content by arranging the selected subsets of segments based at least in part on the determined order.
Liu discloses:
automatically initiating a process for generating a personalized trailer of a video content item (Liu, col. 14, lines 34-36, automatically generating a trailer for a movie).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Liu’s features into the invention of patent no. 11,276,434 in view of Chen for enhancing user’s video viewing experience by automatically providing a personalized video trailer.
Patent No. 11,276,434 in view of Chen-Liu does not explicitly disclose but Tian discloses:
retrieving, from a data structure, data indicative of a template specifying a preferred order of segments for trailers of video content; determining an order of the selected subset of segments based at least in part on the preferred order of segments specified by the template ; and generating the personalized trailer of the video content by arranging the selected subsets of segments based at least in part on the determined order (Tian, para’s 0129-0135, a highlight video “trailer” can be arranged in order of start stage, middle stage, and end stage, i.e., a template; the comprehensive feature information of all the moments is input into the second discriminant mode!, so as to determine the probability value of each moment belonging to the start stage, the end stage, or the middle stage of the highlight clip; since an interval around the starting point of the highlight segment can often also be used as the starting point, the starting phase in this example embodiment may refer to a continuous time interval; wherein, the duration of the starting phase may be a fixed duration, for example, 2 seconds, 3 seconds, etc. can also be determined according to the duration of the highlights, for example, 15 %, 20%, etc. of the duration of the highlights; the same is true for the end stage; wherein the lengths of the beginning stage and the end stage are positively correlated (e.g., proportional) to the length of the middle stage; a plurality of candidate start times and a plurality of candidate end times are determined from each of the times according to each of the probability values. a plurality of candidate segments are determined according to the plurality of candidate start times and candidate end times. In this exemplary embodiment, all candidate start moments and candidate end moments may be combined in pairs to form multiple nominations; then, candidate segments are selected from the multiple nominations. For example, first delete the nominations whose candidate start time is later than the candidate end time; then, sort the remaining nominations according to the scores, and filter the top-ranked (for example, top N) corresponding to the candidate start time and the probability value corresponding to the candidate end time are used to calculate the score of the nomination; the calculation method may be to calculate the product, sum or average value of the two probability values. Candidate segments may also be determined according to other rules, which also belong to the protection scope of the present disclosure. In step 740, each of the candidate segments is evaluated, and the highlight segment and the corresponding second metric value are determined from the plurality of candidate segments according to the evaluation result).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Tian’s features into the invention of Patent No. 11,276,434 in view of Chen-Liu for enhancing user’s playback experience by organizing segments of the trailer according to predetermined rules/template. Using Tian’s rule/temple having a predetermined order, a more personalized trailer of the video content can be generated by arranging the selected subsets of segments in such predetermined order.
5. Claims 34-35, 38-45, and 48-51 and 53 are rejected under the judicially created doctrine of obviousness-type double patenting as being unpatentable over claims 1-9 of U.S. Patent No. 11,972,782 in view of Chen et al. (US Publication 2016/0029106) and further in view of Liu et al. (US Patent 11,694,726) and Tian et al. (English Translation of Chinese Publication CN110347872 2019).
Claim 34 of the instant application comprises elements that are not patentably distinct from claim 1 of patent no. 11,972,782, except for:
receiving a request from a user to interact with a content platform, wherein the user is associated with a user profile on the content platform;
automatically initiating a process for generating a personalized trailer of a video content item, the process comprising:
retrieving preferences of the user profile stored in a user profile database;
selecting a subset of segments of the plurality of segments having metadata that matches one or more of the retrieved preferences;
transmitting the personalized trailer of the video content item for display to a device of the use.
Chen discloses:
retrieving preferences of the user profile stored in a user profile database (Chen, para. 0034, receiving user input for selecting parameters for generating pictorial summary of the video; parameters can be fixed, i.e., stored in a file or database, and not required selection by a user; para’s 0039-0042, parameters used in scene weighting may include a name of a primary character “James Bond”, a list of highlight actions or objects (for example, the user may principally be interested in the car chases in a movie), parameters used in evaluating pictures in the video, such as, for example, parameters selecting a measure of picture quality, and/or parameters used in selecting pictures from a scene for inclusion in the pictorial summary, such as, for example, a number of pictures to be selected per shot. to emphasize in the weighting; para’s 0148-0151, accessing and retrieving one or more parameters from a configuration guide that includes one or more parameters for configuring a pictorial summary of a video; generating, for the video, a pictorial summary based on the accessed/retrieved parameter In at least one implementation, wherein the pictorial summary conforms to “matches” one or more accessed parameters from the configuration guide);
selecting a subset of segments of the plurality of segments having metadata that matches one or more of the retrieved preferences (Chen, para’s 0148-0151, accessing and retrieving one or more parameters from a configuration guide that includes one or more parameters for configuring a pictorial summary of a video; generating, for the video, a pictorial summary based on the accessed/retrieved parameter In at least one implementation, wherein the pictorial summary conforms to “matches” one or more accessed parameters from the configuration guide; para’s 0188-0197, at least one evaluation and selection system includes the functions of evaluating pictures in a video and selecting certain pictures, based on the evaluations, to include in a pictorial summary; identifying different levels of importance (weights) to a scene (or other portion of a video) by considering one or more features such as, for example, the scene position within a video, the appearance frequency of main characters, the length of the scene, and the level/amount of highlighted actions or objects in the scene, considering factors related to how “interesting” a scene, a shot, or a picture is, when determining a weight or ranking, such as, for example, by considering the presence of highlight actions/words and the presence of main characters, and/or using one or more of the following factors in a hierarchical process that analyzes scenes, shots, and individual pictures in generating a pictorial summary: (i) favoring the start scene and the end scene, (ii) the appearance frequency of the main characters, (iii) the length of the scene, (iv) the level of highlighted actions or objects in the scene, or (v) an “appealing quality” factor for a picture);
transmitting the personalized trailer of the video content item for display to a device of the user (Chen, para. 0100, providing the highlight video “trailer” to the user who provides user input as parameter).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Chen’s features into the invention of patent no. 11,972,782 for enhancing user’s playback experience by providing user a video trailer comprising content that matches user profile.
Patent No. 11,972,782 in view of Chen does not explicitly disclose:
automatically initiating a process for generating a personalized trailer of a video content item;
retrieving, from a data structure, data indicative of a template specifying a preferred order of segments for trailers of video content; determining an order of the selected subset of segments based at least in part on the preferred order of segments specified by the template; and generating the personalized trailer of the video content by arranging the selected subsets of segments based at least in part on the determined order.
Liu discloses:
automatically initiating a process for generating a personalized trailer of a video content item (Liu, col. 14, lines 34-36, automatically generating a trailer for a movie).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Liu’s features into the invention of patent No. 11,972,782in view of Chen for enhancing user’s video viewing experience by automatically providing a personalized video trailer.
Patent No. 11,972,782 in view of Chen-Liu does not explicitly disclose but Tian discloses:
retrieving, from a data structure, data indicative of a template specifying a preferred order of segments for trailers of video content; determining an order of the selected subset of segments based at least in part on the preferred order of segments specified by the template ; and generating the personalized trailer of the video content by arranging the selected subsets of segments based at least in part on the determined order (Tian, para’s 0129-0135, a highlight video “trailer” can be arranged in order of start stage, middle stage, and end stage, i.e., a template; the comprehensive feature information of all the moments is input into the second discriminant mode!, so as to determine the probability value of each moment belonging to the start stage, the end stage, or the middle stage of the highlight clip; since an interval around the starting point of the highlight segment can often also be used as the starting point, the starting phase in this example embodiment may refer to a continuous time interval; wherein, the duration of the starting phase may be a fixed duration, for example, 2 seconds, 3 seconds, etc. can also be determined according to the duration of the highlights, for example, 15 %, 20%, etc. of the duration of the highlights; the same is true for the end stage; wherein the lengths of the beginning stage and the end stage are positively correlated (e.g., proportional) to the length of the middle stage; a plurality of candidate start times and a plurality of candidate end times are determined from each of the times according to each of the probability values. a plurality of candidate segments are determined according to the plurality of candidate start times and candidate end times. In this exemplary embodiment, all candidate start moments and candidate end moments may be combined in pairs to form multiple nominations; then, candidate segments are selected from the multiple nominations. For example, first delete the nominations whose candidate start time is later than the candidate end time; then, sort the remaining nominations according to the scores, and filter the top-ranked (for example, top N) corresponding to the candidate start time and the probability value corresponding to the candidate end time are used to calculate the score of the nomination; the calculation method may be to calculate the product, sum or average value of the two probability values. Candidate segments may also be determined according to other rules, which also belong to the protection scope of the present disclosure. In step 740, each of the candidate segments is evaluated, and the highlight segment and the corresponding second metric value are determined from the plurality of candidate segments according to the evaluation result).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Tian’s features into the invention of Patent No. 11,972,782 in view of Chen-Liu for enhancing user’s playback experience by organizing segments of the trailer according to predetermined rules/template. Using Tian’s rule/temple having a predetermined order, a more personalized trailer of the video content can be generated by arranging the selected subsets of segments in such predetermined order.
Claim Rejections - 35 USC § 103
6. The text of those sections of Title 35, U.S. Code not included in this section can be found in a prior Office action.
7. Claims 34-40 and 44-50 are rejected under AIA 35 U.S.C. 103 as unpatentable over Chen et al. (US Publication 2016/0029106) in view of Liu et al. (US Patent 11,694,726), and further in view of Tian et al. (English Translation of Chinese Publication CN110347872 2019).
Regarding claim 34, Chen discloses a computer-implemented method, comprising:
receiving a request from a user to interact with a content platform, wherein the user is associated with a user profile on the content platform (Chen, para’s 0148-0150, receiving user input for accessing a video with an input screen; para. 0034, user interest or preference can be obtained from fixed parameter profile or user input);
initiating a process for generating a personalized trailer of a video content item, the process comprising:
retrieving preferences of the user profile stored in a user profile database (Chen, para. 0034, receiving user input for selecting parameters for generating pictorial summary of the video; parameters can be fixed, i.e., stored in a file or database, and not required selection by a user; para’s 0039-0042, parameters used in scene weighting may include a name of a primary character “James Bond”, a list of highlight actions or objects (for example, the user may principally be interested in the car chases in a movie), parameters used in evaluating pictures in the video, such as, for example, parameters selecting a measure of picture quality, and/or parameters used in selecting pictures from a scene for inclusion in the pictorial summary, such as, for example, a number of pictures to be selected per shot. to emphasize in the weighting; para’s 0148-0151, accessing and retrieving one or more parameters from a configuration guide that includes one or more parameters for configuring a pictorial summary of a video; generating, for the video, a pictorial summary based on the accessed/retrieved parameter In at least one implementation, wherein the pictorial summary conforms to “matches” one or more accessed parameters from the configuration guide);
identifying a plurality of segments of the content item (Chen, para’s 0046-0054, obtaining one or more portions of the video, such as, shots, or groups of scenes, i.e., segments in the video, for parameter weighting);
identifying, for each respective segment of the plurality of segments of the video content item, metadata related to the respective segment of the video content item (Chen, para’s 0046-0054, determining the weight of a scene based on the starting scene and/or the ending scene in the video, appearance frequency of main characters in the scene, i.e., identifying metadata relating to plot structure associated with a scene/segment or metadata relating to the appearance of one or more objects in the scene/segment);
selecting a subset of segments of the plurality of segments having metadata that matches one or more of the retrieved preferences (Chen, para’s 0148-0151, accessing and retrieving one or more parameters from a configuration guide that includes one or more parameters for configuring a pictorial summary of a video; generating, for the video, a pictorial summary based on the accessed/retrieved parameter In at least one implementation, wherein the pictorial summary conforms to “matches” one or more accessed parameters from the configuration guide; para’s 0188-0197, at least one evaluation and selection system includes the functions of evaluating pictures in a video and selecting certain pictures, based on the evaluations, to include in a pictorial summary; identifying different levels of importance (weights) to a scene (or other portion of a video) by considering one or more features such as, for example, the scene position within a video, the appearance frequency of main characters, the length of the scene, and the level/amount of highlighted actions or objects in the scene, considering factors related to how “interesting” a scene, a shot, or a picture is, when determining a weight or ranking, such as, for example, by considering the presence of highlight actions/words and the presence of main characters, and/or using one or more of the following factors in a hierarchical process that analyzes scenes, shots, and individual pictures in generating a pictorial summary: (i) favoring the start scene and the end scene, (ii) the appearance frequency of the main characters, (iii) the length of the scene, (iv) the level of highlighted actions or objects in the scene, or (v) an “appealing quality” factor for a picture);
generating the personalized trailer of the video content by arranging the selected subsets of segments (Chen, para’s 0063-0064, assigning weights to scenes except for the start scene and the end scene which are given different weights; para. 0069, the weights of start scene and end scene are given the highest values in order to increase the representation of the start scene and the end scene in the pictorial summary. This is done because the start scene and the end scene are typically important in the narration of the video; para’s 0148-0151, generating, for the video, a pictorial summary “a trailer” based on the accessed parameter In at least one implementation, wherein the pictorial summary conforms to “matches” one or more accessed parameters from the configuration guide); and
transmitting the personalized trailer of the video content item for display to a device of the user (Chen, para. 0100, providing the highlight video “trailer” to the user who provides user input as parameter).
Chen does not explicitly disclose:
automatically initiating a process for generating a personalized trailer of a video content item;
retrieving, from a data structure, data indicative of a template specifying a preferred order of segments for trailers of video content; determining an order of the selected subset of segments based at least in part on the preferred order of segments specified by the template; and generating the personalized trailer of the video content by arranging the selected subsets of segments based at least in part on the determined order
Liu discloses:
automatically initiating a process for generating a personalized trailer of a video content item (Liu, col. 14, lines 34-36, automatically generating a trailer for a movie).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Liu’s features into Chen’s invention for enhancing user’s video viewing experience by automatically providing a personalized trailer.
Chen-Liu does not explicitly disclose but Tian discloses retrieving, from a data structure, data indicative of a template specifying a preferred order of segments for trailers of video content; determining an order of the selected subset of segments based at least in part on the preferred order of segments specified by the template ; and generating the personalized trailer of the video content by arranging the selected subsets of segments based at least in part on the determined order (Tian, para’s 0129-0135, a highlight video “trailer” can be arranged in order of start stage, middle stage, and end stage, i.e., a template; the comprehensive feature information of all the moments is input into the second discriminant mode!, so as to determine the probability value of each moment belonging to the start stage, the end stage, or the middle stage of the highlight clip; since an interval around the starting point of the highlight segment can often also be used as the starting point, the starting phase in this example embodiment may refer to a continuous time interval; wherein, the duration of the starting phase may be a fixed duration, for example, 2 seconds, 3 seconds, etc. can also be determined according to the duration of the highlights, for example, 15 %, 20%, etc. of the duration of the highlights; the same is true for the end stage; wherein the lengths of the beginning stage and the end stage are positively correlated (e.g., proportional) to the length of the middle stage; a plurality of candidate start times and a plurality of candidate end times are determined from each of the times according to each of the probability values. a plurality of candidate segments are determined according to the plurality of candidate start times and candidate end times. In this exemplary embodiment, all candidate start moments and candidate end moments may be combined in pairs to form multiple nominations; then, candidate segments are selected from the multiple nominations. For example, first delete the nominations whose candidate start time is later than the candidate end time; then, sort the remaining nominations according to the scores, and filter the top-ranked (for example, top N) corresponding to the candidate start time and the probability value corresponding to the candidate end time are used to calculate the score of the nomination; the calculation method may be to calculate the product, sum or average value of the two probability values. Candidate segments may also be determined according to other rules, which also belong to the protection scope of the present disclosure. In step 740, each of the candidate segments is evaluated, and the highlight segment and the corresponding second metric value are determined from the plurality of candidate segments according to the evaluation result).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Tian’s features into Chen-Liu’s invention for enhancing user’s playback experience by organizing segments of the trailer according to predetermined rules/template. Using Tian’s rule/temple having a predetermined order, a more personalized trailer of the video content can be generated by arranging the selected subsets of segments in such predetermined order.
Regarding claim 35, Chen-Liu-Tian discloses the method of claim 34, wherein: the metadata related to the respective segment comprises one or more objects appearing in the respective segment; and the retrieved preferences indicate a preference for at least one of the one or more objects (Chen, para’s 0046-0054, determining the weight of a scene based on determining appearance frequency of main characters in the scene, i.e., identifying metadata relating to the appearance of one or more objects in the scene/segment).
Regarding claim 36, Chen-Liu-Tian discloses the method of claim 34, wherein: the metadata related to the respective segment comprises one or more actors or actresses that appear in the respective segment; and the retrieved preferences indicate a preference for at least one of the one or more actors or actresses (Chen, para’s 0046-0054, determining the weight of a scene based on determining appearance of main characters in the scene, i.e., identifying metadata relating to the appearance of one or more actors or actresses in the scene/segment).
Regarding claim 37, Chen-Liu-Tian discloses the method of claim 34, wherein the metadata related to the respective segment comprises at least one of (i) a genre of the respective segment, (ii) an event of the respective segment, or (iii) audio of the respective segment (Chen, para. 0193, identifying different levels of importance (weights) to a scene (or other portion of a video) by considering one or more features such as, for example, the scene position within a video, the appearance frequency of main characters, the length of the scene, and the highlighted actions or objects in the scene; Liu, col. 2 lines 16-22 and col. 11, lines 11-14, identify genre category for media segments).
The obviousness arguments and motivation to combine the references are the same as claim 34.
Regarding claim 38, Chen-Liu-Tian discloses the method of claim 34, wherein the preferred order specified by the template indicates a predetermined preferred progression of plot elements within a video trailer, and the method further comprises assigning a plot element label to each respective segment of the subset of segments; and determining the order for the selected subset of segments based at least in part on comparing the plot element labels for the selected subset of segments to the preferred progression of plot elements indicated in the template (Chen, para’s 0063-0064, assigning weights to scenes except for the start/intro scene and the end/conclusion scene “plot element labels” which are given different weights; para. 0069, the weights of start scene and end scene are given the highest values in order to increase the representation of the start scene and the end scene in the pictorial summary. This is done because the start scene and the end scene are typically important in the narration of the video; Tian, para’s 0129-0135, a highlight video “trailer” can be arranged in order of start stage, middle stage, and end stage, i.e., a template; the comprehensive feature information of all the moments is input into the second discriminant mode!, so as to determine the probability value of each moment belonging to the start stage, the end stage, or the middle stage of the highlight clip; since an interval around the starting point of the highlight segment can often also be used as the starting point, the starting phase in this example embodiment may refer to a continuous time interval; wherein, the duration of the starting phase may be a fixed duration, for example, 2 seconds, 3 seconds, etc. can also be determined according to the duration of the highlights, for example, 15 %, 20%, etc. of the duration of the highlights; the same is true for the end stage; wherein the lengths of the beginning stage and the end stage are positively correlated (e.g., proportional) to the length of the middle stage; a plurality of candidate start times and a plurality of candidate end times are determined from each of the times according to each of the probability values. a plurality of candidate segments are determined according to the plurality of candidate start times and candidate end times. In this exemplary embodiment, all candidate start moments and candidate end moments may be combined in pairs to form multiple nominations; then, candidate segments are selected from the multiple nominations. For example, first delete the nominations whose candidate start time is later than the candidate end time; then, sort the remaining nominations according to the scores, and filter the top-ranked (for example, top N) corresponding to the candidate start time and the probability value corresponding to the candidate end time are used to calculate the score of the nomination; the calculation method may be to calculate the product, sum or average value of the two probability values. Candidate segments may also be determined according to other rules, which also belong to the protection scope of the present disclosure. In step 740, each of the candidate segments is evaluated, and the highlight segment and the corresponding second metric value are determined from the plurality of candidate segments according to the evaluation result).
The motivation to combine the references and obviousness arguments are the same as claim 34.
Regarding claim 39, Chen-Liu-Tian discloses the method of claim 38 comprising training a machine learning model to accept as input the metadata related to each respective segment and output the plot element label for each respective segment (Tian, para’s 0129-0135, the comprehensive feature information “metadata” of all the moments “segments” is input into the second discriminant model, so as to determine the probability value of each moment “segment” belonging to the start stage, the middle stage, or the end stage of the highlights, i.e., the second discriminant model can be trained to receive metadata related to the moments or segments and output the start stage, the middle stage, or the end stage “the plot element labels” for the moments or segments of the highlights “trailer”).
The motivation to combine the references and obviousness arguments are the same as claim 38.
Regarding claim 40: Chen-Liu-Tian discloses the method of claim 39, wherein the assigning further comprises: identifying one or more audible phrases of each respective segment; determining a corresponding one or more times at which each of the one or more identified audible phrases occur within the video content item; and providing the one or more identified audible phrases and the corresponding one or more times as inputs of the trained machine learning model, to determine the plot element label (Chen, para. 0158, analyze audio that has been turned into text using voice recognition software; para. 0053, by counting the occurrences of the name “Tom”, the system can determine the time(s) and the number of “Tom” appears in the Scene Description 220 text or the Speaking Character 230 text; Tian, para. 0130, the comprehensive feature information of all the moments or times is input into the second discriminant model, so as to determine the probability value of each moment belonging to the start stage of the highlights and the probability of belonging to the end stage of the highlights through the second discrimination model value and the probability value of belonging to the middle stage of the highlight clip; put it differently, the model can receive as input comprehensive feature information of all the moments or times and determine a start stage, an end stage, or middle stage, i.e., plot element labels for highlight portion of each moment or time; see also Wang et al., English Translation of Chinese Publication CN108986785 12-2018, para’s 0100-0103, in order to extract the main plot of the original story text, it is necessary to analyze the original story text and extract the main plot based on the plot elements contained in the original story text. The process of information extraction from the original story text mainly includes three parts: text preprocessing, character recognition, and plot element extraction; the original story text is segmented on a sentence-by-sentence basis using existing or future word segmentation methods, and each word obtained by word segmentation is tagged with part-of-speech; character identification is performed. Specifically, based on the above-mentioned part-of-speech tagging results, a grammatical analyzer or parser can be used to extract the subject of each sentence in the original story text (whose part of speech is generally noun), and then the improved named entity rule model can be used to match the character name, that is, to determine whether the extracted subject is the character name in the original story text. If the subject matches the character name, it may be the character name in the original story text. The improved named entity rule model is based on rule and statistical methods “models”. It trains and learns name entities that appear in a large number of pre-collected novels and story corpus; storyline elements in the original story text can be extracted based on the above-mentioned part-of-speech tagging results, wherein storyline elements refer to the time, place, tasks, props (whose part of speech is generally noun) and actions (whose part of speech is generally verb) in the original story text where the story takes place. The original story text can be segmented using a word segmentation method to obtain each word in the original story text. Then, words that can represent the main storyline elements are selected to summarize the main storyline of the original story text. For example, each word can be selected based on importance, such as selecting words with relatively high frequency of occurrence as words representing the main storyline elements).
The motivation to combine the references and obviousness arguments are the same as claim 38.
Claims 44-50 are rejected for the same reasons set forth in claims 34-40.
8. Claims 41 and 51 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Chen-Liu-Tian, as applied to claims 34 and 44 above, in view of Sharifi (US Publication 2015/0039646).
Regarding claim 41, Chen-Liu-Tian discloses the method of claim 34, comprising generating the personalized trailer of the video content item.
Chen-Liu-Tian does not explicitly disclose but Sharifi discloses selecting an audio track of the video content item, wherein a duration of the audio track corresponds to a duration of the generated personalized trailer of the video content item; and designating the selected audio track as an audio track of the generated personalized trailer of the video content item (Sharifi, para. 0084, select an audio track, from candidate audio tracks, that corresponds to a time period of a movie).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sharifi’s technique into Chen-Liu’s invention for enhancing user’s playback experience by effectively time synchronizing video and audio content.
Claim 51 is rejected for the same reasons set forth in claim 41.
9. Claims 43 and 53 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Chen-Liu-Tian, as applied to claims 34 and 44 above, in view of Dubey et al. (US Patent 12,231,745) or Sardar et al. (US Publication 2021/0011939).
Regarding claim 43, Chen-Liu-Tian discloses the method of claim 34.
Chen-Liu-Tian does not explicitly disclose but Dubey and Sardar each discloses identifying the personalized trailer of the video content item as a first trailer; and determining the order of the selected subset of segments further comprises retrieving a second trailer from the data structure, the second trailer being different from the first trailer; and determining a template for a preferred order of segments that matches an order of segments in the second trailer; and arranging the segments of the first trailer according to the template for the preferred order of segments (Dubey, col. 10 line 58 through col. 11 line 7, as popular quotes change over time, the trailer for the video content may be periodically updated. Accordingly, as different quotes become popular over time, past trailer with previously popular quotes may be replaced with new trailer with currently popular quotes in the same order of arrangement; Sardar et al. 20210011939, para. 0037-0039, applying a model to a particular subset of games; receiving, from the model, score data that identifies the top recommended games and an order thereof; and generating a video comprising trailers of these recommended games in the defined order; as a result, the generated trailer comprises arrangement of recommended previous trailers).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sardar’s technique or Dubey’s technique into Chen-Liu-Tian’s invention for effectively enhancing video content promotion by generating new video trailer having updated material in the same order of arrangement as previous trailer or by generating composite trailer comprising previous content arranged trailers.
Claim 53 is rejected for the same reasons set forth in claim 43.
10. Claim 54 is rejected under AIA 35 U.S.C. 103 as unpatentable over Chen-Liu-Tian, as applied to claim 34 above, in view of Gaur et al. (US Publication 2020/0275158).
Regarding claim 54, Chen-Liu-Tian discloses the method of claim 34, wherein metadata for a first segment of the plurality of segments comprises an indication of a genre of the first segment (Liu, col. 2 lines 16-22 and col. 11, lines 11-14, identify genre category for media segments).
Chen-Liu-Tian does not explicitly disclose but Gaur discloses wherein the selecting of the subset of segments comprises selecting the first segment based on the user profile indicating a preference for the genre of the first segment (Gaur, para. 0052, recommending any content items 201 determined to have one or more scenes associated with the matching genre. For example, if the genre map 202 for a particular content item 201 includes at least one action scene, the recommendation module 252 may recommend the content item 201 to a user determined to have a preference for the action genre).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Gaur’s features into Chen-Liu-Tian’s invention for enhancing user’s video viewing experience by providing content items determined to have matching genre with user’s genre preference.; and wherein the selecting of the subset of segments comprises selecting the first segment based on the user profile indicating a preference for the genre of the first segment.
11. The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. These include:
Henry, US Patent 10,860,862
Hamid et al., US Patent 10,917,704
Dantzler et al., US Patent 9,635,337
Conclusion
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/LOI H TRAN/ Primary Examiner, Art Unit 2484
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