CTNF 18/923,251 CTNF 88395 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Information Disclosure Statement The information disclosure statement (IDS) submitted on 01/20/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Specification 06-16 AIA Applicant is reminded of the proper language and format for an abstract of the disclosure. The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details. The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided. 06-31 AIA The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 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 – 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15-03-aia AIA Claim s 1-5, 7-10, and 12-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by SMOCK et al. published on US 20220335240 A1 hereinafter “SMOCK” . Regarding claim 1. SMOCK discloses a method comprising: receiving, by a processing device, a document that includes a table ( 0030; Figure 1; “[0030] FIG. 1 is a block diagram of a document processing system 100 that receives documents 110, identifies tables using a trained table detection machine learning model 115 to identify table bounding boxes with corresponding confidence levels, crops the tables at a cropper 120 from the document using the table bounding boxes and uses a further trained table structure recognition and interpretation model 125 to identify potentially overlapping object bounding boxes within the tables as well as a confidence for each identified bounding box. In one example, there are six different types of bounding boxes or objects that the table structure recognition object detection model 125 is trained to recognize. ...” ); detecting, by the processing device and using a machine learning model, a cell in the table and a probability of whether the cell corresponds to a row header of the table ( 0034-0035; Figure 1; “[0034] The second three classes are column headers, row headers, and subheaders (also called “projected row headers”). These three object classes are used to interpret the table. They identify which cells contain access cells, or keys, and which cells contain data cells, or values. Column headers objects group together and identify the access cells that usually appear at the top of the table. Row header objects group together and identify the access cells that usually appear on the left of the table. A subheader is a special object class that appears in many tables presented within documents. A subheader occurs when a supercell coincides with a row. In this case, the content of the supercell is meant to join with one or more cells below it in the row header to form compound keys. This table design saves horizontal space, as it is equivalent to having an additional column of supercells in the leftmost portion of the row header.” ); aligning, by the processing device, a border of the cell along a horizontal axis of a row of the table ( 0030-0038; Figure 1; “[0032] The joint modeling of table structure recognition and table interpretation as an object detection problem is achieved using six object classes in one example. The terms object, container, and bounding box are used somewhat interchangeably. Bounding boxes for objects from different classes can coincide and potentially overlap with one or more other bounding boxes. Modeling the structure and interpretation of a table jointly in this way is a much more robust and efficient mechanism than modeling them independently in parallel or in sequence. The model 125 is trained with labeled images of tables, with the labels corresponding to the six different types of bounding boxes, which are referred to as objects, a nomenclature commonly used with object detection models.” ); and generating, by the processing device, a table structure based on the aligned cell and the probability, the table structure including the aligned cell assigned to the row ( 0029-0030; Figure 1; “[0029] A document processing system recognizes tables from various documents that do not contain structure information regarding the tables. The system generates structure information for the recognized tables enabling the selection, editing, and exporting of the data into multiple different applications.” ). Regarding claim 2. SMOCK discloses the method of claim 1, wherein the table structure further includes an indication of whether the cell is the row header ( 0065-0066; Figures 4-5; “[0065] The system 100 cropper 120 extracts the tables as shown at table 400 in FIG. 4 and at table 500 in FIG. 5. The table structure recognition and interpretation model 125 detects rows 401, 402, 403, 404, 405, 406, 407, and 408, columns 410, 411, 412, 413, 414, 415, 416, 417, 418, and 419, headers (column headers encompassing rows 401 and 402 and row header 410), and supercells for an isolated table, which are overlaid and displayed in FIG. 4, as overlapping bounding boxes. There are three supercells in FIG. 4, defined by cells intersecting row 401 and columns 412, 413, and 414, columns 415, 416, and 417, and columns 418 and 419.” ). Regarding claim 3. SMOCK discloses the method of claim 1, wherein the machine learning model is trained to detect the cell and the probability using supervised learning on a training dataset that includes training tables, ground truth bounding boxes surrounding training cells in the training tables, and ground truth classifications indicating whether the training cells represent row headers ( 0036 and 0038 ). Regarding claim 4. SMOCK discloses the method of claim 1, wherein the detecting the cell and the probability includes providing the document including the table and at least one non-table element as input to the machine learning model via different input channels ( 0030; Figure 1; “[0030] … identifies tables using a trained table detection machine learning model 115 to identify table bounding boxes with corresponding confidence levels, crops the tables at a cropper 120 from the document using the table bounding boxes and uses a further trained table structure recognition and interpretation model 125 to identify potentially overlapping object bounding boxes within the tables as well as a confidence for each identified bounding box. …” ), the different input channels including a first input channel of the document, a second input channel of text in the document, a third input channel of images in the document ( 0041; Figure 1 ), a fourth input channel of lines in the document, and a fifth input channel of font characteristics of the text in the document ( 0030, 0047 and 0063; Figures 1-2; “[0047] The properties of a cell in the structure representation include the row and column numbers it lies in; its role as either a column header, row header, subheader, or non-header (data) cell; and the words that it contains, represented either as a list of words or a text string. ...” ). Regarding claim 5. SMOCK discloses the method of claim 1, wherein the detecting the cell includes detecting multiple cells in the table, the method further comprising: detecting, by the processing device and using the machine learning model, an additional cell and an object probability assigned to the additional cell indicating a likelihood that the additional cell represents either a cell object or a table object ( 0107 ); and removing, by the processing device, the additional cell from the multiple cells based on the object probability falling below a threshold, resulting in a reduced subset of cells ( 0107; “[0107] Although a few embodiments have been described in detail above, other modifications are possible. For example, the logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. Other steps may be provided, or steps may be eliminated, from the described flows, and other components may be added to, or removed from, the described systems. Other embodiments may be within the scope of the following claims.” ). Regarding claim 7. SMOCK discloses the method of claim 1, wherein the detecting the cell includes detecting multiple cells in the table, the method further comprising: identifying, by the processing device, gaps in the table that are external to the multiple cells ( 0033 and 0076; Figures 10-12 ); inserting, by the processing device, additional cells to fill the gaps ( 0048 ); identifying, by the processing device, a portion of content of the table that spans two or more of the additional cells ( 0034 ); and generating, by the processing device, a merged cell by merging the two or more additional cells, wherein the table structure includes the merged cell ( 0033, 0048 and 0076; Figures 10-12 ). Regarding claim 8. SMOCK discloses the method of claim 1, wherein the aligning the border of the cell includes: aligning the cell within the row ( 0065-0066; Figures 3-5; “[0065] The system 100 cropper 120 extracts the tables as shown at table 400 in FIG. 4 and at table 500 in FIG. 5. The table structure recognition and interpretation model 125 detects rows 401, 402, 403, 404, 405, 406, 407, and 408, columns 410, 411, 412, 413, 414, 415, 416, 417, 418, and 419, headers (column headers encompassing rows 401 and 402 and row header 410), and supercells for an isolated table, which are overlaid and displayed in FIG. 4, as overlapping bounding boxes. There are three supercells in FIG. 4, defined by cells intersecting row 401 and columns 412, 413, and 414, columns 415, 416, and 417, ...” ) by performing at least one of: repositioning a first border of the cell to coincide with a first horizontal axis of the row ( 0065-0066; Figures 4-5; “[0066] In FIG. 5, the table structure recognition and interpretation model 125 detects rows 501, 502, 503, 504, 505, and 506, columns 510, 511, 512, and 513, headers (column header 501 and row header 510), and supercells (none present in this example) for the isolated table 500, which are overlaid and displayed here as overlapping bounded boxes.” ), and repositioning a second border of the cell to coincide with a second horizontal axis of the row ( 0065-0066; Figures 4-5 ); and aligning the cell within a column of the table ( 0065-0066; Figures 3-5 ) by performing at least one of: repositioning a third border of the cell to coincide with a first vertical axis of the column ( 0065-0066; Figures 4-5 ), and repositioning a fourth border of the cell to coincide with a second vertical axis of the column ( 0065-0066; Figures 4-5 ). Regarding claim 9. SMOCK discloses the method of claim 1, wherein the detecting the cell includes detecting multiple cells in the table, the method further comprising: detecting, by the processing device, a pair of overlapping cells of the multiple cells ( 0033, 0048 and 0076; Figures 1 and 10-12 ); and generating, by the processing device, refined cells by merging or separating the overlapping cells, a determination of whether to merge or separate the overlapping cells being based on a degree of overlap between the overlapping cells and border coordinates of additional cells adjacently surrounding the overlapping cells, wherein the table structure includes the refined cells ( 0033, 0048 and 0076; Figures 1 and 10-12 ). Regarding claim 10. SMOCK discloses the method of claim 1, wherein the detecting the cell includes detecting multiple cells in the table ( 0030; Figure 1 ), the method further comprising: identifying, by the processing device, a pair of adjacent cells of the multiple cells having a gap separating the adjacent cells that is devoid of the multiple cells ( 0048 ); and generating a repositioned cell by repositioning a first border of a first adjacent cell of the adjacent cells to coincide with a second border of a second adjacent cell of the adjacent cells, wherein the table structure includes the repositioned cell ( 0048 ). Regarding claim 12. SMOCK discloses the method of claim 1, wherein the detecting the cell includes detecting multiple cells in the table, and the generating the table structure includes: generating the row of the table by assigning a first group of the multiple cells to the row, the first group of the multiple cells having top or bottom borders within a first threshold distance from one another ( 0065-0066 and 0076-0078; Figures 2-5 and 10-12 ); and generating a column of the table by assigning a second group of the multiple cells to the column, the second group of the multiple cells having left or right borders within a second threshold distance of one another, wherein the table structure includes the row and the column ( 0065-0066 and 0076-0078; Figures 2-5 and 10-12 ). Regarding claim 13. SMOCK discloses the method of claim 1, wherein the generating the table structure includes calculating a cell span for the cell representing a number of rows and columns in the table that the cell spans based on a degree to which the cell overlaps the number of rows and columns, wherein the table structure includes the cell span ( 0048 and 0065-0066; Figures 4 and 5 ). Regarding claim 14. SMOCK discloses the method of claim 1, wherein the detecting the cell includes detecting multiple cells in the table and probabilities assigned to the multiple cells indicating whether respective cells in the table correspond to row headers of the table, and the generating the table structure includes classifying the cell as the row header based on the probabilities assigned to other cells that are within a same column as the cell ( 0034, 0065, 0077 and 0081; Figures 10-13 ). Regarding claim 15. SMOCK discloses the method of claim 1, wherein the detecting includes detecting multiple cells in the table and probabilities assigned to the multiple cells indicating whether respective cells in the table correspond to column headers of the table, and the generating the table structure includes classifying the cell as a column header based on the probabilities assigned to other cells that are within a same row as the cell ( 0034, 0065, 0077 and 0081; Figures 10-13 ). Regarding claim 16. SMOCK discloses the method of claim 1, further comprising assigning, by the processing device, a portion of table content of the table to the cell based on a degree of overlap between the portion of the table content and the cell ( 0002, 0030 and 0065-0066; Figures 3-5 ). Regarding claim 17. SMOCK discloses the method of claim 1, further comprising encoding, by the processing device, the table in a configuration file format or a markup language based on the table structure ( 0004, 0030, 0047 and 0050; Figures 1 ). Regarding claim 18. Claim 18 has similar limitations as to those treated in the above rejections, and are met by the reference as discussed above, and has been rejected for the same reasons of anticipations as used in the rejections above. Regarding claim 19. System claim 19 is drawn to the system corresponding to the method of using same as claimed in claim 1. Therefore, system claim 19 corresponds to method claim 1 and is rejected for the same reasons of anticipation as used above. Regarding claim 20. Non-transitory computer-readable medium claim 20 is drawn to the non-transitory computer-readable medium of using the corresponding to the method of using the same as claimed in claim 1. Therefore, non-transitory computer-readable medium claim 20 corresponds to the method claim 1, and is rejected for the same reasons of anticipation as used above . Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-20-02-aia AIA This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. 07-21-aia AIA Claim s 6 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over SMOCK as applied to claims 1 and 5 above, in view of Thompson et al. published on US 20220335240 A1 hereinafter “Thompson” . Regarding claim 6. SMOCK discloses the method of claim 5, but failed to further disclose comprising identifying, by the processing device, a portion of content in the table that is external to the reduced subset of cells, and reinstating the additional cell that contained the portion of the content prior to removal. Thompson, however, in the same field of endeavor, shows a method comprising identifying, by the processing device, a portion of content in the table that is external to the reduced subset of cells, and reinstating the additional cell that contained the portion of the content prior to removal ( 0402 and 0459; Figures 15A-D; “[0402] … a listing of detected tables and corresponding graphical representations is shown in FIG. 15A, with tables listed by page and table number (i.e., where multiple tables are found within a given page, the tables are associated with an identifier, here a sequential number), while FIG. 15B shows graphical representations of several pages of a dataset and corresponding tables identified therein (as indicated by broad black bounding boxes). Note the detection model advantageously identifies true tables, while not designating similar elements such as graphs, charts, etc. in the various pages of the test dataset. In addition, in some approaches a user may utilize the output shown in FIG. 15B to identify and/or designate additional tables, remove erroneously designated tables, etc. from the set output by the detection process.” ). It would have been obvious to the person of having ordinary skilled in the art to combine the teachings of modifying the table format as shown Thompson in the Inferring Structure Information From Table Images of SMOCK in order to receive documents that contains tables and effectively and efficiently process the information and yield predictive result. Regarding claim 11. SMOCK discloses the method of claim 1, further comprising: detecting, by the processing device and using the machine learning model, an additional cell of the table and table boundaries of the table ( 0030, 0039, 0057 and 0079; Figs. 1 and 13 ). SMOCK failed to explosively disclose generating a repositioned cell by repositioning an additional border of the additional cell to coincide with the table boundaries, wherein the table structure includes the repositioned cell. Thompson, however, in the same field of endeavor, shows generating a repositioned cell by repositioning an additional border of the additional cell to coincide with the table boundaries, wherein the table structure includes the repositioned cell ( 0144 ). The motivation used on the rejection of claim 6 to combine the Thompson prior art into the SMOCK prior art still applies to the rejection of claim 11. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ASMAMAW G TARKO whose telephone number is (571)272-7493. The examiner can normally be reached M-F: 8am-5pm EST. 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, Chris Kelley can be reached at (571) 272-7331. 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. /ASMAMAW G TARKO/ Primary Examiner, Art Unit 2482 Application/Control Number: 18/923,251 Page 2 Art Unit: 2482 Application/Control Number: 18/923,251 Page 3 Art Unit: 2482
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