DETAILED ACTION
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.
Applicant's submission filed on 12/30/2025 has been entered. Claims 1, 10 & 19 were amended. Claims 1-20 are pending.
Response to Arguments
Applicant’s arguments with respect to the prior art rejection of claims 1, 10 & 19 have been fully considered but are not persuasive. Page 2 of iText teaches fully automated solutions for data recognition in a PDF document, including identifying text patterns (numeric, currency sign, etc) which corresponds to a regular expression search. Further, a fully automated solution for text pattern data recognition in a PDF file would imply that the entire file is scanned and reaches an end of file character, thus signaling the end of file has been reached.
Applicant’s arguments directed to the newly added limitations have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground of rejection is made in view of a newly identified prior art reference.
The examiner observes that previously, the three independent claims (i.e., claims 1, 10 & 19) recited similar limitations. However, the Response filed 12/30/2025 amended claim 19 to omit the “provide” step newly added to claims 1 & 10. It is unclear to the examiner if this was intentional.
Claim Rejections - 35 USC § 112(b)
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 1-20 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.
Upon a thorough review of claim 1, several indefiniteness issues were identified. The examiner is presenting the issues in a footnote format as this is believed to be, in this instance, the most convenient way to identify the limitations they are paired with.
Claims 7 and 8 are also discussed below.
The remaining claims are rejected due to their dependency on claim 1. Claims 10-18 recite limitations corresponding to claims 1-9, respectively, and are rejected for the same reasons discussed above. Claims 19 & 20 recite limitations corresponding to claims 1 & 8, respectively, and are rejected for the same reasons discussed above.
1. A system comprising:
a data conversion platform, comprising:
a processor; and
memory storing computer-readable instructions that, when executed by the processor, cause the data conversion platform to:
receive, via a network, a first input data1 comprising a file, wherein the file is in a first format of a plurality of formats corresponding to a first source computing system and comprising printable and non-printable characters;
identify, based on a count2 of characters imported3 from the file being less than a threshold upon reaching an end of the file, the file as an image file;
convert the file from a first image format to a second image format, wherein the second image format comprises improved contrast from the first image format;
perform,4 optical character recognition of the file in the second image format;
import the first input data as a string based on identification of a format5 associated with the first source computing system6;
generate, based on a second count of imported7 characters of the first input data being less than the threshold, an error;
provide, based on the error and to a data conversion system8, training feedback comprising one or both of an updated pattern in a pattern data store9 and a mapping in a mapping data store;
generate, based on an input pattern file, a first array from pattern matches10 identified from the imported first input data;
generate, based on a configuration file, a second array comprising matches between an input information format11 and an output information format12;
send, automatically via the network and based on generation of the second array, output data as an output file and in a format13 capable of being processed by an application computing system as second input data; and
trigger, automatically and based on an indication the output file is received at the application computing system, processing of the output file by the application computing system; and
the application computing system comprising:
a second processor; and
second memory storing second instructions that, when executed by the second processor, cause the application computing system to:
import, automatically upon receipt of the output file, the output file, wherein the output file is in a second format incompatible with the first format; and
perform an operation based on the second input data of the output file received from the data conversion platform.
7. (Original) The system of claim 1, wherein the output data is formatted as an extensible markup language (XMIL) file14.
8. (Original) The system of claim 1, wherein the instructions further cause the data conversion platform to:15
import characters from the first input data;
compare a count16 of imported characters to a threshold; and
perform, based on the count of imported characters not meeting the threshold, optical character recognition on the first input data.
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over:
Pallmann (USPN 6,094,684, hereinafter “Pallmann”) in view of
iText: pdf2Data” by iText (published/crawled on 10/25/2020 at Internet Archive Wayback Machine, hereinafter “iText”), in view of
“Improving Optical Character Recognition Techniques” by Ramesh et al. (published in 2018, hereinafter “Ramesh”), and further in view of
Jain et al. (USPN 10,162,850, hereinafter “Jain”).
Regarding claim 1, Pallmann teaches
A system comprising:
a data conversion platform, comprising: a processor; and memory storing computer-readable instructions that, when executed by the processor, cause the data conversion platform to:
receive, via a network [Pallmann, Fig. 1 (116) & (118)], a first input data comprising a file, wherein the file is in a first format of a plurality of formats corresponding to a first source computing system and comprising printable and non-printable characters [Pallmann, Fig. 13, Col. 5, lines 48-56, Col. 5-6, lines 64-3, “The data source 104 in system 100 can be as remote as on another continent … the data source 104 is a computer”; Col. 5-6, lines 64-3, “data 108 of the data source 104 is in some format such as text”, “data 108 is in a text format, a report format (i.e. a text file with a repeating pattern of information) or a Hypertext Markup Language (HTML) format”; Col. 6, lines 23-36, “filter textual data, the machine 102 can be instructed to ignore lines of the source data 120 that are blank, or that contain certain text values”; Col. 6, lines 39-42, “user to instruct machine 102 to skip headers, footers, and non-data lines and pages”];
import the first input data as a string based on identification of a format associated with the first source computing system [Pallmann, Fig. 27, Fig. 31A; Col. 5-6, lines 64-3, “data 108 is in a text format, a report format (i.e. a text file with a repeating pattern of information) or a Hypertext Markup Language (HTML) format”; Col. 6, lines 23-36, “filter textual data, the machine 102 can be instructed to ignore lines of the source data 120 that are blank, or that contain certain text values”; Col. 6, lines 39-42, “user to instruct machine 102 to skip headers, footers, and non-data lines and pages”];
generate, based on an input pattern file, a first array from pattern matches identified from the imported first input data [Pallmann, Fig. 19, Fig. 5A-5C; Col. 12, lines 34-48, “FIGS 5A, 5B and 5C illustrate the link notation parameters defined for machine 102. A link is composed of one or more sections. A section is identified by a line containing a section name, enclosed in square brackets. In the machine 102, fifteen section names have been defined: Link, Word, WordPerfect, WordPro, Excel, Quattro, 1-2-3, Access, Paradox, Approach, Notes, html, email, IE and Netscape. Other section names could be defined in other embodiments or by plug-ins. A link may contain additional sections for target application-specific parameters, network type parameters, or other areas in which extensibility is desired”; col. 11, lines 26-31, “link notation enables the machine 102 to provide a consistent interface to the modules 306, 308, 310, 312, 314 and 316 and plug-in modules that are or might be used to accomplish the various processing tasks”; Col. 12, lines 32-33, “machine 102, links are stored on a disk in a \Links subdirectory, having the file type .lk.”];
generate, based on a configuration file, a second array comprising matches between an input information format and an output information format [Pallmann, Fig. 9; Col. 38, lines 16-28, “data mapping module 312 parses the filtered, normalized textual data in the file 120' into fields using the page, line, column, width, cell and fieldname field-definition parameters of the Mapping parameter … provide formatting information”, “DM module 312 uses the Mapping parameter to assign the field name and number specified by the cell field-definition parameter to the data from the file 120' specified by the page, line, column and width field-definition parameters”; Col. 38, lines 29-40];
send, automatically via the network and based on generation of the second array, output data as an output file and in a format capable of being processed by an application computing system as second input data [Pallmann, Col. 38, lines 29-40 , “DM module 312 reads the record, divides the record into data fields based on the link's Mapping parameter values and passes to the data target 106 the record as mapped into data fields”; Fig. 10; Col. 39, lines 26-35, “AI module transmits the mapped data from the data mapping module 312 to a target application using a communication method allowed by the target application, the computer 112 and the operating system of computer 112”, “AI module 316 locates and launches the desired target application”]; and
trigger, automatically and based on an indication the output file is received at the application computing system, processing of the output file by the application computing system [Pallmann, Col. 38, lines 44-51, “DM module 312 launches the appropriate target application using the AI module 316. For example, if the target application is Excel, the DM launches Excel using the AI module. If the target application is Word, the DM launches Word using the AI module”; Fig. 9, Fig. 10; Col. 39, lines 26-35, “AI module 316 locates and launches the desired target application”]; and
the application computing system comprising: a second processor; and second memory storing second instructions that, when executed by the second processor, cause the application computing system to [Pallmann, Fig. 1 (106)]:
import, automatically upon receipt of the output file, the output file, wherein the output file is in a second format incompatible with the first format [Pallmann, Fig. 1, Fig. 10; Col. 7, lines 28-43, “Machine 102 may deliver the delivered data 122 to a target application in a manner that instructs the target application to create a new target file 110 to Save the data 122, for example. The data may be delivered in a manner that instructs the target application to import the data 122 to the end of a preexisting target file 110, for example. Or the data may be delivered in a manner that instructs the target application to import the data 122 to a Specified location in target file 110.”; Fig. 10; Col. 39, lines 26-35, “AI module 316 locates and launches the desired target application”]; and
perform an operation based on the second input data of the output file received from the data conversion platform [Pallmann, Col. 38, lines 44-51, “DM module 312 launches the appropriate target application using the AI module 316. For example, if the target application is Excel, the DM launches Excel using the AI module. If the target application is Word, the DM launches Word using the AI module”; Col. 7, lines 28-43, “data 122 delivered to a data target shall be called the delivered data 122. When machine 102 delivers the delivered data 122 to a data target 106 that is an application program (i.e. a target application), machine 102 can instruct the target application program to handle the data 122 in a specified manner. Machine 102 may deliver the delivered data 122 to a target application in a manner that instructs the target application to create a new target file 110 to save the data 122, for example. The data may be delivered in a manner that instructs the target application to import the data 122 to the end of a preexisting target file 110, for example. Or the data may be delivered in a manner that instructs the target application to import the data 122 to a specified location in target file 110”].
Pallmann does not explicitly teach identify, based on a count of characters imported from the file being less than a threshold, the file as an image file.
However, iText teaches identify, based on a count of characters imported from the file being less than a threshold upon reaching an end of the file, the file as an image file [iText, page 2, “Typical Rules Are” section; and page 7, “Practical Guidelines” section].
Pallmann and iText are analogous art because they are in the same field of endeavor, data conversion. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Pallmann with the data extraction and conversion techniques taught in iText to achieve the predictable result of a comprehensive solution for obtaining available text. See also Pallmann’s column 2, lines 34-39 and column 3, lines 21-42.
The combination of Pallmann and iText does not explicitly teach convert the file from a first image format to a second image format, wherein the second image format comprises improved contrast from the first image format; and perform, optical character recognition of the file in the second image format.
However, Ramesh teaches
convert the file from a first image format to a second image format, wherein the second image format comprises improved contrast from the first image format [Ramesh, page 362, § 3.1.3, binarization]; and
perform, optical character recognition of the file in the second image format [Ramesh, page 363, § 3.2].
Pallmann, iText and Ramesh are analogous art because they are in the same field of endeavor, data conversion. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Pallmann and iText with the further discussion of OCR techniques for extracting text from images to achieve the predictable result of a comprehensive solution for obtaining available text. See also Ramesh’s Abstract section.
The combination of Pallmann, iText and Ramesh does not explicitly teach “generate, based on a second count of imported characters of the first input data being less than the threshold, an error; and provide, based on the error and to a data conversion system, training feedback comprising one or both of an updated pattern in a pattern data store and a mapping in a mapping data store”.
However, Jain teaches
generate, based on a second count of imported characters of the first input data being less than the threshold, an error [Jain, column 16, lines 16-28, character counts and column 29, lines 23-30, errors presented to users to receive feedback]; and
provide, based on the error and to a data conversion system, training feedback comprising one or both of an updated pattern in a pattern data store and a mapping in a mapping data store [Jain, column 25, lines 42-53, feedback on machine learning model used to retrain that model].
Pallmann, iText, Ramesh, and Jain are analogous art because they are in the same field of endeavor, data conversion. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Pallmann, iText, and Ramesh with the machine learning models and training feedback taught by Jain to achieve the predictable improvements that come with machine learning processes.
Regarding claim 2, the combination of Pallmann, iText, Ramesh, and Jain teaches the system of claim 1, wherein the data conversion platform is integrated, at least in part, within the application computing system [iText, page 9, “Conclusion” section].
Regarding claim 3, the combination of Pallmann, iText, Ramesh, and Jain teaches the system of claim 1, wherein the first input data is incompatible with the application computing system [iText, page 9, “Conclusion” section].
Regarding claim 4, the combination of Pallmann, iText, Ramesh, and Jain teaches the system of claim 1, wherein the instructions further cause the data conversion platform to:
identify a file format of the first input data [iText, page 2, “What is it?” section]; and
import, based on the file format, the printable and non-printable characters from the first input data [iText, page 2, “What is it?” section].
Regarding claim 5, the combination of Pallmann, iText, Ramesh, and Jain teaches the system of claim 1, wherein the instructions further cause the data conversion platform to:
identify a file format of the first input data [iText, page 2, “Typical Rules Are” section]; and
perform, based on an identification of an image file, optical character recognition to identify characters within the first input data [iText, page 2, “Typical Rules Are” section]; and
import identified characters from the first input data [iText, page 2, “Typical Rules Are” section].
Regarding claim 6, the combination of Pallmann, iText, Ramesh, and Jain teaches the system of claim 5, wherein the first input data is a pdf document [iText, page 2, “What is it?” section].
Regarding claim 7, the combination of Pallmann, iText, Ramesh, and Jain teaches the system of claim 1, wherein the output data is formatted as an extensible markup language (XML) file [iText, page 7, targetXML].
Regarding claim 8, the combination of Pallmann, iText, Ramesh, and Jain teaches the system of claim 1, wherein the instructions further cause the data conversion platform to:
import characters from the first input data [iText, page 7, “Practical Guidelines” section];
compare a count of imported characters to a threshold [iText, page 7, “Practical Guidelines” section]; and
perform, based on the count of imported characters not meeting the threshold, optical character recognition on the first input data [iText, page 7, “Practical Guidelines” section].
Regarding claim 9, the combination of Pallmann, iText, Ramesh, and Jain teaches the system of claim 8, wherein the instructions further cause the data conversion platform to convert the first input data to gray scale before performing optical character recognition [Ramesh, page 362, § 3.1.3, binarization].
Claims 10-18 recite limitations corresponding to claims 1-9, respectively, and are rejected for the same reasons discussed above.
Claims 19 & 20 recite limitations corresponding to claims 1 & 8, respectively, and are rejected for the same reasons discussed above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Scott A. Waldron whose telephone number is (571)272-5898. The examiner can normally be reached Monday - Friday 9:00 am - 5:00 pm.
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, Neveen Abel-Jalil can be reached at (571)270-0474. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Scott A. Waldron/Primary Examiner, Art Unit 2152 01/10/2026
1 Applicant appears to use “first input data” and “file” interchangeably throughout the claims, sometimes even in adjoining limitations. These should be standardized throughout because operations done to the file are not always reflected in the first input data limitations.
2 Because Applicant has amended the claims to recite a “second count”, this limitation should be amended to recite “a first count”.
3 For clarity there should be an explicit “import” step created to distinguish from later “import” steps. This will help clarify which importation operation is referred to by making all of them explicit.
4 This comma should be deleted.
5 Is this another plurality of formats? It appears this operation will always happen because the file is an image file per the “receive” limitation. In other words, the plurality of formats correspond to it.
6 The “first input data” comprises a “file” and the file was already identified as an image in the steps above. How is it now imported as a string?
7 Which import step is this based on? The implicit (first) import above or the (second) import in the limitation directly above this one?
8 This specification appears to use “data conversion platform” and “data conversion system” interchangeably. However, it is unclear what the distinction in the specification is, and therefore, unclear what the distinction between the two is in the claims. Do they refer to the same thing as found in line 2 (data conversion platform) of this claim?
9 Is the “input pattern file” a part of the “pattern data store” below?
10 It is unclear what elements the matches are between. Compare this to the limitation directly below, which specifies it is “between an input information format and an output information format”.
11 Is this a “file format” as described above? There are several formats throughout the claims and it is unclear if they should be standardized due to amendments over time. Currently there are “first format”, “first image format”, “input information format”, “output information format”, “a format capable of being processed by an application computing system”, “second format”, and claim 4 & 5’s “file format”. Should some of these be consolidated for clarity?
12 See footnote 11.
13 See footnote 12.
14 It appears this describes a file format, and possibly should be referred to that way, consistent with the issues discussed in footnote 11.
15 The examiner cannot be certain, but it is possible claim 8 raises a § 112(d) issue for failure to further limit claim 1. Claim 1 already recites importing characters, comparing a count to a threshold, and perform OCR based on it not meeting the threshold. However, the examiner is not making a § 112(d) rejection because he cannot be certain in light of the § 112(b) issues already raised.
16 It appears this should be referred to as “a third count” because two other count operations were recited in claim 1.