DETAILED ACTION
This Non-Final communication is in response to Application No. 18/670,319 filed 5/21/2024. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claims 1-21 have been examined.
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 3, 10, and 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.
Regarding claim 3, (and similarly in claims 10 and 17), “the standard client form” lacks antecedent basis in the claims.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 4-8, 11-15, and 18-21, as best understood, are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
The independent claim(s) recite(s) at least “evaluating a client form structure comprising one or more generic fields for a client system of the plurality of client systems in a form specific language …, including analyzing one or more client forms from the client system …”, and “determining a relational map between the one or more generic fields in the client form structure for the client system and one or more standard fields in a standard form structure”. These limitations are construed as abstract ideas for being performable in the human mind or on paper. A human can certainly evaluate a client forms in some form specific language for the fields and determine a mapping between the client form fields and standard form fields by comparing versions of the forms side by side such as when they are paper forms.
This judicial exception is not integrated into a practical application because the additional limitations of “a plurality of client systems” and “an artificial intelligence (AI) model” are merely generic computing components on which the instructions to implement the abstract idea are applied. The “receiving a plurality of client forms …” and “looking up a client configuration of the client system …” is insignificant pre-solution activity as data gathering. Additional limitations directed toward mere instructions to apply the exception to generic computing components and insignificant extra-solution activity, alone or in combination, do not integrate the judicial exception into a practical application (See MPEP§2106.05(f) and §2106.05(g)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements identified above, being directed toward mere instructions to apply the exception to generic computing components and insignificant extra-solution activity, alone or in combination, are well-understood routine and conventional, do not provide an inventive concept, and thus, do not amount to significantly more than the judicial exception. Therefore, the independent claims are directed toward ineligible subject matter.
Dependent claims 4-7, 11-14, and 18-21 recite additional limitations that are also construed as additional abstract ideas for similar reasons as above, and are, therefore, also directed toward ineligible subject matter.
Claim Rejections - 35 USC § 102
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.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 4-8, 11-15 and 18-21, as best understood, is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kundu et al. (US 2024/0071047 A1, published 2/29/2024).
Regarding claim 1, Kundu teaches a method of automatic form conversion comprising:
receiving a plurality of client forms from a plurality of client systems. More specifically, Figure 1 depicts part of the process for mapping keys (fields) of forms to standard fields of standard forms (Kundu, abstract, [0002], [0027]-[0029]). Figure 2 depicts the process of training the machine learning model used in the mapping process (Kundu, [0045], [0051]).
evaluating a client form structure comprising one or more generic fields for a client system of the plurality of client systems in a form specific language by an artificial intelligence (AI) model, including analyzing one or more client forms from the client system by the AI model. More specifically, a form recognizer and machine learning models extract the field/value pairs and any variant words or phrases that may be semantically the same from forms in a specific language format such as PDF (Kundu, [0029], [0051]).
looking up a client configuration of the client system by the AI model. More specifically, the standardized field/value pairs and forms referenced and used by the models are customized for each client (Kundu, [0034], [0051], [0055], [0064]-[0065], [0076], [0079]-[0080]).
determining a relational map between the one or more generic fields in the client form structure for the client system and one or more standard fields in a standard form structure. More specifically, the field/value pairs are mapped to standard field/value pairs of a form type (standard form structure) by the machine learning models (Kundu, [0035], [0045], [0070]).
Regarding claim 4, Kundu teaches the method of claim 1, wherein said analyzing the one or more client forms from the client system by the AI model comprises identifying the one or more generic fields configured to represent one or more common items in the client form structure by the AI model, and wherein said determining the relational map comprises mapping between the one or more generic fields in the client form structure and the corresponding one or more standard fields configured to represent the one or more common items in the standard form structure. More specifically, for different form documents, different versions of a same form document, or the same form document but provided by different parties, different key formats are used for a common item. The disclosure includes constructing a Knowledge Graph containing popular standard formats of keys (e.g., “standard keys”) and developing machine learning models and associated processes to automatically map an extracted key (e.g., a “Custom Key” or “Input Key”) to a Standard Key (Kundu, [0020]-[0021], [0030]).
Regarding claim 5, Kundu teaches the method of claim 4, wherein the client form structure is common across the plurality of client systems including a first client system and a second client system of the plurality of client systems identified as a client system field in the client form structure, and wherein at least one or more generic fields configured to store corresponding one or more common items in the client form structure for the first client system are different from at least one or more generic fields configured to store the corresponding at least one or more items in the client form structure for the second client system. More specifically, for different form documents, different versions of a same form document, or the same form document but provided by different parties, different key formats are used for a common item. The disclosure includes constructing a Knowledge Graph containing popular standard formats of keys (e.g., “standard keys”) and developing machine learning models and associated processes to automatically map an extracted key (e.g., a “Custom Key” or “Input Key”) to a Standard Key (Kundu, [0020]-[0021], [0030]).
Regarding claim 6, Kundu teaches the method of claim 1, further comprising: determining by the AI model at least one of meaning and context associated with each generic field of the one or more generic fields based on the client configuration. More specifically, the process of using AI to map fields of an input form to fields of a standardized form includes determining a context - identifying an input form type associated with standard form types (“layer 0” – custom client configuration - Kundu, [0034], [0051], [0055], [0064]-[0065], [0076], [0079]-[0080]), and from there ranking pairings of input fields and standard fields on the likelihood of having the same meaning (“layer 2”) (Kundu, [0035]-[0037], [0040]-[0042], Figure 1). The AI models are trained with popular field phrases and domain specific phrases used for standard fields of standard forms (Kundu, [0045]-[0048]). The AI models are capable of determining the semantic meaning of words or phrases, and specifically whether the input fields are determined to be semantically similar or the same as standard fields (Kundu, [0050], [0073]).
Regarding claim 7, Kundu teaches the method of claim 6, wherein said determining the at least one of meaning and context comprises: analyzing one or more client text strings in each generic field based on the client configuration; and associating each generic field with the at least one of meaning and context represented by the one or more client text strings. More specifically, the process of using AI to map fields of an input form to fields of a standardized form includes determining a context - identifying an input form type associated with standard form types (“layer 0”), and from there ranking pairings of input fields and standard fields on the likelihood of having the same meaning (“layer 2”) (Kundu, [0035]-[0037], [0040]-[0042], Figure 1). The AI models are trained with popular field phrases and domain specific phrases used for standard fields of standard forms (Kundu, [0045]-[0048]). The AI models are capable of determining the semantic meaning of words or phrases, and specifically whether the input fields are determined to be semantically similar or the same as standard fields (Kundu, [0050], [0073]).
Regarding claims 8 and 11-14, these claims recite the non-transitory computer-readable storage medium with instructions for performing the steps of the method of claims 1 and 4-7, therefore, the same rationale of rejection is applicable.
Regarding claims 15 and 18-21, these claims recite the system for performing the steps of the method of claims 1 and 4-7, therefore, the same rationale of rejection is applicable.
Claim Rejections - 35 USC § 103
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.
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(s) 2, 9, and 16, as best understood, is/are rejected under 35 U.S.C. 103 as being unpatentable over Kundu, and further in view of Dettman et al. (US 10,120,844 B2, hereinafter “Dettman”)
Regarding claim 2, Kundu teaches the method of claim 1, and while Kundu generates mappings for each input form based on an identified (standard) form type, Kundu may not explicitly teach every aspect of using a previously created mapping for another form, or more specifically, further comprising: analyzing another client form from the client system by the AI model; and converting the other client form into the standard form structure based on the relational map.
Dettman discloses techniques for transforming input documents having disparate formats into a normalized (standard) format. According to one embodiment, a plurality of fields is identified in an input document that has a given format. Each field includes a descriptor and text content associated with the descriptor. For each field, semantic properties are evaluated for the descriptor and text content against a plurality of mapping rules to determine whether the field is consistent with one of a plurality of fields of a target format (Dettman, abstract; col 1, lines 11-14). The input documents, which are supplied from different sources (clients), are converted to the normalized (standard) documents based on previously established mapping rules (Dettman, col 3, lines 30-50; col 4, line 29-36; col 5, lines 29-34).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention given the teachings of Kundu and Dettman that a method for automatic form conversion where mappings between fields of client forms and fields of standard forms are established would include that a previously established mapping would be used to convert other forms. With Kundu and Dettman disclosing mapping fields of client forms to fields of standard forms, and with Dettman additionally disclosing the input documents, which are supplied from different sources (clients), are converted to the normalized (standard) documents based on previously established mapping rules, one of ordinary skill in the art of implementing a method for automatic form conversion where mappings between fields of client forms and fields of standard forms are established would include that a previously established mapping would be used to convert other forms in order to save on form processing where the mappings can be re-used. One would therefore be motivated to combine these teachings as in doing so would create this method for automatic form conversion where mappings between fields of client forms and fields of standard forms are established.
Regarding claim 9, this claim recites the non-transitory computer-readable storage medium with instructions for performing the steps of the method of claim 2, therefore, the same rationale of rejection is applicable.
Regarding claim 16, this claim recites the system for performing the steps of the method of claim 2, therefore, the same rationale of rejection is applicable.
Claim(s) 3, 10, and 17, as best understood, is/are rejected under 35 U.S.C. 103 as being unpatentable over Kundu and Dettman, and further in view of Oppenlander et al. (US 2006/0288269 A1, hereinafter “Oppenlander”).
Regarding claim 3, Kundu and Dettman teach the method of claim 2, however, may not explicitly teach every aspect of further comprising: printing the one or more generic fields in the other client form as the one or more standard fields in the standard client form based on the relational map.
Oppenlander discloses a method for generating and delivering an electronic form to a user. The method involves mapping fields of standard form into a form file (Oppenlander, abstract). The completed form file is a format ready for printing (Oppenlander, [0048], [0067]).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention given the teachings of Kundu and Dettman with Oppenlander that a method for automatic form conversion where mappings between fields of client forms and fields of standard forms are established would include printing the forms after the fields have been mapped to the fields of a standard form. With Kundu, Dettman, and Oppenlander disclosing mapping fields of client forms to fields of standard forms, and with Oppenlander additionally disclosing that mapping to standard forms is used for printing, one of ordinary skill in the art of implementing a method for automatic form conversion where mappings between fields of client forms and fields of standard forms are established would include printing the forms after the fields have been mapped to the fields of a standard form in order to have forms be consistent and correct versions when printed as required by banks and auto-dealerships. One would therefore be motivated to combine these teachings as in doing so would create this method for automatic form conversion where mappings between fields of client forms and fields of standard forms are established.
Regarding claim 10, this claim recites the non-transitory computer-readable storage medium with instructions for performing the steps of the method of claim 3, therefore, the same rationale of rejection is applicable.
Regarding claim 17, this claim recites the system for performing the steps of the method of claim 3, therefore, the same rationale of rejection is applicable.
Pertinent Prior Art
The prior art made of record on form PTO-892 and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
Dua (US 2019/0087463 A1) – semantically mapping an input form to an electronic form standard.
Gormish (US 8,732,570 B2) – creating and using a mapping to fill forms.
D’Oria (US 11,406,455 B2) - converting legacy electronic forms and static electronic documents to web-fillable electronic forms.
Coquard (US 11,934,771 B2) - transforming an unstructured set of data representing a standardized form to a structured set of data.
Ye (US 8,850,304 B2) - mapping fields of various electronic forms to a common object model, uses the mapping data to automatically populate corresponding fields of the forms.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PATRICK F RIEGLER whose telephone number is (571)270-3625. The examiner can normally be reached M-F 9:30am-6:00pm, ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kieu Vu can be reached at (571) 272-4057. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PATRICK F RIEGLER/ Primary Examiner, Art Unit 2171
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