DETAILED ACTION
1. This is a Final Office Action Correspondence in response to arguments/amendments U.S. Application No. 18/544229 filed on May 14, 2026.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Applicant
3. The Applicant is encouraged to contact the Examiner in hopes of reaching a resolution in light of compact prosecution.
Response to Arguments
4. Applicant’s arguments have been considered but are not persuasive.
On Pg. 11 of remarks in regards to 35 U.S.C. 103, relating to claim 21, Applicant argues the amended limitations.
Examiner replies that a Eshghi teaches this limitation. Par. 0077 Eshghi discloses identifying the features between documents and the location of the features. The location of the features is seen as the structure of the particular target data object.
On pg. 12-14 of remarks in regards to 35 U.S.C. 103, relating to claim 21, Applicant argues the Eshghi does not teach extracting content. Par. 0069-0071 Eshghi discloses matching the representative document structure with the content objects of the feature vectors to form document clusters. The extracted client data is matched to the representative document structure. The matched data is seen as the structural comparison of the particular target data object and the particular reference object. The extracted data is seen as the set of content. The client data contain objects and the representative document structure contains objects. Fig. 5 and Par. 0054-0056 Eshghi discloses the documents are stored in document clusters as templates.
Claim Rejections - 35 USC § 103
5. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
6. 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.
7. Claim(s) 21-40 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eshghi et al. U.S. Patent Application Publication No. 2022/0108065 (herein as ‘Eshghi’) and further in view of Saraswat et al. U.S. Patent Application Publication No. 2019/0205636 (herein as ‘Saraswat’).
As to claim 21 Eshghi teaches a computer-implemented method, comprising:
obtaining, at a service of a cloud computing environment, from a client via one or more programmatic interfaces, an indication of a plurality of reference objects which are to be utilized to extract content of one or more target data objects of the client (Par. 0052 Eshghi discloses the user devices are with a user in the server environment. Par. 0105 Eshghi discloses the system within a cloud-based environment. Par. 0056-0058 Eshghi discloses the user providing user input as content with the content being matched to attributes within the document templates. The identified attributes are seen as the indication. The attributes within the document templates are the reference objects. The user content is seen as the target data object);
wherein individual ones of the reference objects and the one or more target data objects comprise at least a document having a structure (Par. 0077 Eshghi discloses identifying the features between documents and the location of the features. The location of the features is seen as the structure of the particular target data object);
extracting, based at least in part on a structural comparison of a particular target data object of the client and a particular reference object of the plurality of reference objects indicated by the client via the one or more programmatic interfaces, a set of content from the particular target data object (Par. 0069-0071 Eshghi discloses matching the representative document structure with the content objects of the feature vectors to form document clusters. The extracted client data is matched to the representative document structure. The matched data is seen as the structural comparison of the particular target data object and the particular reference object. The extracted data is seen as the set of content. The client data contain objects and the representative document structure contains objects. Fig. 5 and Par. 0054-0056 Eshghi discloses the documents are stored in document clusters as templates);
transmitting, from the service to the client via the one or more programmatic interfaces, the set of content extracted from the particular target data object of the client, (Par. 0069-0071 Eshghi discloses matching the representative document structure with the content objects of the feature vectors to form document clusters. The extracted client data is matched to the representative document structure. The matched data is seen as the structural comparison of the particular target data object and the particular reference object. The extracted data is seen as the set of content. The client data contain objects and the representative document structure contains objects. Fig. 5 and Par. 0054-0056 Eshghi discloses the documents are stored in document clusters as templates. The templates are used to respond to user input. Using the templates in response to user input is seen as transmitting set of content);
Eshghi does not teach but Saraswat teaches receiving, an explanation request pertaining to the set of content extracted from the particular target data object, transmitting, to the client from the service via the one or more programmatic interfaces, an indication of at least the particular reference object of the plurality of reference objects indicated by the client via the one or more programmatic interfaces (Par. 0031 Sarawat discloses an interface for displaying information to the user and receiving information from the user. Par. 0038 Sarasway discloses the dictionary is created a keyword extraction algorithms. Par. 0041 Saraswat discloses the user sending a request for feedback to update a dictionary. The dictionary performs verification with the match quality indicator being used to verify and identify terms and once identified the key-value pair is stored with the associated document. Par. 0045 Saraswat discloses presenting as output the key-value pairs. The user using the interface to provide information and view information is seen as transmits an indication of the particular reference object. The identified verification of the matching term by the key-value pair is seen as the indication. The document is seen as the reference object. In response to the explanation request is seen as the verification of the new key term included in the dictionary).
Eshghi and Saraswat are analogous art because they are in the same field of endeavor, machine learning. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the machine learning techniques of Eshghi to include the identifier of Saraswat, to identify relevant data within unstructured documents (Par. 0002 Saraswat).
As to claim 22 Eshghi in combination with Saraswat teaches each and every limitation of claim 21.
In addition Eshghi teaches wherein the structural comparison comprises computing an estimate of a difference in (a) a location of a particular key of a key-value pair within the particular reference object and (b) a location of the particular key of the key-value pair within the particular target data object, wherein the set of content comprises a value corresponding to the particular key (Par. 0077 Eshghi discloses comparing the subject features to a set of respective features for identifying the features between documents and the location of the features to produce a matching score. Par. 0077 Eshghi discloses the comparison between the features in the template document and the subject content objects can be based upon the location of features. The matching score is seen as the difference).
As to claim 23 Eshghi in combination with Saraswat teaches each and every limitation of claim 21.
In addition Eshghi teaches further comprising: transmitting, from the service to the client via the one or more programmatic interfaces, an indication of a confidence level associated with at least a portion of the set of content extracted from the particular target data object (Par. 0077 Eshghi discloses the matching score are based upon the features of the content objects).
As to claim 24 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 21.
In addition Eshghi teaches further comprising: providing, from the service to the client via the one or more programmatic interfaces, an annotation associated with the particular reference object, wherein the annotation is generated from the particular reference object via an automated tool, and wherein the annotation indicates a key of a key-value pair identified within the particular reference object (Par. 0041 Saraswat discloses the match quality indicator being used to verify and identify terms and once identified the key-value pair is stored with the associated document. The key-value pair is seen as the annotation, the particular reference object is seen as the document).
As to claim 25 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 21.
In addition Eshghi teaches wherein the particular reference object comprises one or more of: (a) text, (b) one or more images, (c) one or more videos, or (d) one or more audio segments (Par. 0026-0027 Eshghi discloses documents).
As to claim 26 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 21.
In addition Eshghi teaches further comprising:
in response to receiving, at the service, from the client via the one or more programmatic interfaces, a request to extract content from the particular target data object, directing, to a repository within which respective representations of at least the plurality of reference objects are stored, a search query pertaining to the particular target data object, wherein the search query is prepared based at least in part on a preliminary analysis of the particular target data object (Par. 0046 Eshghi discloses searching for different document templates to identify which document template matches the content objects. The identified template contains attributes that match the query content objects);
and obtaining, from the repository in response to the search query, an indication of the particular reference object (Par. 0046 Eshghi discloses when the subject content object matches the document template, the subject content object is associated with the object metadata. The stored association is seen as the indication of the particular reference object).
As to claim 27 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 26.
In addition Eshghi teaches wherein the preliminary analysis comprises performing optical character recognition on the particular target data object, and wherein a parameter of the search query comprises a text token identified as a result of performing the optical character recognition (Par. 0021 Eshghi discloses the optical character recognition).
As to claim 28 Eshghi teaches a system, comprising: one or more computing devices; wherein the one or more computing devices include instructions that upon execution on or across the one or more computing devices cause the one or more computing devices to:
obtain, at a service of a cloud computing environment, from a client via one or more programmatic interfaces, an indication of a plurality of reference objects which are to be utilized to extract content of one or more target data objects of the client (Par. 0052 Eshghi discloses the user devices are with a user in the server environment. Par. 0105 Eshghi discloses the system within a cloud-based environment. Par. 0056-0058 Eshghi discloses the user providing user input as content with the content being matched to attributes within the document templates. The identified attributes are seen as the indication. The attributes within the document templates are the reference objects. The user content is seen as the target data object);
wherein individual ones of the reference objects and the one or more target data objects comprise at least a document having a structure (Par. 0077 Eshghi discloses identifying the features between documents and the location of the features. The location of the features is seen as the structure of the particular target data object);
extract, based at least in part on a structural comparison of a particular target data object and a particular reference object of the plurality of reference objects indicated by the client via the one or more programmatic interfaces, a set of content from the particular target data object (Par. 0069-0071 Eshghi discloses matching the representative document structure with the content objects of the feature vectors to form document clusters. The extracted client data is matched to the representative document structure. The matched data is seen as the structural comparison of the particular target data object and the particular reference object. The extracted data is seen as the set of content. The client data contain objects and the representative document structure contains objects. Fig. 5 and Par. 0054-0056 Eshghi discloses the documents are stored in document clusters as templates);
transmit, from the service to the client via the one or more programmatic interfaces, the set of content extracted from the particular target data object of the client, (Par. 0069-0071 Eshghi discloses matching the representative document structure with the content objects of the feature vectors to form document clusters. The extracted client data is matched to the representative document structure. The matched data is seen as the structural comparison of the particular target data object and the particular reference object. The extracted data is seen as the set of content. The client data contain objects and the representative document structure contains objects. Fig. 5 and Par. 0054-0056 Eshghi discloses the documents are stored in document clusters as templates. The templates are used to respond to user input. Using the templates in response to user input is seen as transmitting set of content);
Eshghi does not teach but Saraswat teaches and, receive an explanation request pertaining to the set of content extracted from the particular target data object, transmit, to the client from the service via the one or more programmatic interfaces and in response to the explanation request, an indication of at least the particular reference object of the plurality of reference objects indicated by the client via the one or more programmatic interfaces (Par. 0031 Sarawat discloses an interface for displaying information to the user and receiving information from the user. Par. 0038 Sarasway discloses the dictionary is created a keyword extraction algorithms. Par. 0041 Saraswat discloses the user sending a request for feedback to update a dictionary. The dictionary performs verification with the match quality indicator being used to verify and identify terms and once identified the key-value pair is stored with the associated document. Par. 0045 Saraswat discloses presenting as output the key-value pairs. The user using the interface to provide information and view information is seen as transmits an indication of the particular reference object. The identified verification of the matching term by the key-value pair is seen as the indication. The document is seen as the reference object. In response to the explanation request is seen as the verification of the new key term included in the dictionary).
Eshghi and Saraswat are analogous art because they are in the same field of endeavor, machine learning. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the machine learning techniques of Eshghi to include the identifier of Saraswat, to identify relevant data within unstructured documents (Par. 0002 Saraswat).
Eshghi does not teach but Mishra teaches the indication of at least the particular reference object provided as an explanation pertaining to the set of extracted content (Par. 0058 Mishra discloses requesting additional information known as sub resource content related to extracted information from a main resource content. The additional information known as sub resource content is seen as particular reference object provided as an explanation).
Eshghi and Mishra are analogous art because they are in the same field of endeavor, machine learning. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the machine learning techniques of Eshghi to include the additional needed information of Mishra, to prevent the user from waiting for important information related to requested content (Par. 0007-0008 Mishra).
As to claim 29 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 28.
In addition Eshghi teaches wherein the structural comparison comprises computing an estimate of a difference in (a) a location of a particular key of a key-value pair within the particular reference object and (b) a location of the particular key of the key-value pair within the particular target data object, wherein the set of content comprises a value corresponding to the particular key (Par. 0077 Eshghi discloses comparing the subject features to a set of respective features for identifying the features between documents and the location of the features to produce a matching score. Par. 0077 Eshghi discloses the comparison between the features in the template document and the subject content objects can be based upon the location of features. The matching score is seen as the difference).
As to claim 30 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 28.
In addition Eshghi teaches wherein the one or more computing devices include further instructions that upon execution on or across the one or more computing devices further cause the one or more computing devices to: transmit, from the service to the client via the one or more programmatic interfaces, an indication of a confidence level associated with at least a portion of the set of content extracted from the particular target data object (Par. 0077 Eshghi discloses the matching score are based upon the features of the content objects).
As to claim 31 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 28.
In addition Eshghi teaches wherein the one or more computing devices include further instructions that upon execution on or across the one or more computing devices further cause the one or more computing devices to: provide, from the service to the client via the one or more programmatic interfaces, an annotation associated with the particular reference object, wherein the annotation is generated from the particular reference object via an automated tool, and wherein the annotation indicates a key of a key-value pair identified within the particular reference object (Par. 0041 Saraswat discloses the match quality indicator being used to verify and identify terms and once identified the key-value pair is stored with the associated document. The key-value pair is seen as the annotation, the particular reference object is seen as the document).
As to claim 32 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 28.
In addition Eshghi teaches wherein the particular reference object comprises one or more of: (a) text, (b) one or more images, (c) one or more videos, or (d) one or more audio segments (Par. 0026-0027 Eshghi discloses documents).
As to claim 33 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 28.
In addition Eshghi teaches wherein the one or more computing devices include further instructions that upon execution on or across the one or more computing devices further cause the one or more computing devices to:
in response to receiving, at the service, from the client via the one or more programmatic interfaces, a request to extract content from the particular target data object, direct, to a repository within which respective representations of at least the plurality of reference objects are stored, a search query pertaining to the particular target data object, wherein the search query is prepared based at least in part on a preliminary analysis of the particular target data object (Par. 0046 Eshghi discloses searching for different document templates to identify which document template matches the content objects);
and obtain, from the repository in response to the search query, an indication of the particular reference object (Par. 0046 Eshghi disclose when the subject content object matches the document template, the subject content object is associated with the object metadata).
As to claim 34 Eshghi in combination with Saraswat and Mishra teaches each and every limitation of claim 33.
In addition Eshghi teaches wherein the preliminary analysis comprises performing optical character recognition on the particular target data object, and wherein a parameter of the search query comprises a text token identified as a result of performing the optical character recognition (Par. 0021 Eshghi discloses the optical character recognition).
As to claim 35 Eshghi teaches one or more non-transitory computer-accessible storage media storing program instructions that when executed on or across one or more processors cause the one or more processors to:
obtain, at a service of a cloud computing environment, from a client via one or more programmatic interfaces, an indication of a plurality of reference objects which are to be utilized to extract content of one or more target data objects of the client (Par. 0052 Eshghi discloses the user devices are with a user in the server environment. Par. 0105 Eshghi discloses the system within a cloud-based environment. Par. 0056-0058 Eshghi discloses the user providing user input as content with the content being matched to attributes within the document templates. The identified attributes are seen as the indication. The attributes within the document templates are the reference objects. The user content is seen as the target data object);
extract, based at least in part on a structural comparison of a particular target data object and a particular reference object of the plurality of reference objects indicated by the client via the one or more programmatic interfaces, a set of content from the particular target data object (Par. 0069-0071 Eshghi discloses matching the representative document structure with the content objects of the feature vectors to form document clusters. The extracted client data is matched to the representative document structure. The matched data is seen as the structural comparison of the particular target data object and the particular reference object. The extracted data is seen as the set of content. The client data contain objects and the representative document structure contains objects. Fig. 5 and Par. 0054-0056 Eshghi discloses the documents are stored in document clusters as templates);
wherein individual ones of the reference objects and the one or more target data objects comprise at least a document having a structure (Par. 0077 Eshghi discloses identifying the features between documents and the location of the features. The location of the features is seen as the structure of the particular target data object);
transmit, from the service to the client via the one or more programmatic interfaces, a set of content extracted from a particular target data object of the client, (Par. 0069-0071 Eshghi discloses matching the representative document structure with the content objects of the feature vectors to form document clusters. The extracted client data is matched to the representative document structure. The matched data is seen as the structural comparison of the particular target data object and the particular reference object. The extracted data is seen as the set of content. The client data contain objects and the representative document structure contains objects. Fig. 5 and Par. 0054-0056 Eshghi discloses the documents are stored in document clusters as templates. The templates are used to respond to user input. Using the templates in response to user input is seen as transmitting set of content);
Eshghi does not teach but Saraswat teaches and, in response to an explanation request pertaining to the set of content extracted from the particular target data object of the client, transmit, to the client from the service via the one or more programmatic interfaces, an indication of at least the particular reference object of the plurality of reference objects indicated by the client via the one or more programmatic interfaces (Par. 0031 Sarawat discloses an interface for displaying information to the user and receiving information from the user. Par. 0038 Sarasway discloses the dictionary is created a keyword extraction algorithms. Par. 0041 Saraswat discloses the user sending a request for feedback to update a dictionary. The dictionary performs verification with the match quality indicator being used to verify and identify terms and once identified the key-value pair is stored with the associated document. Par. 0045 Saraswat discloses presenting as output the key-value pairs. The user using the interface to provide information and view information is seen as transmits an indication of the particular reference object. The identified verification of the matching term by the key-value pair is seen as the indication. The document is seen as the reference object. In response to the explanation request is seen as the verification of the new key term included in the dictionary).
Eshghi and Saraswat are analogous art because they are in the same field of endeavor, machine learning. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the machine learning techniques of Eshghi to include the identifier of Saraswat, to identify relevant data within unstructured documents (Par. 0002 Saraswat).
As to claim 36 Eshghi in combination with Saraswat teaches each and every limitation of claim 35.
In addition Eshghi teaches wherein the structural comparison comprises computing an estimate of a difference in (a) a location of a particular key of a key-value pair within the particular reference object and (b) a location of the particular key of the key-value pair within the particular target data object, wherein the set of content comprises a value corresponding to the particular key (Par. 0077 Eshghi discloses comparing the subject features to a set of respective features for identifying the features between documents and the location of the features to produce a matching score. Par. 0077 Eshghi discloses the comparison between the features in the template document and the subject content objects can be based upon the location of features. The matching score is seen as the difference).
As to claim 37 Eshghi in combination with Saraswat teaches each and every limitation of claim 35.
In addition Eshghi teaches storing further program instructions that when executed on or across the one or more processors further cause the one or more processors to: transmit, from the service to the client via the one or more programmatic interfaces, an indication of a confidence level associated with at least a portion of the set of content extracted from the particular target data object (Par. 0077 Eshghi discloses the matching score are based upon the features of the content objects).
As to claim 38 Eshghi in combination with Saraswat teaches each and every limitation of claim 35.
In addition Eshghi teaches storing further program instructions that when executed on or across the one or more processors further cause the one or more processors to: provide, from the service to the client via the one or more programmatic interfaces, an annotation associated with the particular reference object, wherein the annotation is generated from the particular reference object via an automated tool, and wherein the annotation indicates a key of a key-value pair identified within the particular reference object (Par. 0041 Saraswat discloses the match quality indicator being used to verify and identify terms and once identified the key-value pair is stored with the associated document. The key-value pair is seen as the annotation, the particular reference object is seen as the document).
As to claim 39 Eshghi in combination with Saraswat teaches each and every limitation of claim 35.
In addition Eshghi teaches wherein the particular reference object comprises one or more of:(a) text, (b) one or more images, (c) one or more videos, or (d) one or more audio segments (Par. 0026-0027 Eshghi discloses documents).
As to claim 40 Eshghi in combination with Saraswat teaches each and every limitation of claim 35.
In addition Eshghi teaches storing further program instructions that when executed on or across the one or more processors further cause the one or more processors to:in response to receiving, at the service, from the client via the one or more programmatic interfaces, a request to extract content from the particular target data object,direct, to a repository within which respective representations of at least the plurality of reference objects are stored, a search query pertaining to the particular target data object, wherein the search query is prepared based at least in part on a preliminary analysis of the particular target data object (Par. 0046 Eshghi discloses searching for different document templates to identify which document template matches the content objects);
and obtain, from the repository in response to the search query, an indication of the particular reference object (Par. 0046 Eshghi disclose when the subject content object matches the document template, the subject content object is associated with the object metadata).
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Hoehne et al. U.S. Patent No. 11,281,928 (herein as ‘Hoehne’). Hoehne discloses disclosed herein are system, method, and computer program product embodiments for querying document terms and identifying target data from documents. In an embodiment, a document processing system may receive a document and a query string. The document processing system may perform optical character recognition to obtain character information and positioning information for the characters of the document. The document processing system may generate a two-dimensional character grid for the document. The document processing system may apply a convolutional neural network to the character grid and the query string to identify target data from the document corresponding to the query string. The convolutional neural network may then produce a segmentation mask and/or bounding boxes to identify the targeted data.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/J.A.M/ August 13, 2026Examiner, Art Unit 2159
/AMRESH SINGH/Primary Examiner, Art Unit 2159
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