Detailed Action
This action is in response to amendments filed on 01/05/2026.
This action is in response to application filed on 08/10/2023 which is continuation of application no. 17/390748 (now U.S. patent # 11748554 B2) filed on 07/30/2021.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are canceled.
Claims 21-23, 25-31, 33-40 are pending.
Claims 21-23, 25-31, 33-40 are rejected.
Applicant's Response
In Applicant's Response dated 01/05/2026, Applicant amended claims 21, 29, and 37. Applicant argued against various rejections previously set forth in the Office Action mailed on 09/05/2025.
In light of applicant’s amendments/remarks, all rejections of claims under 35 U.S.C. 101 set forth previously are withdrawn.
Allowable Subject Matter
Claims 22, 23, 25, 30-31, 33, and 38-40 would be allowable if rewritten to include all the limitation of its parent claim and all intervening claims, and further amended to overcome non-statutory double patenting rejections as note below.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 21, 26-29, and 34-37 are rejected under the judicially created doctrine of obviousness-type double patenting as being unpatentable over claims 1-2, 6-8, and 12 of U.S. Patent No. 11748554 B2 in view of Ebeling et al. (US 20170270113 A1, referred herein after as D1) and/or in view of Jiang et al. (US 20190205743 A1, referred hereinafter as D3) in view of Goyal (US 20150339282 A1, referred hereinafter as D4). Although the conflicting claims are not identical, they are not patentably distinct from each other because all the limitation of claims 21, 26-29, and 34-37 are disclosed by claims 1-2, 6-8, and 12 of U.S. Patent No. 11748554 B2 (see table below for claim mapping) and/or claims are merely in different statutory categories; however, U.S. Patent No. 11748554 B2 does not expressly disclose the following limitations:
receiving a plurality of second documents, the plurality of second documents including the one or more amendments to the first document, the plurality of second documents including the plurality of second characters; applying the machine learning model to the plurality of second documents to identify one or more content sections corresponding to a plurality of amendments in the plurality of second documents and one or more types of amendments corresponding to the plurality of amendments, the machine learning model identifying the one or more content sections and the one or more types of amendments based on the at least one first character and the at least one second character in the plurality of second characters in the plurality of second documents; generating the amended first document based on the first document and including the plurality of amendments corresponding to the identified one or more content sections identified by the machine learning model; and generating the graphical user interface displaying the amended first document.
determine, using the machine learning model, a first probability indicating a likelihood of the identified content section in the second document having the at least one second character is related to a content section in the first document having the at least one first character;
the graphical user interface displaying a selectable interface element; and upon receiving a selection of the selectable interface element, performing, using the at least one processor, one or more actions associated with the amended first document, the performing of the one or more actions includes at least one of: executing an approval action associated with the amended first document, executing a disapproval action associated with the amended first document, executing an update action for updating one or more content sections in the plurality of content sections, or any combination thereof.
However, D1, D3, and D4 discloses the above limitations (also as noted under 103 rejection headings below).
Firstly, D1 (figure 5, 7, 10A-10B and text, 0017, 0048, 0067-0071) feature “a”.
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention, as disclosed, to include the teachings of D1 as noted above. This would have been obvious for the purpose automatically inserting highly relevant/correct data into fields/sections of a document as disclosed by D1.
Secondly, combination of D1 and D3 discloses features “b”. For instance, D1(figure 5, 7, 10A-10B and text, 0017, 0048, 0067-0071) discloses all limitation of features “b” except for a first probability indicating a likelihood of [relation]; however, D3 (abstract, 0061, figure 2, 4) discloses generating, based on extracted content features/words/sentence, a text similarity score between the pair of messages using a second neural network, combining the generated text similarity score with additional data associated with the messages to generate a total similarity score, and generating a message thread based on the generated total similarity score for the pair of messages selected from the plurality of unstructured messages. It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention, to include the teachings of D3. This would have been obvious for the purpose automatically inserting/detangling content to make it for easier consumption/understanding by users as disclosed by D3(0002).
D4 (0026, 0073-0076) discloses the graphical user interface displaying a selectable interface element; and upon receiving a selection of the selectable interface element, performing, using the at least one processor, one or more actions associated with the amended first document, the performing of the one or more actions includes at least one of: executing an approval action associated with the amended first document, executing a disapproval action associated with the amended first document, executing an update action for updating one or more content sections in the plurality of content sections, or any combination thereof.
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention, disclosed in D1, to include the teachings of D4. This would have been obvious with predicable results of providing users with ability to approve and reject amendments to a document as disclosed by D4.
Instant Application
U.S. Patent #11748554 B2
Claim 21
Claims 1, 2
Claim 22
Claim 23
Claim 25
Claim 26
Claim 27
Claim 6
Claim 28
Claim 6
Claim 29
Claim 7, 8, or claim 13
Claim 30
Claim 31
Claim 33
Claim 34
Claim 35
Claim 12
Claim 36
Claim 12
Claim 37
Claim 7, 8
Claim 38
Claim 39
Claim 40
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
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 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.
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.
Claim, 21, 26-28, 29, and 34-37, rejected under 35 U.S.C. 103 as being unpatentable over Ebeling et al. (US 20170270113 A1, referred herein after as D1) in view of Jiang et al. (US 20190205743 A1, referred hereinafter as D3) in view of Goyal (US 20150339282 A1, referred hereinafter as D4).
As per claim 21, D1 discloses,
A computer implemented method, comprising, (D1, title, abstract).
receiving, using at least one processor, a first document and a second document, the second document including one or more amendments to the first document, the first document including a plurality of first characters, and the second document including a plurality of second characters, (D1, figure 5, , 7, 10A-10B and text discloses receiving, using at least one processor, a first document (e.g. see figure 10B) and a second document (e.g. emails, conversations, text messages, files, documents etc.), the second document including one or more amendments to the first document (e.g. emails/messages includes one or more amendments related to document being discussed) , the first document including a plurality of first characters, and the second document including a plurality of second characters).
applying, using the at least one processor, a machine learning model to the first and second documents to identify a content section in a plurality of content sections corresponding to at least one amendment in the one or more amendments in the second document and a type of amendment corresponding to the at least one amendment, (D1, figure 5, , 7, 10A-10B and text, 0017, 0048, 0067-0071 discloses receiving, using at least one processor, a first document (e.g. see figure 10B) and a second document (e.g. emails, conversations, text messages, files, documents etc.), the second document including one or more amendments to the first document (e.g. emails/messages includes one or more amendments related to document being discussed), and applying, using the at least one processor, a machine learning model/algorithms/machine learning processing to the first and second documents to identify a content section/portions in a plurality of content sections in a document that matches/corresponds to at least one amendment in the one or more amendments in the second document and a type of amendment corresponding to the at least one amendment (e.g. either insert or not the amendment based on parsing keywords/determined relevance.)).
the machine learning model identifying the content section and the type of amendment based on at least one first character in the plurality of first characters and at least one second character in the plurality of second characters, (D1, figure 5, , 7, 10A-10B and text, 0017, 0048, 0067-0071 discloses applying, using the at least one processor, a machine learning model/algorithms to the first and second documents to identify a content section/portions in a plurality of content sections in a document that matches/corresponds to at least one amendment in the one or more amendments in the second document and a type of amendment corresponding to the at least one amendment (e.g. either insert or not the amendment based on parsing keywords/determined relevance.), the machine learning model identifying the content section and the type of amendment based on at least one first character in the plurality of first characters and at least one second character in the plurality of second characters (e.g., attribute data, metadata, keywords are matched in order to determine what content to insert a document.).
determining using the machine learning model,… the identified content section in the second document having the at least one second character is related to a content section in the first document having the at least one first character, (D1, figure 5, , 7, 10A-10B and text, 0017, 0048, 0067-0071 discloses determining, using the machine learning model/algorithm/machine learning processing,… the identified content section in the second document having the at least one second character is related to a content section in the first document having the at least one first character (e.g. attribute data, metadata, keywords are matched in order to determine what content to insert at particular section/location of document.).
generating, using the at least one processor, an amended first document based on the first document and including the at least one amendment corresponding to the identified content section identified by the machine learning model, (D1, figure 5, 7, 10A-10B and text, 0017, 0048, 0067-0071 discloses generating, using the at least one processor, an amended first document based on the first document and including the at least one amendment corresponding (e.g. user communication/amendments) to the identified content section identified by the machine learning model/algorithms.).
and generating, using the at least one processor, a graphical user interface displaying the amended first document and indicating the at least one amendment and the identified type of the at least one amendment in the amended first document, (D1, figure 5, 7, 10A-10B and text, 0017, 0048, 0067-0071 discloses generating, using the at least one processor, a graphical user interface displaying the amended first document (e.g. see figures 10A-10B) and indicating the at least one amendment and the identified type of the at least one amendment in the amended first document (e.g. annotation indicating insertion/addition and author).).
D1 fails to expressly disclose – [determining/generating] a first probability indicating a likelihood of [relation between messages/characters/content].
D3 (abstract, 0061, figure 2, 4) discloses generating, based on extracted content features/words/sentence, a text similarity score between the pair of messages using a second neural network, combining the generated text similarity score with additional data associated with the messages to generate a total similarity score, and generating a message thread based on the generated total similarity score for the pair of messages selected from the plurality of unstructured messages
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention, disclosed in D1, to include the teachings of D3. This would have been obvious for the purpose automatically inserting/detangling content to make it for easier consumption/understanding by users as disclosed by D3(0002).
D1/D3 discloses executing an update action for updating one or more content sections in the plurality of content sections; however, D1/D3 fails to expressly disclose - the graphical user interface displaying a selectable interface element; and upon receiving a selection of the selectable interface element, performing, using the at least one processor, one or more actions associated with the amended first document, the performing of the one or more actions includes at least one of: executing an approval action associated with the amended first document, executing a disapproval action associated with the amended first document, executing an update action for updating one or more content sections in the plurality of content sections, or any combination thereof.
D4 (0026, 0073-0076) discloses the graphical user interface displaying a selectable interface element; and upon receiving a selection of the selectable interface element, performing, using the at least one processor, one or more actions associated with the amended first document, the performing of the one or more actions includes at least one of: executing an approval action associated with the amended first document, executing a disapproval action associated with the amended first document, executing an update action for updating one or more content sections in the plurality of content sections, or any combination thereof.
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention, disclosed in D1, to include the teachings of D4. This would have been obvious with predicable results of providing users with ability to approve and reject amendments to a document as disclosed by D4.
As per claim 26, the rejection of claim 21 further incorporated, D1 discloses,
further comprising receiving a plurality of second documents, the plurality of second documents including the one or more amendments to the first document, the plurality of second documents including the plurality of second characters, (D1, figure 5, , 7, 10A-10B and text discloses receiving any number of documents including a plurality of second documents, the plurality of second documents including the one or more amendments to the first document, the plurality of second documents including the plurality of second characters (E.g. emails, text message etc.)).
applying the machine learning model to the plurality of second documents to identify one or more content sections corresponding to a plurality of amendments in the plurality of second documents and one or more types of amendments corresponding to the plurality of amendments, the machine learning model identifying the one or more content sections and the one or more types of amendments based on the at least one first character and the at least one second character in the plurality of second characters in the plurality of second documents; generating the amended first document based on the first document and including the plurality of amendments corresponding to the identified one or more content sections identified by the machine learning model; and generating the graphical user interface displaying the amended first document, (D1, figure 5, , 7, 10A-10B and text, 0017, 0048, 0067-0071 discloses applying the machine learning model to the plurality of second documents to identify one or more content sections corresponding to a plurality of amendments in the plurality of second documents and one or more types of amendments corresponding to the plurality of amendments (e.g. either insert or not the amendment based on parsing keywords/determined relevance.), the machine learning model identifying the one or more content sections and the one or more types of amendments based on the at least one first character and the at least one second character in the plurality of second characters in the plurality of second documents (e.g., attribute data, metadata, keywords are matched in order to determine what content to insert a document.) and generating the amended first document based on the first document and including the plurality of amendments corresponding to the identified one or more content sections identified by the machine learning model; and generating the graphical user interface displaying the amended first document (e.g. see figures 10A-10B).).
As per claim 27, the rejection of claim 21 further incorporated, D1 discloses,
wherein the type of amendment includes at least one of the following: an addition amendment, a substitution amendment, a deletion amendment, a modification amendment, and any combinations thereof, (D1, title, abstract, figure 5, 7, 10A-10B, 0017, 0048, 0067-0071 and accompanying text determining amendments type being of “inclusion” type, and further discloses/shows displaying the amended original/first document comprises displaying, within the document interface, adjacent to any amendment, information about the amendment, the information including at least one of: an identifier corresponding to which amendment document of the set of amendment documents includes the amendment, the type of amendment, and a timing identifier corresponding to the amendment document of the set of amendment documents that includes the amendment (e.g. see figure 10A-10B including user identifier, timing, other metadata information regarding amendments.)).
As per claim 28, the rejection of claim 21 further incorporated, D1 discloses,
wherein the displaying the amended first document includes displaying, within the graphical user interface, adjacent to the at least one amendment, information about the at least one amendment, the information including at least one of: an identifier of the second document, the type of amendment, a timing identifier corresponding to the second document, and any combinations thereof, (D1, title, abstract, figure 5, 7, 10A-10B, 0017, 0048, 0067-0071 and accompanying text determining amendments type being of “inclusion” type, and further discloses/shows displaying the amended original document comprises displaying, within the document interface, adjacent to any amendment, information about the amendment, the information including at least one of: an identifier corresponding to which amendment document of the set of amendment documents includes the amendment, the type of amendment, and a timing identifier corresponding to the amendment document of the set of amendment documents that includes the amendment (e.g. see figure 10A-10B including user identifier, timing, other metadata information regarding amendments.)).
As per claims 29, and 34-37:
Claims 29, 34-37 are system and medium claims corresponding to method claims 21, 26-28 and are of substantially same scope.
Accordingly, claims 29, 34-37 are rejected under the same rational as set forth for claims 21, 26-28.
Response to Arguments
Applicant’s arguments filed on 01/05/2026 have been fully considered but they are not persuasive and/or moot in view new grounds of rejections.
Applicant argues that “first probability…” is different from “similarity score” (response page 20).
The examiner disagrees.
D3 (0061, figure 2, 4) discloses generating, based on extracted content features/words/sentence, a text similarity score between the pair of messages using a second neural network, combining the generated text similarity score with additional data associated with the messages to generate a total similarity score. The examiner notes that similarity score quantitively indicates the likelihood or degree that two pair of content/text are related, and as such clearly reads on “first probability” as claimed.
Accordingly, applicant’s argument is not persuasive.
Conclusion
Applicant's amendment necessitated any 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 extension fee 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 date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
See form 892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MUSTAFA A AMIN whose telephone number is (571)270-3181. The examiner can normally be reached on Monday-Friday from 8:00 AM to 5:00 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kevin Young, can be reached on 571-270-3180. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MUSTAFA A AMIN/ Primary Examiner, Art Unit 2194