DETAILED ACTION
This action is responsive to the application filed 8/23/2024.
Claims 1-10 are pending.
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.
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because the claim is directed to a structuring program. A program is software, and software per se does not constitute a process, machine, manufacture, or composition of matter within the scope of the statute.
Claim Rejections - 35 USC § 102
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.
Claims 1-5, 9 and 10 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Yashiro, et al., JP H0743718 (“Yashiro”). Citations in the following rejections are to the page numbers of the English translation attached to the provided reference.
With regard to Claim 1, Yashiro teaches a structuring device comprising: a processor configured to execute a program; and a storage device configured to store the program (p. 4, process is carried out on a multimedia document stored on a computer), wherein
a processing module pool that stores a plurality of processing modules capable of executing processing based on a feature related to a layout in document data, and a template data pool that stores template data in which two or more processing modules combined according to a dependency relationship among the plurality of processing modules are defined, are accessible (p. 6 describes that a common logical structure is expressed for documents in a certain class of existing documents. The document class and associated structure specifies the order which specific extraction tasks will be performed to identify and apply structure to the document. P. 11 describes that the system uses a common/specific logical structure relation table, which stores the common logical structure and indicates the processes to be performed to generate an instance of a specific logical structure), and the processor executes
acquisition processing of acquiring structuring target document data (p. 4 describes acquiring a color multimedia document stored in the storage device in the computer),
extraction processing of extracting specific template data from the template data pool based on a result of a selection input of a feature related to a layout of the structuring target document data acquired by the acquisition processing (p. 8 describes that data describing the format of the input document is read, in order to carry out the structure analysis process and call the correct routines for structuring the document), and
structuring processing of outputting first structured data in which the structuring target document data is structured by the feature related to the layout, by executing two or more specific processing modules forming the specific template data extracted by the extraction processing according to a dependency relationship among the two or more specific processing modules (pp. 10-11 describe that the common logical structure table which stores the common logical document structure is used to store each instance of a document for which the structure is determined as a child table identifying each input document for which the specific sequence of structuring processes has been executed to generate and store the structure for the specific document).
Claim 9 recites a method which is carried out by the device of Claim 1, and is similarly rejected. Claim 10 recites a program which implements the device of Claim 1, and is likewise rejected,
With regard to Claim 2, Yashiro teaches that the plurality of processing modules include a first processing module essential for any template data and a second processing module which is selectable according to the selection input. P. 4 describes that the process for any document requires a module which separates the document image into a single color text and figure/table part, and a full-color part related to images in the document. P. 5 describes that this document data is then input into the structure generation unit to generate the structure, which is carried out according to the determined common logical structure of the document.
With regard to Claim 3, Yashiro teaches that the first processing module includes a row extraction module that extracts a row element forming a row from the document data, a paragraph extraction module that extracts a paragraph element forming a paragraph based on the row element, and a detection module that detects whether the paragraph element corresponds to a heading, and in the structuring processing, the processor generates the first structured data by distinguishing between a paragraph element corresponding to the heading and a paragraph element not corresponding to the heading based on a detection result of the detection module. Pp. 8-9 describe that processing is performed for each row in a column area, after which paragraph processing is performed to identify paragraphs, where by processing line-by-line enables the paragraph identification to determine chapter/section titles.
With regard to Claim 4, Yashiro teaches that the first processing module includes a page coupling module that couples, based on the paragraph element, a leading paragraph element in a first page in the document data and a paragraph element at an end of a second page immediately preceding the first page, and in the structuring processing, the processor generates the first structured data by distinguishing between the paragraph element corresponding to the heading and the paragraph element not corresponding to the heading based on the detection result of the detection module and a page coupling result of the page coupling module. Pp. 10-11 describe that a chapter relation can relate the chapter title and paragraphs. The invention further functions by generating a relationship identifying when a separated logical structure such as a paragraph spans multiple pages, thereby representing a multi-page document and linking a paragraph element that spans multiple pages.
With regard to Claim 5, Yashiro teaches that when two consecutive columns are present in the document data and two consecutive paragraph elements satisfy a predetermined condition, the first processing module includes a page coupling module that couples the two consecutive paragraph elements, and in the structuring processing, the processor generates the first structured data by distinguishing between the paragraph element corresponding to the heading and the paragraph element not corresponding to the heading based on the detection result of the detection module and a page coupling result of the page coupling module. Pp. 10-11 describe that a chapter relation can relate the chapter title and paragraphs. The invention further functions by generating a relationship identifying when a separated logical structure such as a paragraph spans multiple pages, thereby representing a multi-page document and linking a paragraph element that spans multiple pages.
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.
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.
Claims 6-8 are rejected under 35 U.S.C. 103 as being unpatentable over Yashiro, in view of Sarrafzadeh, et al., U.S. Patent No. 11,763,075 (“Sarrafzadeh”).
With regard to Claim 6, Yashiro, in view of Sarrafzadeh teaches that a classifier that associates the feature related to the layout in the document data with the processing module is accessible, and in the extraction processing, the processor extracts the specific template data by selecting the specific processing module corresponding to the result of the selection input using the classifier.
Yashiro teaches at p. 6 that the processing determined to be carried out on a document is determined using a particular common logical structure for a document class. Sarrafzadeh teaches at Col. 3, line 62 – Col. 4, line 32 that a machine learning model can be used for intelligently identifying templates which can be used to create a document using input document data and the template structure. A trained classifier can be used to match content and structure of an input document with a type and subtype, in order to select the appropriate template.
It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Yashiro to implement the selection of a common structure for processing a document, using the selection process described in Sarrafzadeh. One of skill in the art would have sought the modification, to improve system functioning by enabling a process for selecting common logical structures that uses machine learning and other processes which can increase the accuracy of the selection process, ensuring documents are properly processed to add the appropriate structure thereto.
With regard to Claim 7, Yashiro, in view of Sarrafzadeh teaches that when the document data is input, a classifier trained to extract the template data from the template data pool based on the feature related to the layout in the document data is accessible, and in the extraction processing, the processor extracts the specific template data by selecting the specific processing module corresponding to the result of the selection input using the classifier.
Yashiro teaches at p. 6 that the processing determined to be carried out on a document is determined using a particular common logical structure for a document class. Sarrafzadeh teaches at Col. 3, line 62 – Col. 4, line 32 that a machine learning model can be used for intelligently identifying templates which can be used to create a document using input document data and the template structure. A trained classifier can be used to match content and structure of an input document with a type and subtype, in order to select the appropriate template.
It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Yashiro to implement the selection of a common structure for processing a document, using the selection process described in Sarrafzadeh. One of skill in the art would have sought the modification, to improve system functioning by enabling a process for selecting common logical structures that uses machine learning and other processes which can increase the accuracy of the selection process, ensuring documents are properly processed to add the appropriate structure thereto.
With regard to Claim 8, Yashiro teaches that the processor executes determination processing of determining a coincidence between second structured data corresponding to the structuring target document data and third structured data for each piece of template data obtained by executing the structuring processing on the structuring target document data for each piece of the template data in the template data pool, and outputting, as label data, the template data which is a generation source of the second structured data based on a determination result. Pp. 11-12 describe that the logical structure extraction unit extracts and stores elements of an input document in relation to the elements of the common logical structure. Specific elements such as sections are stored in a relation table in association with the common logical structure, thereby labeling the document as an instance of the particular common logical structure.
Yashiro, in view of Sarrafzadeh teaches training processing of training the classifier based on the template data obtained by inputting the structuring target document data to the classifier and the label data outputted by the determination processing, and in the extraction processing, the processor extracts the specific template data by selecting the specific processing module corresponding to the result of the selection input using the classifier trained by the training processing.
Yashiro teaches at p. 6 that a selected common logical structure is selected for processing an input document to recognize the specific structure of an input document. Sarrafzadeh teaches at Col. 8, line 13 – Col. 9, line 22 describe that a number of different types of documents can be collected, as well as different types of templates. Document data and template data can be labeled depending on a type to which they pertain, and the labeled documents used to train machine learning processes, which include a classifier as described at Col. 3, line 62 – Col. 4, line 32.
It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Yashiro to implement the selection of a common structure for processing a document, using the selection process described in Sarrafzadeh. One of skill in the art would have sought the modification, to improve system functioning by enabling a process for selecting common logical structures that uses machine learning and other processes which can increase the accuracy of the selection process, ensuring documents are properly processed to add the appropriate structure thereto.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Iguchi, et al., U.S. PGPUB No. 2005/0200876 teaches module selection for processing an input document to add structure thereto.
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/KEITH D BLOOMQUIST/Primary Examiner, Art Unit 2171
6/21/2026
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