DETAILED OFFICE ACTION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/12/2025 has been entered.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments, see pg. 9, filed 11/12/2025, with respect to the status of the claims are hereby acknowledged.
Applicant’s arguments, see pg. 9-10, filed 11/12/2025, rejection of claims 1-20 under 35 U.S.C. 103 are hereby acknowledged and have been fully considered. The examiner notes that the applicant’s arguments are directed to the newly amended limitations not previously presented.
In particular, applicant argues the following:
The Supreme Court in KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 399 (2007) insisted in its holding that finding all of the claim elements in the prior art is necessary, though not sufficient, in order to conclude that a patent claim is obvious. An obviousness rejection of amended independent claim 1 under 35 U.S.C. § 103 would be improper because Zhou and Marsh do not, individually or in combination, disclose or suggest all of the elements recited in amended independent claim 1.
Claim 1 has been amended to clarify that "media content items" are "tagg[ed]... with one or more attributes and one or more corresponding content attribute scores", where "the attributes describe segments of targeted audience" and "a respective content attribute score represents a similarity between a respective media content item and a respective attribute." For example, as described in paragraph [0044] of the specification, "an attribute can be a phrase that describes a segment of the targeted audience, e.g., 'young pet owner'."
In response to applicant’s arguments, the test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981). Additionally, on the issue of obviousness, the Supreme Court stated the analysis of a rejection on obviousness grounds need not seek out precise teachings directed to the specific subject matter of the challenged claim, for a court can take account of the inferences and creative steps that a person of ordinary skill in the art would employ. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 418, 82 USPQ2d 1385 (2007). The obvious analysis cannot be confined by a formalistic conception of the words teaching, suggestion, and motivation. Id. at 419. Further, the Court stated that common sense teaches, however, that familiar items may have obvious uses beyond their primary purposes, and in many cases a person of ordinary skill will be able to fit the teachings of multiple patents together like pieces of a puzzle. See id. at 420.
Furthermore, in response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., "an attribute can be a phrase that describes a segment of the targeted audience, e.g., 'young pet owner'.") are not recited in the rejected claim(s). 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). All things considered, a new grounds of rejection is set forth in order to address the newly amended limitations with newly found prior art.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-5, 10-16, 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhou, Yiming et al. US 20030097657 A1 (hereafter Zhou) and in further view of Niebles Duque; Juan Carlos et al. US 8924993 B1 (hereafter Niebles) and in further view of Marsh, David J. US 20030233241 A1 (hereafter Marsh).
Regarding claim 1, “a method comprising: at a headend including one or more processors and a non-transitory memory: obtaining content attribute scores of attributes associated with media content items, wherein the attributes describe segments of targeted audience, and a respective content attribute score represents a similarity between a respective media content item and a respective attribute; tagging the media content items with one or more attributes and one or more corresponding content attribute scores, including tagging a set of targeted content items with a set of attribute identifiers; transmitting the tagged media content items to a weakly connected device, wherein the one or more content attribute scores are used by the weakly connected devices to determine user attribute scores indicating levels of interest for the one or more attributes based on viewed media content items at the weakly connected device, and causing the weakly connected device to locate a set of user attribute scores corresponding to the set of attribute identifiers and select a targeted content item from the set of targeted content items based at least in part on the set of user attribute scores” Zhou para 26, 67, 131, 143, 182 teaches programs transmitted to user STB contain metadata information (i.e., tagging information) comprising attributes identifying the program content that enable the rights owner to target their program material comprising advertisements wherein target information includes target types and metadata comprising program and targeting that is transmitted to be stored at the STB local storage (see para 131 special targeting information is added to or supplements the program information metadata to enable the video program it references to be aimed at a user target); para 82-88 targeting content to user devices based on metadata comprising comparing labels or values for the database contents understood as providing values for attributes for comparison; para 89-94 – targeting program content takes into consideration program history data with data mainly from monitoring programs viewed corresponds to “determine user attribute scores indicating levels of interest for the one or more attributes based on viewed media content items at the weakly connected device”; para 95-103 user information in the STB comprising scores related to content attributes is utilized in order to analyze user computed preferences comprising a relative degree of preference in order to select targeted content for viewing at the STB. With respect to the weakly connected devices, Zhou teaches the disclosed STB receives data in an unidirectional manner as disclosed in Fig. 1 and para 6 disclose video metadata and video content is received from the head-end without a return path to the head-end device understood as either unidirectional or bidirectional links between the content provider and the user.
Furthermore, with respect to the limitation “obtaining content attribute scores of attributes associated with media content items, wherein the attributes describe segments of targeted audience,” whereas Zhou does not use the same terms “content attribute scores” (i.e., in haec verba), as discussed above, Zhou does teach that the metadata associated with the media content items is used to target the particular interests of the viewers (see para 82-88 targeting content to user devices based on metadata comprising comparing labels or values for the database contents understood as providing values for attributes for comparison and para 95-103 user information in the STB comprising scores related to content attributes is utilized in order to analyze user computed preferences comprising a relative degree of preference in order to select targeted content for viewing at the STB.) A person of ordinary skill in the art would have reasonably inferred that wherein Zhou does teach that the metadata associated with the media content items is transmitted to a user device and used to target the particular interests of the viewers, the prior art also recognizes the benefit of utilizing additional metadata to classify data about the media content. For example, in an analogous art, Niebles teaches features for a video may further include textual metadata, such as the video title and any tag words or phrases assigned to the video and further teaches features for a video may further include content features derived directly or indirectly from audiovisual content of the video. For example, such content features can include features related to visual properties (see col. 8:5-56 and col. 10:4-12 and col. 10:39-56; discussing when the video classifier model 215 for a particular demographic attribute value is applied to a video, it determines whether (or to what degree) its associated demographic attribute value represents the video. In other embodiments, to infer continuous attributes (e.g., age) the model 215 is trained using regression analysis, and when applied to a video determines the quantity (and possibly the precision of the estimation) associated to the attribute 210 that best represents the video… wherein the term degree is also considered a score value). All things considered, Niebles teaches content attribute values/scores of attributes associated with media content items wherein the attributes describe segments of targeted audience comprising demographics.
In an analogous art, Marsh para 73 teaches “recommendation engine 616 determines that an attribute value in the user preference file matches an attribute value found in a content description file, the matching engine 616 can calculate an attribute score for the matching attribute. For example, an "actor" attribute in the user preference file may contain a value of "Steve Martin." If an "actor" attribute in the content description file also contains the value of "Steve Martin," then the "actor" attribute is designated as a matching attribute. An attribute score can then be assigned to the matching attribute, and one or more attribute scores assigned in a program can be used to calculate a program score for the program.”
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention modify Zhou’s invention comprising programs transmitted to user STB contain metadata information (i.e., tagging information) comprising attributes identifying the program content that enable the rights owner to target their material and determine levels of interest for the one or more attributes based on viewing history of viewed media content items at a connected device with unidirectional capabilities by further incorporating known elements of Niebles’ invention for identifying attributes of media content and associated values/scores based on features for a video including textual metadata, such as the video title and any tag words or phrases assigned to the video, features derived directly or indirectly from audiovisual content of the video in order to generate a particular demographic attribute value is applied to a video, it determines whether (or to what degree) its associated demographic attribute value represents the video and determines the quantity (and possibly the precision of the estimation) associated to the attribute that best represents the video because the combination of elements would enable the invention of Zhou, Niebles to use of user-specific data to evaluate various media content and then make recommendations as to which content a user would most likely wish to experience as disclosed in Marsh for utilizing an attribute score/value associated with content description data in order to calculate a value to determine whether the content is to be presented to the end user for viewing and provide a locally tailored viewing experience at the end user device without communicating with the headend.
Regarding claim 2, “wherein obtaining the content attribute scores of attributes associated with the media content items includes: identifying the one or more attributes of the media content items; and utilizing a natural language processing (NLP) model to calculating for the media content items the content attribute scores” is further rejected on obviousness grounds as discussed in the rejection of claim 1 wherein Niebles col. 8:5-56 teaches the training, a positive training set is formed for each phrase, the positive training set containing videos having that phrase (e.g., within their textual metadata 117A); Features, such as those described above, are extracted for each of the videos in the positive and negative training sets and are provided as input to an ensemble learning algorithm, such as Support Vector Machines (SVM), boosting algorithms such as AdaBoost, or the like. The output of the learning algorithm is, for each category phrase, the corresponding category classifier model. Whereas Niebles teaches machine learning algorithms, see also prior art to Marsh disclosing elements of content attributes wherein Marsh para 71-73 teaches “recommendation engine 616 determines that an attribute value in the user preference file matches an attribute value found in a content description file, the matching engine 616 can calculate an attribute score for the matching attribute. For example, an "actor" attribute in the user preference file may contain a value of "Steve Martin." If an "actor" attribute in the content description file also contains the value of "Steve Martin," then the "actor" attribute is designated as a matching attribute. An attribute score can then be assigned to the matching attribute, and one or more attribute scores assigned in a program can be used to calculate a program score for the program.” A person of ordinary skill in the art would have reasonably inferred, based on the combined teachings of Zhou and Marsh that content is associated with attribute values that define the relevance of the attributes to the user preferences to determine whether there is a particular degree of similarity in order to determine whether content will be selected for presentation to the end user.
Regarding claim 3, “further comprising: prior to performing the tagging, determining whether a media content item is in one or more predefined categories; and forgoing tagging a content attribute score for the media content item in accordance with determining that the media content item is in the one or more predefined categories” is further rejected on obviousness grounds as discussed in the rejection of claims 1-2 wherein Marsh para 79 incorporates by reference Marsh application 10/125,260 (US20030195863A1 para 211-224 disclosing an embodiment wherein tagging of content is given a main categorization but the other content elements are set to zero is interpreted as only tagging a main category and ignoring other potential categories when multiple categories may apply).
Regarding claim 4, “further comprising: adding an attribute different from the one or more attributes; tagging a subset of the media content items with the attribute and a set of content attribute scores; and transmitting to the weakly connected device identifiers of the subset of the media content items, the attribute, and the set of content attribute scores” is further rejected on obviousness grounds as discussed in the rejection of claims 1-3 wherein Zhou teaches tagging advertisements (para 39, 97, 154, 173) and Marsh para 79 incorporates by reference Marsh application 10/125,260 (US20030195863A1 para 81 disclosing a grouping comprising a series have an extra attribute for the group of media content in the series).
Regarding claim 5, “further comprising: setting a set of priority scores for the set of targeted content items; transmitting to the weakly connected device the set of priority scores; and causing the weakly connected device to apply the set of priority scores to a set of scores calculated for the set of targeted content items when selecting the targeted content item from the set of targeted content items” is further rejected on obviousness grounds as discussed in the rejection of claims 1-2 wherein Marsh para 105-107 discloses a weighting factor when determining whether a program should be recommended to a user and wherein Marsh para 79 incorporates by reference Marsh application 10/125,260 (US20030195863A1 para 85 disclosing a priority of metadata as a ranking; see also para 100 metadata provider specifies the order of importance of the multiple entries using the Entry Index field. The metadata provider can provide information as to why each different entry exists in the Entry Tag elements of each Alternate Content Identifiers entity.).
Regarding the method claims 10-16 the claims are grouped and rejected with the method claims 1-5 because the steps of the method claims are met by the disclosure of the apparatus and methods of the reference(s) as discussed in the rejection of claims 1-3 and because the steps of the method are easily converted into elements of a computer device by one of ordinary skill in the art. With respect to the limitation of claim 11, the combination of prior art to Zhou and Marsh are discussed in the rejection of claims 1-5 discuss tracking the user’s viewing history which corresponds to “tracking the viewed media content items at the client device” of claim 11 and wherein claim 1 recites the limitation “determine levels of interest for one or more attributes based on viewed media content items at the weakly connected device.” With respect to claim 12, the limitation regarding “a user input” corresponds to tracking the user’s viewing history interpreted as the viewer selecting content for viewing. Regarding the weights discussed in claims 13 and the priority score of claim 15, as discussed in combination of references in the rejection of claims 1-5, Marsh para 105-107 discloses a weighting factor when determining whether a program should be recommended to a user and wherein Marsh para 79 incorporates by reference Marsh application 10/125,260 (US20030195863A1 para 85 disclosing a priority of metadata as a ranking; see also para 100 metadata provider specifies the order of importance of the multiple entries using the Entry Index field. The metadata provider can provide information as to why each different entry exists in the Entry Tag elements of each Alternate Content Identifiers entity.).
Regarding the device claims 18-20 the claims are grouped and rejected with the method claims 1-3 because the steps of the method claims are met by the disclosure of the apparatus and methods of the reference(s) as discussed in the rejection of claims 1-3 and because the steps of the method are easily converted into elements of a computer device by one of ordinary skill in the art.
Claim(s) 6-9, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Zhou, Yiming et al. US 20030097657 A1 (hereafter Zhou) Niebles Duque; Juan Carlos et al. US 8924993 B1 (hereafter Niebles) and in further view of Marsh, David J. US 20030233241 A1 (hereafter Marsh) and in further view of Sheppard; Michael et al. US 20170091786 A1 (hereafter Sheppard).
Regarding claim 6, whereas Zhou, Niebles, and Marsh in the rejection of claims 1-5 disclose wherein the respective targeted content item is associated with one or more attributes, each defining a respective segment of targeted audience, Zhou and Marsh do not disclose obtaining a number of viewers as claimed (i.e., “further comprising: obtaining a number of viewers of the set of targeted content items; estimating a proportion of population viewing a respective targeted content item in the set of targeted content items at a plurality of weakly connected devices, wherein the respective targeted content item is associated with one or more attributes, each defining a respective segment of targeted audience; and determining number of times the respective targeted content item being viewed by the respective segment of the targeted audience at the plurality of weakly connected devices based on the number of viewers and the proportion of population”). See also Niebles col. 6:14-45 disclosing identifying demographics comprising identifying viewing periods for each of a number of different users and a set of videos viewed during a particular time period. See also Marsh para 79 incorporates by reference Marsh application 10/125,260 (US20030195863A1 para 227 disclosing target audience tag identifiers).
In an analogous art, Sheppard discloses the deficiency of Zhou, Niebles, and Marsh with respect to an invention for obtaining a number of viewers of the set of targeted content items (Abstract - determine demographics of populations to measure media audiences of populations includes determining demographics for members of a first household of a sub-population; see also para 15-18 accurately estimate demographics of a population (e.g., a population as a whole) based on tuning data of a sub-population; para 45 utilizing metadata for use in identifying the media as part of the media exposure; para 66-68 calculating target demographics).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention modify Zhou’s invention comprising programs transmitted to user STB contain metadata information (i.e., tagging information) comprising attributes identifying the program content that enable the rights owner to target their material and determine levels of interest for the one or more attributes based on viewing history of viewed media content items at a connected device with unidirectional capabilities by further incorporating known elements of Niebles’ invention for identifying attributes of media content and associated values/scores based on features for a video comprising identifying a number of viewers of each media content item and by further incorporating known elements of Marsh’s invention for utilizing an attribute score/value associated with content description data and target audience identifiers in order to calculate a value to determine whether the content is to be presented to the end user for viewing and provide a locally tailored viewing experience at the end user device without communicating with the headend by further incorporating known elements of Sheppard’s invention for determining viewership of media content and accurately viewership of content comprising estimate demographics of a population (e.g., a population as a whole) based on tuning data of a sub-population wherein media content comprises metadata for use in identifying the media as part of the media exposure in order to take into consideration the viewership of non-panelist user devices that have displayed content to a user but have limited communication with headend devices and more accurately calculate all viewership information.
Regarding claim 7, “wherein estimating the proportion of population viewing the respective targeted content item in the set of targeted content items at the plurality of weakly connected devices includes: obtaining panel data representing viewing of the respective targeted content item at a plurality of client devices; and deriving the proportion of population viewing the respective targeted content item at the plurality of weakly connected devices from the panel data” is further rejected on obviousness grounds as discussed in the rejection of claims 1-6 wherein Marsh para 79 incorporates by reference Marsh application 10/125,260 (US20030195863A1 para 227 disclosing target audience tag identifiers). See also Niebles col. 6:14-45 disclosing identifying demographics comprising identifying viewing periods for each of a number of different users and a set of videos viewed during a particular time period. See also Sheppard Abstract - determine demographics of populations to measure media audiences of populations includes determining demographics for members of a first household of a sub-population; see also para 15-18 accurately estimate demographics of a population (e.g., a population as a whole) based on tuning data of a sub-population; para 45 utilizing metadata for use in identifying the media as part of the media exposure; para 66-68 calculating target demographics).
Regarding claim 8, “wherein estimating the proportion of population viewing the respective targeted content item in the set of targeted content items at the plurality of weakly connected devices includes: obtaining reporting of client data representing viewing the respective targeted content item at fully connected devices; and estimating the proportion of population viewing the respective targeted content item in the set of targeted content items at the plurality of weakly connected devices based at least in part on the client data” is further rejected on obviousness grounds as discussed in the rejection of claims 1-7 wherein Niebles col. 6:14-45 disclosing identifying demographics comprising identifying viewing periods for each of a number of different users and a set of videos viewed during a particular time period. See also Marsh para 79 incorporates by reference Marsh application 10/125,260 (US20030195863A1 para 227 disclosing target audience tag identifiers). See also Sheppard Abstract - determine demographics of populations to measure media audiences of populations includes determining demographics for members of a first household of a sub-population; see also para 15-18 accurately estimate demographics of a population (e.g., a population as a whole) based on tuning data of a sub-population; para 45 utilizing metadata for use in identifying the media as part of the media exposure; para 66-68 calculating target demographics).
Regarding claim 9, “wherein estimating the proportion of population viewing the respective targeted content item in the set of targeted content items at the plurality of weakly connected devices includes: obtaining reporting of client data representing the level of interests from the weakly connected device via an independent source coupled with the weakly connected device; and deriving the proportion of population based at least in part on the client data” is further rejected on obviousness grounds as discussed in the rejection of claims 1-7 wherein Niebles col. 6:14-45 disclosing identifying demographics comprising identifying viewing periods for each of a number of different users and a set of videos viewed during a particular time period. See also Marsh para 79 incorporates by reference Marsh application 10/125,260 (US20030195863A1 para 227 disclosing target audience tag identifiers). See also Sheppard Abstract - determine demographics of populations to measure media audiences of populations includes determining demographics for members of a first household of a sub-population; see also para 15-18 accurately estimate demographics of a population (e.g., a population as a whole) based on tuning data of a sub-population; para 45 utilizing metadata for use in identifying the media as part of the media exposure; para 66-68 calculating target demographics).
Regarding the method claims 17 the claims are grouped and rejected with the method claims 1-9 because the steps of the method claims are met by the disclosure of the apparatus and methods of the reference(s) as discussed in the rejection of claims 1-9 and because the steps of the method are easily converted into steps of the method of claim 17.
CONCLUSION
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/ALFONSO CASTRO/Primary Examiner, Art Unit 2421