DETAILED ACTION
A. This action is in response to the following communications: Amendment filed: 01/30/2026. This action is made Final.
B. Claims 1-20 remain 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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to certain methods of organizing human activity without significantly more. The claim(s) 1, 13 and 20 recite(s) “receiving a plurality of documents by a computing device, wherein each document includes at least one table of a plurality of tables;”, grouping of abstract ideas. The mere nominal recitation of a computing device does not take the claim out of the “certain methods of organizing human activity” grouping. Thus, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application because the claim as a whole merely describes how to generally “apply” the concept of receiving, identifying and extracting in a computer environment. The claimed “computing activity” are recited at a high level of generality and are merely invoked as tools perform a data extraction process. Even considered in combination, simply implementing the abstract idea on a generic computer with storage devices recited at a high level of generality is not a practical application of the abstract idea.The limitation extracting data from each table in the subset of similar tables by the computing device;, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “by the computing device,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by the computing device language, “consolidating the extracted data into a consolidated table by the computing device and generating one or more visualizations using the consolidated table” in the context of this claim encompasses the user manually organizing data.
The claim does not include additional elements that are sufficient to amount to the significantly more than the judicial exception because as noted previously, computing device and actions performed by generic computing device individually and in combination merely describe how to generally “apply” the concept of consolidating extracted data in a computer environment. The same applies here. (MPEP 2106.05(d). Thus, even when viewed as a whole, nothing in the claims adds significantly more (i.e. an inventive concept) to the abstract idea.
The claim is ineligible.
Claims 2-12 and 14-19 do not include elements that amount to significantly more than the abstract idea and are also rejected under the same rational.
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) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Desai, Anish et al. (US Pub. 2017/0357631 A1), herein referred to as “Desai” in view of Murphy, Ronald Francis et al. (US Pub 2015/0324192 A1), herein referred to as “Murphy”.
As for claims 1, 13 and 20, Desai teaches. A method comprising:
receiving a plurality of documents by a computing device, wherein each document includes at least one table of a plurality of tables (par. 30 user input to a location on a hard drive that has a plurality of documents wherein the invention (herein software) uses a document analyzer to automatically parse these groups of documents the user inputted; par. 31 computer receives user inputs to identify a structure J which by example is a table within one of many inputted documents for the software to use the document analyzer; the structure is termed “layout structure”);
identifying a subset of similar tables from the plurality of tables by the computing device (par. 33 computer 100 uses the predetermined identifier (e.g. identifier in FIG. 1B) to identify the structure J as being present in document 112I; subset of documents are identified for having same layout structure by using a template; par. 35 goes further in examples of finding same layout structure in a subset group of documents A, I and N and their structures labeled as B, J and M (used in the disclosure to help follow along););
extracting data from each table in the subset of similar tables by the computing device (par. 45 identifying similar documents by use of a template and using the document analyzer to extra tables from all similar documents); and
consolidating the extracted data into a consolidated table by the computing device (par. 62 aggregate data from the data parsed by the document analyzer for further analysis by the user).
Desai does not specifically teach consolidated schema; however in the same field of endeavor Murphy teaches wherein consolidating the extracted data into the consolidated table comprises using, for each table, a table schema for the table and a consolidated schema for the consolidated table, each schema including a name for each column, to map data from columns of the table into corresponding columns of the consolidated table (par. 52 and 62 each type if stored in own schema (table schema for tables), creating a temp schema that can be inlined as a single schema definition in the WSDL (e.g., Web Services Description Language); user creates the WSDL and specifies the types used in operations, those specific types are automatically inlined into the WSDL document. This aggregation of needed types into a WSDL simplifies the WSDL. we can aggregate (e.g. consolidate) all the types needed and include them in-line under the <types> section.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Murphy into Desai because Murphy suggest in paragraph 13 a computer-implemented system and method for creating, managing, and reusing schema type definitions in SOA services, grouped in the form of libraries is needed.
As for claims 2, 13 and 20, Desai teaches. The method of claim 1, further comprising generating one or more visualizations using the consolidated table (par. 46 execution of document analyzer 134 by processor 120 requires user 183 to select an action to be performed in rules file 133X and hence the type of data to be collected from each layout structure J, e.g. for storage in an RDBMS table or for display on a computer screen).
As for claims 3 and 14, Desai teaches. The method of claim 2, wherein generating one or more visualizations using the consolidated table comprises: receiving an indication of a variable of interest of the consolidated table; and generating the one or more visualizations based on the variable of interest (par. 47 the output of processor 120 when executing document analyzer 134, such as the collection 135J and/or the statistics 136J, may be in different forms depending on the embodiment, e.g. web page 191 for use in a browser, spreadsheet 192 for use in a spreadsheet program, or relational database 138 that is accessed via a relational database management system (RDBMS)).
As for claims 4 and 15, Desai teaches. The method of claim 1, wherein each table of the plurality of tables is associated with metadata; and further comprising: identifying the subset of the similar tables from the plurality of tables based on the metadata (par. 45-46 extracted document metadata used in finding matches in layout structure J).
As for claims 5 and 16, Desai teaches. The method of claim 4, wherein the metadata associated with each table comprises one or more of a title of the table or a title of a document of the plurality of documents that the table was extracted from (par. 38 and 45 layout structure J can be a table having cells (also called “tabular cells”), and a name of the table can be inserted by a user as identifier ID-J immediately before the table J; document metadata is parsed from document analyzer which includes name/title of documents stored as metadata).
As for claims 6 and 17, Desai teaches. The method of claim 1, further comprising:
receiving a consolidated schema for the consolidated table; and consolidating the extracted data into the consolidated table using the consolidated schema (par. 48 output of processor 120 when stored in an RDBMS table (such as table 138J) can be further processed by use of queries in a structured query language (SQL), to generate reports in the form of web pages for display by computer 184 to user 183; the schema being a web-page such as XML and/or the RDBMS).
As for claims 7 and 18, Desai teaches. The method of claim 1, further comprising: for each table of the similar tables, determining a table schema for the table; and consolidating the extracted data into the consolidated table using the table schemas and the consolidated schema (par. 48 document analyzer 134 of some embodiments is a hosted (software as a service or SaaS) application that is invoked by user 183 providing a location (e.g. URL) of the document repository (where the group 115X of word-processing documents reside) and select a rules file 133X (instructions to document analyzer 134, as to what layout structures to look for in documents 112I-112N being analyzed (see group 115X in FIG. 1B), and what text and statistics to collect from each layout structure that is recognized in the documents).
As for claims 8 and 19, Desai teaches. The method of claim 7, wherein determining a table schema for the table comprises determining the table schema using a machine learning model (par. 54 the document analyzer is a form of machine learning model though not specifically stating the terms but uses natural language processing which is a ML model technique to identify documents and contents therein when parsing automatically through a set of documents).
As for claim 9, Desai teaches. The method of claim 7, wherein the table schema for each table comprises a name for each column of a plurality of columns of the table, and the consolidated table comprises a name for each column of a plurality columns of the consolidated table (par. 45-46 using names stored in metadata from documents in the collection of documents used by the documents analyzer to find related documents that match a template in order to aggregate data from particularly same type of documents (e.g. business data forms)).
As for claim 10, Desai teaches. The method of claim 9, wherein consolidating the extracted data into the consolidated table comprises, for each table of the plurality of tables comprises:
consolidating the extracted data from the table into the consolidated table by matching the names of the columns of the table with the names of the columns of the consolidated table (note analysis of claim 9 above with the following example found in par. 58 two additional layout structures B and M in word-processing documents 112A-112N are also word-processing tables in template 131X, and each row in these two tables includes a name of a person. The persons in table B are authors and the word “Authors” is used as ID-B to identify table B in template 131X, while the persons in table M are reviewers and the word “Reviewers” is used as ID-M to identify table M in template 131X.).
As for claim 11, Desai teaches. The method of claim 1, wherein the plurality of documents comprises PDF documents (par. 129 identifying different document types such as .doc, .rtf. and .docx; the PDF file extension would not have any functional weight applied to this limitation as its purpose in the claim and the examples given in the prior art are of that the same in functionality and therefore an arbitrary file extension would not be novel).
As for claim 12, Desai teaches. The method of claim 1, wherein the at least one table in each document of the plurality of documents does not include structural or semantic information about the contents of the tables (par. 46 gives scenario of when plurality of documents does not include structure or semantic information and uses wild cards by the document analyzer to determine similarity between documents).
(Note :) It is noted that any citation to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006,1009, 158 USPQ 275, 277 (CCPA 1968)).
Response to Arguments
Applicant's arguments filed have been fully considered but they are not persuasive.
A1. Applicant argues that 35 USC 101 should be withdrawn.
R1. Examiner notes that the addition to the term ‘schema’ which as known in the art is defined as( A schema is a structured framework, plan, or mental model that organizes information, patterns, or knowledge.). Examiner notes that a use of a specific schema is on par with using out of box software and Examiner notes that under MPEP 2106, software—including "out-of-the-box" or computer-readable medium (CRM) claims—is generally considered an abstract idea under 35 U.S.C. 101 as it is not yet integrated into a practical application that improves the functionality of the computer itself or a technical field by adding “significantly more”.
The 35 USC 101 rejection will be maintained until proper amendment that overcomes the abstract idea concerns addressed herein.
R2. Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
THIS ACTION IS MADE FINAL. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Inquires
Any inquiry concerning this communication should be directed to NICHOLAS AUGUSTINE at telephone number (571)270-1056.
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.
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/NICHOLAS AUGUSTINE/Primary Examiner, Art Unit 2178 May 11, 2026
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