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 .
The present application claims priority from Japanese application JP2024-049445 filed on 03/26/2024.
This communication is responsive to the amendment filed on 06/29/2026.
Status of claims:
Claim 17 is newly added.
Claims 1-17 are pending for examination.
Response to Arguments
Applicants' arguments with respect to the amended claims have been considered in view of the new ground(s) of rejection necessitated by amendment.
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 1-17 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 15 and 16: recite the limitations “a contribution degree…” and “a marginal
contribution of each attribute to a probability ….”, which render the claims indefinite because the claims provide no guidance as how the above limitations are identified, defined, and performed. Applicant is required for clarification/correction.
Applicant is reminded that 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).
Claims 1, 15 and 16: recite the limitations “classify…, calculate…; acquire…; and input…”. There is no output result(s) of the claims. Applicant is required for clarification/correction of the above issues.
- All dependent claims are rejected under the same rational as their based claim as above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-16 are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al., (CN 2021/10440176 A), hereinafter “Xu”, in view of Cheng (CN 2020/10289148 A), and further in view of Saranathan et al. (US 12591740 B20), hereinafter “Saranathan”.
Claim 1, Xu discloses an information processing system (see Abstract, a video processing method), comprising:
at least one processor (page 2, last 2 paragraphs, a processor, a communication interface, a memory and a communication bus, wherein the processor, a communication interface, a memory through the communication bus to finish the mutual communication); and
at least one memory device that stores a plurality of instructions which, when executed by the at least one processor (page 2, last 2 paragraphs, a processor, a communication interface, a memory and a communication bus, wherein the processor, a communication interface, a memory through the communication bus to finish the mutual communication), causes the at least one processor to:
- classify, based on an attribute value of each of a plurality of types of attributes stored in association with each of a plurality of users, the plurality of users into a plurality of clusters (page 5, step A1-step A3, classifying the M users according to the N external characteristics of the M users; and obtaining a plurality of user cluster, namely M user is divided into a plurality of user cluster, each user cluster at least comprises one user);
- calculate, for each of a plurality of users classified into a target cluster being any one of the plurality of clusters, a contribution degree of each of the plurality of types of attributes to classify into the target cluster (page 5, step A1-step A3, determining the target algorithm matched with the target user and obtaining the important degree of each external feature, selecting an external feature (target external feature) with the largest influence to classify the user).
Xu fails to acquire, based on the attribute value of each of the plurality of types of attributes stored in association with each of the plurality of users classified into the target cluster, a representative attribute value that represents the target cluster corresponding to one of the plurality of types of attributes; and output, based on the representative attribute value and the contribution degree, information indicating a representative personality of a user belonging to the target cluster.
Meanwhile, Cheng discloses acquire, based on the attribute value of each of the plurality of types of attributes stored in association with each of the plurality of users classified into the target cluster, a representative attribute value that represents the target cluster corresponding to one of the plurality of types of attributes (page 2, par. [1]-[4] and page 3, par. [5], certain attributes (e.g., "representation" attribute), but for other attributes (e.g., "birthplace" attribute, etc.), when processing with the full-reservation mode, on the one hand, it will bring a large number of repeating attribute values, increasing the storage overhead; on the other hand, it also brings hidden trouble of storing error attribute value, resulting in the accuracy of the generated knowledge map is reduced; obtaining entity information cluster of the target entity, the target entity has a plurality of attributes, the entity information cluster corresponding to a plurality of entity information source, each attribute corresponding to at least one entity information source, for each attribute, in the entity information cluster comprises providing at least one entity information source identifier of the attribute, and the attribute value provided by the entity information source; for each attribute of the plurality of attributes of the target entity, determining the attribute type of the attribute, and determining the corresponding attribute value processing strategy according to the attribute type, wherein the attribute type comprises one of a single value attribute, a multi-value attribute, a reserved attribute, a dependent attribute; and processing policy according to the determined attribute value, based on the attribute value provided by the entity information source corresponding to the attribute, generating the fusion attribute value of the attribute); and
- output, based on the representative attribute value and the contribution degree, information indicating a representative personality of a user belonging to the target cluster (page 2, [4] and page 7, par [7]-[10], obtain the target entity belongs to a plurality of attribute values of a plurality of attribute, wherein the entity information source " bean curd sheet of Zhang Guorong of the page ", "Baidu Baike's Zhang Guorong introduction page" has its corresponding identification Fusion-1, Fusion-2, and the entity information source is represented by its URL coding, respectively is url-1, url-2, the attribute value obtained from the page of the opening of the broad bean curd sheet is: (corresponding to the attribute of the "video representation"), "Spring and summer autumn" (corresponding to the attribute of the "song representation"), and the " " attribute "of" the " " the " " hegemonig "(corresponding to the" song " attribute); The attribute value of the attribute of the "film and television representation" attribute, which is obtained from the Zhang Guorong of Baidu Pake, is "Spike Sixiance", "The Soul of the Queen", and the attribute value "silence" corresponding to the attribute of the "song representation", "I", "Monica).
Therefore, it would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the system of Xu to use an attribute value of each of the plurality of types of attributes stored in association with each of the plurality of users classified into the target cluster and output, based on the representative attribute value and the contribution degree, information indicating a representative personality of a user belonging to the target cluster, in order to enable targeted communication that addresses the specific needs and pain points of the target audience leading to mare effective marketing campaigns.
The combination of Xu and Cheng discloses the invention as claimed, except “the processor calculates the contribution degree of each of the plurality of types of attributes based on Shapley values obtained by applying SHapley Additive exPlanations ("SHAP") to an output of a trained classification model, the Shapley values indicating a marginal contribution of each attribute to a probability that each of the plurality of users belongs to the target cluster”
On the other hand, Saranathan discloses the processor calculates the contribution degree of each of the plurality of types of attributes based on Shapley values obtained by applying SHapley Additive exPlanations ("SHAP") to an output of a trained classification model, the Shapley values indicating a marginal contribution of each attribute to a probability that each of the plurality of users belongs to the target cluster (col. 3 lines 1-26, determine a topic probability score (TPS) corresponding to the at least one preprocessed text document, via an unsupervised machine learning (ML) model, wherein the TPS indicates probability of each of the at least one preprocessed text document among the plurality of text documents, being associated with at least one cluster generated by the unsupervised ML model. The at least one processor is configured to determine a confidence score (CS) corresponding to the at least one preprocessed text document, via a supervised ML model, wherein the CS indicates a reliability level associated with classification of each of the at least one preprocessed text document among the plurality of text documents, predicted by the supervised ML model; and col. 10 lines 5-55, the topic model may be configured to generate the label for the at least one document among the plurality of text documents, using title-generation techniques by analyzing the distribution of words to generate the label for each of the topics. (44) Topic 1: 20% dog, 10% cat, . . . ; wherein the label generated may be “PET”. Topic 2: 30% peanuts, 15% almonds, 10% rice, . . . ; wherein the label generated may be “Food” Topic 3: Bedok 30%, EastCoast 20%, . . . ; wherein the label generated may be “Location”. Topic 4: Christina, Burke . . . ; wherein the label generated may be “Person”. Determine a confidence score (CS) corresponding to the at least one preprocessed text document. In an example, the confidence score may indicate a reliability level associated with the classification of each of the at least one preprocessed text document among the plurality of text documents, predicted by the supervised ML model 104b. In the example, the supervised ML model 104b that classifies images as dog or cat may provide an output: Document 1: [0.99 dog, 0.01 cat]; i.e., the determining module 216 may be configured to determine the confidence score corresponding to the at least one preprocessed text document as 99% confident that the image is a dog. Thus, the determining module may determine the confidence score establishing the reliability of the unsupervised ML model's 104b prediction. (69) In an exemplary embodiment, the forecasting ML model 104c may be configured to generate explainability corresponding to the final forecast. In an example, the forecasting ML model 104c may use model-agnostic methods such as, but not limited to, Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) to generate explainability corresponding to the at least one preprocessed text document based on the correlation of at least one preprocessed text document and the feature importance analysis. In the example, explainability may refers to the ability of the forecasting ML model 104c to provide understandable and interpretable explanations for its decisions or predictions.).
Therefore, it would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the system of the cited references to include the feature as Saranathan to achieve the highest levels of accuracy and adaptability for enhancing decision-making processes and enriching human interactions with intelligent systems.
Claim 2, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the plurality of instructions cause the at least one processor to train a machine learning model through use of training data including the attribute value of each of the plurality of types of attributes in each of the plurality of users and ground truth data indicating a cluster into which each of the plurality of users is classified, wherein the contribution degree of each of the plurality of types of attributes to the classification into the target cluster is calculated for each of the plurality of users classified into the target cluster based on the trained machine learning model and the attribute values of the plurality of types of attributes in each of the plurality of users classified into the target cluster (page 8, par. [5]-[6], each attribute of the plurality of attributes of the target entity, determining the attribute type of the attribute, and determining the attribute value processing strategy corresponding to the attribute type according to the attribute type, wherein the attribute type comprises a single value attribute, multi-value attribute, reserved attribute, one of dependent attribute. wherein the attribute type represents characteristic of the attribute, comprising a single value attribute, multivalue attribute, reserved attribute, one of dependent attribute, the single attribute is to characterie the attribute only has one attribute value, such as " age " attribute is a single value attribute; the multi-value attribute is intended to characterie the attribute has a plurality of attribute values, for example, for a " television drama work " attribute, such as may include a plurality of attribute values; the dependent attribute is intended to characterie that the attribute has a strong dependency relationship with other attributes).
Claim 3, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Xu discloses the plurality of instructions cause the at least one processor to calculate an importance degree for the classification of the plurality of users into the target cluster for each of the plurality of types of attributes based on the contribution degrees calculated for the plurality of users classified into the target cluster, wherein the information indicating the representative personality of a user belonging to the target cluster is output based on the representative attribute value and the importance degree (page 11, [1]-[8], a second classification module, for the plurality of user clusters, the user number is greater than or equal to the user in the target user cluster of the second number, according to the important degree of the target external characteristic to classify, obtaining a plurality of sub-user clusters in the target user cluster).
Claim 4, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the plurality of instructions cause the at least one processor to select some of the plurality of types of attributes based on the importance degree, wherein the information indicating the representative personality of the plurality of users belonging to the target cluster is output based on the representative attribute values in the selected some of the plurality of types of attributes (page 9, [1]-[4], the process of determining the attribute type of the attribute for each attribute of the plurality of attributes of the target entity comprises: The method comprises the following steps: firstly, obtaining the entity type of the target entity; Then, the attribute type of the attribute is determined according to the entity type of the target entity, for the same attribute "wife", when the target entity is a "Pu Yi", the corresponding entity class is "human-Qing dynasty emperor"; then the attribute type is a "multi-value attribute"; and when the target entity is " Jun Yun ", the corresponding entity type is " human-video star "; the attribute type is " single value attribute ". Therefore, for the same attribute, when it is corresponding to different entities, can according to the entity type of the entity to determine the attribute type of the attribute, so as to determine the proper attribute value processing strategy).
Claim 5, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the plurality of instructions cause the at least one processor to calculate, as the importance degree, an average value of the contribution degrees calculated for the plurality of users classified into the target cluster for each of the plurality of types of attributes (page 8, par. [2]-[6], each attribute of the plurality of attributes of the target entity, determining the attribute type of the attribute, and according to the attribute type determining the corresponding attribute value processing strategy, wherein the attribute type comprises a single value attribute, multi-value attribute, reserved attribute, one of the dependent attribute, wherein the attribute type represents characteristic of the attribute, comprising one of a single value attribute, a multi-value attribute, a reserved attribute, a dependent attribute, the single attribute is intended to characterie the attribute only has one attribute value, for example, the age attribute is a single value attribute; the multi-value attribute is intended to characterie the attribute has a plurality of attribute values, for example, for a " TV drama work " attribute, such as may include a plurality of attribute values; the dependent attribute of the dependent attribute is intended to characterie that the attribute has a strong dependency relationship with other attributes).
Claim 6, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the plurality of instructions cause the at least one processor to calculate, as the importance degree, a value indicating a correlation based on the contribution degrees and the attribute values in the plurality of users classified into the target cluster for each of the plurality of types of attributes (page 8, par. [2]-[6], each attribute of the plurality of attributes of the target entity, determining the attribute type of the attribute, and according to the attribute type determining the corresponding attribute value processing strategy, wherein the attribute type comprises a single value attribute, multi-value attribute, reserved attribute, one of the dependent attribute, wherein the attribute type represents characteristic of the attribute, comprising one of a single value attribute, a multi-value attribute, a reserved attribute, a dependent attribute, the single attribute is intended to characterie the attribute only has one attribute value, for example, the age attribute is a single value attribute; the multi-value attribute is intended to characterie the attribute has a plurality of attribute values, for example, for a " TV drama work " attribute, such as may include a plurality of attribute values; the dependent attribute of the dependent attribute is intended to characterie that the attribute has a strong dependency relationship with other attributes).
Claim 7, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Xu Cheng discloses the plurality of instructions cause the at least one processor to:
- calculate an average value of the contribution degrees calculated for the plurality of users for each of the plurality of types of attributes (page 3, par. [1], calculating the attribute value contribution number of the entity information source to the attribute; ordering said at least two entity information sources according to the order of the contribution number of the attribute value from big to small and calculating the appearance times of each attribute value of the attribute, wherein the attribute value of the attribute is arranged from big to small according to the appearing times);
- select some of the plurality of users as one or more representative users based on the average value and the contribution degrees of the plurality of users classified into the target cluster in each of at least some of the plurality of types of attributes (page 6, par. [7], selecting attribute value for all attributes in the same entity information cluster, that is, in the entity information cluster, for each attribute of the entity, selecting the effective attribute value from the attribute values of the plurality of sources, thereby obtaining the attribute of the fusion attribute value); and
- generate a representative attribute value that represents the target cluster based on the attribute value in the one or more representative users for the at least some of the plurality of types of attributes (page 6, par. [6]-[10], generate entity information cluster).
Claim 8, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the plurality of instructions cause the at least one processor to acquire a relative value that indicates a relative relationship between each of the representative attribute values calculated for the plurality of types of attributes and an overall representative attribute value calculated for a group formed of the plurality of clusters, and wherein the information indicating the representative personality of a user belonging to the target cluster is output based on the contribution degree, the acquired relative value, and the representative attribute value (page 2, [4] and page 7, par [7]-[10], obtain the target entity belongs to a plurality of attribute values of a plurality of attribute, wherein the entity information source " bean curd sheet of Zhang Guorong of the page ", "Baidu Baike's Zhang Guorong introduction page" has its corresponding identification Fusion-1, Fusion-2, and the entity information source is represented by its URL coding, respectively is url-1, url-2, the attribute value obtained from the page of the opening of the broad bean curd sheet is: (corresponding to the attribute of the "video representation"), "Spring and summer autumn" (corresponding to the attribute of the "song representation"), and the " " attribute "of" the " " the " " hegemonig "(corresponding to the" song " attribute); The attribute value of the attribute of the "film and television representation" attribute, which is obtained from the Zhang Guorong of Baidu Pake, is "Spike Sixiance", "The Soul of the Queen", and the attribute value "silence" corresponding to the attribute of the "song representation", "I", "Monica).
Claim 9, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the plurality of instructions cause the at least one processor to acquire, for an attribute that indicates a category out of the plurality of types of attributes, a relative value indicating a probability that a plurality of users classified into the plurality of clusters belong to a category indicated by the representative attribute value of the target cluster (page 9, par. [7], according to the determined result, the attribute type of the attribute is multi-value attribute, then in the step S402, based on the entity information source ordering result of the attribute, the entity information source ordering the first is determined as the target entity information source, and using the attribute value provided by the target entity information source as the fusion attribute value).
Claim 10, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the information indicating the representative personality of a user belonging to the target cluster is output based on the representative attribute value in an attribute selected from the plurality of types of attributes based on the contribution degree and the acquired relative value (page 2, par. [1]-[4] and page 3, par. [5], certain attributes (e.g., "representation" attribute), but for other attributes (e.g., "birthplace" attribute, etc.), when processing with the full-reservation mode, on the one hand, it will bring a large number of repeating attribute values, increasing the storage overhead; on the other hand, it also brings hidden trouble of storing error attribute value, resulting in the accuracy of the generated knowledge map is reduced; obtaining entity information cluster of the target entity, the target entity has a plurality of attributes, the entity information cluster corresponding to a plurality of entity information source, each attribute corresponding to at least one entity information source, for each attribute, in the entity information cluster comprises providing at least one entity information source identifier of the attribute, and the attribute value provided by the entity information source; for each attribute of the plurality of attributes of the target entity, determining the attribute type of the attribute, and determining the corresponding attribute value processing strategy according to the attribute type, wherein the attribute type comprises one of a single value attribute, a multi-value attribute, a reserved attribute, a dependent attribute; and processing policy according to the determined attribute value, based on the attribute value provided by the entity information source corresponding to the attribute, generating the fusion attribute value of the attribute).
Claim 11, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the plurality of instructions cause the at least one processor to input, to a language model, a direction that includes the representative attribute values of at least some of the plurality of types of attributes for the target cluster and that causes the language model to generate a sentence indicating personality, and output the information indicating the representative personality of a user belonging to the target cluster based on output of the language model for the input (page 2, [4] and page 7, par [7]-[10], obtain the target entity belongs to a plurality of attribute values of a plurality of attribute, wherein the entity information source " bean curd sheet of Zhang Guorong of the page ", "Baidu Baike's Zhang Guorong introduction page" has its corresponding identification Fusion-1, Fusion-2, and the entity information source is represented by its URL coding, respectively is url-1, url-2, the attribute value obtained from the page of the opening of the broad bean curd sheet is: (corresponding to the attribute of the "video representation"), "Spring and summer autumn" (corresponding to the attribute of the "song representation"), and the " " attribute "of" the " " the " " hegemonig "(corresponding to the" song " attribute); The attribute value of the attribute of the "film and television representation" attribute, which is obtained from the Zhang Guorong of Baidu Pake, is "Spike Sixiance", "The Soul of the Queen", and the attribute value "silence" corresponding to the attribute of the "song representation", "I", "Monica).
Claim 12, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the plurality of instructions cause the at least one processor to select some of the plurality of types of attributes based on the contribution degree, wherein the plurality of instructions cause the at least one processor to input, to a language model, a direction that includes the representative attribute values of the selected some of the plurality of types of attributes and that causes the language model to generate a sentence indicating personality, and output the information indicating the representative personality of the plurality of users belonging to the target cluster based on output of the language model for the input (page 2, par. [1]-[4] and page 3, par. [5], certain attributes (e.g., "representation" attribute), but for other attributes (e.g., "birthplace" attribute, etc.), when processing with the full-reservation mode, on the one hand, it will bring a large number of repeating attribute values, increasing the storage overhead; on the other hand, it also brings hidden trouble of storing error attribute value, resulting in the accuracy of the generated knowledge map is reduced; obtaining entity information cluster of the target entity, the target entity has a plurality of attributes, the entity information cluster corresponding to a plurality of entity information source, each attribute corresponding to at least one entity information source, for each attribute, in the entity information cluster comprises providing at least one entity information source identifier of the attribute, and the attribute value provided by the entity information source; for each attribute of the plurality of attributes of the target entity, determining the attribute type of the attribute, and determining the corresponding attribute value processing strategy according to the attribute type, wherein the attribute type comprises one of a single value attribute, a multi-value attribute, a reserved attribute, a dependent attribute; and processing policy according to the determined attribute value, based on the attribute value provided by the entity information source corresponding to the attribute, generating the fusion attribute value of the attribute).
Claim 13, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses the plurality of instructions cause the at least one processor to input, to a language model, a direction that includes the relative values of at least some of the plurality of types of attributes for the target cluster and that causes the language model to generate a sentence indicating personality, and output the information indicating the representative personality of a user belonging to the target cluster based on output of the language model for the input (page 2, [4] and page 7, par [7]-[10], obtain the target entity belongs to a plurality of attribute values of a plurality of attribute, wherein the entity information source " bean curd sheet of Zhang Guorong of the page ", "Baidu Baike's Zhang Guorong introduction page" has its corresponding identification Fusion-1, Fusion-2, and the entity information source is represented by its URL coding, respectively is url-1, url-2, the attribute value obtained from the page of the opening of the broad bean curd sheet is: (corresponding to the attribute of the "video representation"), "Spring and summer autumn" (corresponding to the attribute of the "song representation"), and the " " attribute "of" the " " the " " hegemonig "(corresponding to the" song " attribute); The attribute value of the attribute of the "film and television representation" attribute, which is obtained from the Zhang Guorong of Baidu Pake, is "Spike Sixiance", "The Soul of the Queen", and the attribute value "silence" corresponding to the attribute of the "song representation", "I", "Monica).
Claim 14, the combination of Xu, Cheng and Saranathan discloses the invention as claimed. In addition, Cheng discloses input, to a language model, a direction that is based on the representative attribute value and the contribution degree and that causes the language model to generate a sentence for generating an image indicating personality (page 12, par. [2], for the target entity in FIG. 2 B, Zhang Guorong, if the ordering result for the entity information source of the attribute "video representation" is as follows: Chang Kuo-jung, a hundred-hundred department, describes the pages of the leaflets. then the entity information source " Baidu Baike of Zhang Guorong introduction page " the attribute value of " Dongxian xi toxin ", the qian humor is compared with the attribute value of the " hegemonibye " from the entity information source " bean sauce ", the attribute value is different, for example, the attribute value of the attribute value of the entity information source " bean curd sheet " of the " hegemonibye " is added to the attribute value included in the entity information source " Baidu Baike of Zhang Guorong introduction page ", finally obtaining the most sequenced entity information source comprising the attribute value " Dongcun ", " the " the " the); and
- input, to an image generation model, a generation direction for an image based on output of the language model for the input, and output, as the information indicating the representative personality of a user belonging to the target cluster, information including the image that is output from the image generation model (page 2, [4] and page 7, par [7]-[10], obtain the target entity belongs to a plurality of attribute values of a plurality of attribute, wherein the entity information source " bean curd sheet of Zhang Guorong of the page ", "Baidu Baike's Zhang Guorong introduction page" has its corresponding identification Fusion-1, Fusion-2, and the entity information source is represented by its URL coding, respectively is url-1, url-2, the attribute value obtained from the page of the opening of the broad bean curd sheet is: (corresponding to the attribute of the "video representation"), "Spring and summer autumn" (corresponding to the attribute of the "song representation"), and the " " attribute "of" the " " the " " hegemonig "(corresponding to the" song " attribute); The attribute value of the attribute of the "film and television representation" attribute, which is obtained from the Zhang Guorong of Baidu Pake, is "Spike Sixiance", "The Soul of the Queen", and the attribute value "silence" corresponding to the attribute of the "song representation", "I", "Monica).
Claim 15, is an information processing method for performing the system of claim 1. Therefore, it is rejected under the same rationale as claim 1 above.
Claim 16, is a non-transitory computer readable storage medium claim having instruction for executing the system of claim 1. Therefore, it is rejected under the same rationale as claim 1 above.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Xu, Cheng and Saranathan, and further in view of Manning et al. (US 2017/0031919), herein after “Manning”
Claim 17, the combination of Xu, Cheng and Saranathan discloses the invention as claimed, except “the plurality of instructions cause the at least one processor to classify the plurality of users into the plurality of clusters by applying a Gaussian Mixture Model (GMM) to the attribute value of each of the plurality of types of attributes stored in association with each of the plurality of users”.
Meanwhile, Manning discloses the plurality of instructions cause the at least one processor to classify the plurality of users into the plurality of clusters by applying a Gaussian Mixture Model (GMM) to the attribute value of each of the plurality of types of attributes stored in association with each of the plurality of users (par. [0029]-[0030], , Another benefit of using Gaussian mixture models is that Gaussian mixture models assume that artist vectors have been generated from a mixture of Gaussians with various means and variances. The closer an artist vector is to the mean of a particular category's Gaussian, the better the match the artist is for that category).
Therefore, it would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the system of the cited references to include the feature as Manning to assume that artist vectors have been generated from a mixture of Gaussians with various means and variances for creating content items that are intended to be presented to users for selection, grouping content items by genre provides an indication of relationship among grouped items.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure (see PTO-892).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Loan T. Nguyen whose telephone number is (571) 270-3103. The examiner can normally be reached on Monday from 10:00 am - 6:00 pm, Thursday-Friday from 10:00 am - 2:00 pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aleksandr Kerzhner can be reached on (571) 270-1760. The fax phone number for the organization where this application or proceeding is assigned is 571-270-4103. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
09/14/2026
/LOAN T NGUYEN/ Examiner, Art Unit 2165
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