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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/21/25, 04/10/25 and 02/26/26 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim 9 will not be rejected under 35 U.S.C. 101 because the computer readable medium storing instructions in claim 9 is within a system that are executable by one or more processing devices.
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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim 17 is rejected under 35 U.S.C. 101 because claim 17 recites computer readable medium, which does not fall into any one of the four statutory subject matter as covering both non-statutory subject matter and statutory subject matter. In an effort to assist the Applicant in overcoming a rejection or potential rejection under 35 U.S.C. 101, the Examiner suggests the following approach: a claim drawn to such a computer readable storage medium storing a program that covers both transitory and non-transitory embodiments may be amended to narrow the claim to cover only statutory embodiments to avoid a rejection under 35 U.S.C. 101 by adding the limitation “non-transitory” to the claim. The examiner respectfully suggest changing the claim to recite “A non-transitory computer-readable storage medium storing instructions that are executable...”
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, 2, 6-10, 14-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gao et al US 20230133690 in view of Ball et al US 20230230403.
Regarding claim 1, Gao et al teaches A method comprising:
displaying, by at least one computing device, a user interface (the output module 615 may transmit output signals for display in a user interface (paragraph 0069);
receiving, by the at least one computing device, one or more documents from a data source based on input to the user interface (optical character recognition model may process the input document (e.g., an image of a form) to detect and recognize optical character recognition words (paragraph 0041 and fig 3). A user may submit the input document 400 to a system or application via a user interface (paragraph 0056);
receiving, by the at least one computing device, at least one key name included in text content of the one or more documents based on input to the user interface (A user may submit an input key phrase querying a value for a key-value pair (paragraph 0056); and
Gao et al fails to teach updating, by the at least one computing device, the user interface to display at least one value associated with the at least one key name, wherein the at least one value is obtained using a document graph that represents the one or more documents using:
a plurality of nodes that each represent a string of characters included in the one or more documents; and
wherein at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes based on the first node of the plurality of nodes
Adam et al teaches updating, by the at least one computing device, the user interface to display at least one value associated with the at least one key name (for a value, the output may be a text string or a number, an indicator (e.g., CHECKED/UNCHECKED, TRUE/FALSE, etc.) indicating whether a checkbox (or other user interface input element) is marked (column 10, lines 44-50), wherein the at least one value is obtained using a document graph that represents the one or more documents using (the key-value association unit can identify pairings of keys and values based on the weights of the edges in the graph according to an automated graph partitioning algorithm, to thus programmatically determine which keys from a document correspond to which values, even when the key-value association unit has no advance knowledge of the layout of the particular document (column 1, lines 55-67):
a plurality of nodes that each represent a string of characters included in the one or more documents (a key-value association unit can automatically identify which “keys” and which “values” detected in an electronic document correspond to one another. the key-value association unit can identify pairings of keys and values based on the weights of the edges in the graph according to an automated graph partitioning algorithm, to thus programmatically determine which keys from a document correspond to which values, even when the key-value association unit has no advance knowledge of the layout of the particular document (column 1, lines 55-67); and
wherein at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes based on the first node of the plurality of nodes (The graph 126 may be a weighted bipartite graph with a first set of nodes corresponding to the keys, and a second set of nodes corresponding to the values. Each node from the first set of nodes (representing the keys) may include an edge to each of the second set of nodes (representing the values) (column 6, lines 61-67)
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al to include: updating, by the at least one computing device, the user interface to display at least one value associated with the at least one key name, wherein the at least one value is obtained using a document graph that represents the one or more documents using:
a plurality of nodes that each represent a string of characters included in the one or more documents; and
wherein at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes based on the first node of the plurality of nodes
The reason for doing so would be to accurately identify key values in a document.
Gao et al in view of Adams et al fails to teach a plurality of edges that each connect two or more of the plurality of nodes, wherein a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes.
Ball et al teaches a plurality of edges that each connect two or more of the plurality of nodes (combinations of nodes and/or edges to identify combinations of nodes and/or edges that are similar to the substructure. For example, a combination of nodes and/or edges that are similar to the substructure may match or include a target substructure that was searched for by the search tool (paragraph 0075), wherein a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes (the “node branch diff” focuses on angle distribution of branches extented from one node, and thus represents a feature for a single node. For example, as shown in FIG. 8C, the node A's branches could be characterized as [180°, 270°], and the node B's branches could be characterized as [90°, 270°]. The similarity (“sim”) between node A and node B may be defined as an inner product of normalized length (distance) distribution along the circle, and the difference (“diff”) can obtained as: diff=1−sim (paragraph 0077).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al in view of Adams et al to include: a plurality of edges that each connect two or more of the plurality of nodes, wherein a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes.
The reason for doing so would be to allow a user to accurately view key pairs of a document by looking at the key names and associated values.
Regarding claim 2, Gao et al in view of Adams et al further in view of Ball et al teaches wherein each of the plurality of nodes further represents a location of the string of characters in the one or more documents (Adams et al: he actual text may not have been yet identified (e.g., such as when the text recognition/localization unit(s) 214 have detected regions/locations including the text, but not the actual text itself), and thus at circle (7C) the key-value association unit 119 may cause the text recognition/localization unit(s) 214 to identify the actual text of the keys and values. For example, the key-value association unit 119 may send a request to the text recognition/localization unit(s) 214 that includes (or identifies) the particular regions of interest to be analyzed for text recognition. The resulting text could be returned to the key-value association unit 119, stored as document data 220 (column 10, lines 60-67).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al in view of Adams et al to include: wherein each of the plurality of nodes further represents a location of the string of characters in the one or more documents.
The reason for doing so would be to allow a user to identify key pairs of a document by looking at the key names and associated values.
Regarding claim 6, Gao et al in view of Adams et al further in view of Ball et al teaches wherein the document graph that represents the one or more documents is generated using fuzzy matching to associate the at least one key name with at least one string of characters represented by the plurality of nodes (Gao et al: the server may determine that the value 406 “US-001” is the corresponding value to the input key phrase. In some examples, the input key phrase may not match any key in the input document 400. For instance, instead of inputting “invoice #” the user may input “invoice number.” The server may determine that the phrase “invoice number” is a closest match to the key 404 “invoice # (paragraph 0059).
Regarding claim 7, Gao et al in view of Adams et al further in view of Ball et al teaches comprising generating at least one token for the at least one key name, wherein the plurality of nodes of the document graph are generated using the at least one token (Gao et al: other computing device executing the transformer-based model may tokenize the input key phrase into words (paragraph 0043)).
Regarding claim 8, Gao et al in view of Adams et al further in view of Ball et al teaches wherein the at least one key name includes multiple key names, each of the multiple key names represented by one of the plurality of nodes in the document graph, wherein the threshold distance between a first one of the plurality of nodes and a second one of the plurality of nodes represents a distance between a bounding box surrounding a first one of the multiple key names and a bounding box surrounding a second one of the multiple key names as included in the one or more documents (Adams et al: the edge weight may simply be set as the distance between an average embedding from each of the two regions (i.e., the region or polygon/bounding box encompassing the key, and the region or polygon/bounding box encompassing the value) (column 7, lines 22-35).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al to include: wherein the at least one key name includes multiple key names, each of the multiple key names represented by one of the plurality of nodes in the document graph, wherein the threshold distance between a first one of the plurality of nodes and a second one of the plurality of nodes represents a distance between a bounding box surrounding a first one of the multiple key names and a bounding box surrounding a second one of the multiple key names as included in the one or more documents.
The reason for doing so would be to allow a user to identify key pairs of a document by looking at the key names and associated values.
Regarding claim 9, Gao et al teaches A system comprising:
at least one processor (processor 830 (paragraph 0086); and
a computer-readable storage medium storing instructions that are executable by the at least one processor to (The memory 825 may store computer-readable, computer-executable software including instructions that, when executed, cause the processor 830 to perform various functions (paragraph 0085):
display a user interface (the output module 615 may transmit output signals for display in a user interface (paragraph 0069);
receive one or more documents from a data source based on input to the user interface (optical character recognition model may process the input document (e.g., an image of a form) to detect and recognize optical character recognition words (paragraph 0041 and fig 3). A user may submit the input document 400 to a system or application via a user interface (paragraph 0056);
receive at least one key name included in text content of the one or more documents based on input to the user interface (A user may submit an input key phrase querying a value for a key-value pair (paragraph 0056); and
Gao et al fails to teach update the user interface to display at least one value associated with the at least one key name, wherein the at least one value is obtained using a document graph that represents the one or more documents using:
a plurality of nodes that each represent a string of characters included in the one or more documents; and
a plurality of edges that each connect two or more of the plurality of nodes, wherein at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes.
Adam et al teaches update the user interface to display at least one value associated with the at least one key name (for a value, the output may be a text string or a number, an indicator (e.g., CHECKED/UNCHECKED, TRUE/FALSE, etc.) indicating whether a checkbox (or other user interface input element) is marked (column 10, lines 44-50), wherein the at least one value is obtained using a document graph that represents the one or more documents using (the key-value association unit can identify pairings of keys and values based on the weights of the edges in the graph according to an automated graph partitioning algorithm, to thus programmatically determine which keys from a document correspond to which values, even when the key-value association unit has no advance knowledge of the layout of the particular document (column 1, lines 55-67):
a plurality of nodes that each represent a string of characters included in the one or more documents (a key-value association unit can automatically identify which “keys” and which “values” detected in an electronic document correspond to one another. the key-value association unit can identify pairings of keys and values based on the weights of the edges in the graph according to an automated graph partitioning algorithm, to thus programmatically determine which keys from a document correspond to which values, even when the key-value association unit has no advance knowledge of the layout of the particular document (column 1, lines 55-67); and
a plurality of edges that each connect two or more of the plurality of nodes, wherein at least one of the plurality of edges connects a first node of the plurality of nodes (The graph 126 may be a weighted bipartite graph with a first set of nodes corresponding to the keys, and a second set of nodes corresponding to the values. Each node from the first set of nodes (representing the keys) may include an edge to each of the second set of nodes (representing the values) (column 6, lines 61-67)
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al to include: update the user interface to display at least one value associated with the at least one key name, wherein the at least one value is obtained using a document graph that represents the one or more documents using:
a plurality of nodes that each represent a string of characters included in the one or more documents; and
a plurality of edges that each connect two or more of the plurality of nodes, wherein at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes.
The reason for doing so would be to accurately identify key values in a document.
Gao et al in view of Adams et al fails to teach at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes.
Ball et al teaches at least one of the plurality of edges connects a first node of the plurality of nodes (combinations of nodes and/or edges to identify combinations of nodes and/or edges that are similar to the substructure. For example, a combination of nodes and/or edges that are similar to the substructure may match or include a target substructure that was searched for by the search tool (paragraph 0075) with a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes (the “node branch diff” focuses on angle distribution of branches extented from one node, and thus represents a feature for a single node. For example, as shown in FIG. 8C, the node A's branches could be characterized as [180°, 270°], and the node B's branches could be characterized as [90°, 270°]. The similarity (“sim”) between node A and node B may be defined as an inner product of normalized length (distance) distribution along the circle, and the difference (“diff”) can obtained as: diff=1−sim (paragraph 0077).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al in view of Adams et al to include: at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes.
The reason for doing so would be to allow a user to accurately view key pairs of a document by looking at the key names and associated values.
Regarding claim 10, Gao et al in view of Adams et al further in view of Ball et al teaches wherein each of the plurality of nodes further represents a location of the string of characters in the one or more documents (Adams et al: he actual text may not have been yet identified (e.g., such as when the text recognition/localization unit(s) 214 have detected regions/locations including the text, but not the actual text itself), and thus at circle (7C) the key-value association unit 119 may cause the text recognition/localization unit(s) 214 to identify the actual text of the keys and values. For example, the key-value association unit 119 may send a request to the text recognition/localization unit(s) 214 that includes (or identifies) the particular regions of interest to be analyzed for text recognition. The resulting text could be returned to the key-value association unit 119, stored as document data 220 (column 10, lines 60-67).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al in view of Adams et al to include: wherein each of the plurality of nodes further represents a location of the string of characters in the one or more documents.
The reason for doing so would be to allow a user to identify key pairs of a document by looking at the key names and associated values.
Regarding claim 14, Gao et al in view of Adams et al further in view of Ball et al teaches wherein the document graph that represents the one or more documents is generated using fuzzy matching to associate the at least one key name with at least one string of characters represented by the plurality of nodes (Gao et al: the server may determine that the value 406 “US-001” is the corresponding value to the input key phrase. In some examples, the input key phrase may not match any key in the input document 400. For instance, instead of inputting “invoice #” the user may input “invoice number.” The server may determine that the phrase “invoice number” is a closest match to the key 404 “invoice # (paragraph 0059)..
Regarding claim 15, Gao et al in view of Adams et al further in view of Ball et al teaches wherein the instructions are further executable to generate at least one token for the at least one key name, wherein the plurality of nodes of the document graph are generated using the at least one token (Gao et al: other computing device executing the transformer-based model may tokenize the input key phrase into words (paragraph 0043)).
Regarding claim 16, Gao et al in view of Adams et al further in view of Ball et al teaches wherein the at least one key name includes multiple key names, each of the multiple key names represented by one of the plurality of nodes in the document graph, wherein the threshold distance between a first one of the plurality of nodes and a second one of the plurality of nodes represents a distance between a bounding box surrounding a first one of the multiple key names and a bounding box surrounding a second one of the multiple key names as included in the one or more documents (Adams et al: the edge weight may simply be set as the distance between an average embedding from each of the two regions (i.e., the region or polygon/bounding box encompassing the key, and the region or polygon/bounding box encompassing the value) (column 7, lines 22-35).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al to include: wherein the at least one key name includes multiple key names, each of the multiple key names represented by one of the plurality of nodes in the document graph, wherein the threshold distance between a first one of the plurality of nodes and a second one of the plurality of nodes represents a distance between a bounding box surrounding a first one of the multiple key names and a bounding box surrounding a second one of the multiple key names as included in the one or more documents
The reason for doing so would be to allow a user to identify key pairs of a document by looking at the key names and associated values.
Regarding claim 17, Gao et al teaches A computer-readable storage medium storing instructions that are executable by one or more processing devices to perform operations (A non-transitory computer-readable medium storing code for form processing (paragraph 0118) comprising:
displaying a user interface (the output module 615 may transmit output signals for display in a user interface (paragraph 0069);
receiving one or more documents from a data source based on input to the user interface (optical character recognition model may process the input document (e.g., an image of a form) to detect and recognize optical character recognition words (paragraph 0041 and fig 3). A user may submit the input document 400 to a system or application via a user interface (paragraph 0056);
receiving at least one key name included in text content of the one or more documents based on input to the user interface (A user may submit an input key phrase querying a value for a key-value pair (paragraph 0056); and
Gao et al fails to teach updating the user interface to display at least one value associated with the at least one key name, wherein the at least one value is obtained from a document graph that represents the one or more documents using:
a plurality of nodes that each represent a string of characters included in the one or more documents; and a plurality of edges that each connect two or more of the plurality of nodes, wherein at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes.
Adams et al teaches updating the user interface to display at least one value associated with the at least one key name (for a value, the output may be a text string or a number, an indicator (e.g., CHECKED/UNCHECKED, TRUE/FALSE, etc.) indicating whether a checkbox (or other user interface input element) is marked (column 10, lines 44-50), wherein the at least one value is obtained from a document graph that represents the one or more documents using (the key-value association unit can identify pairings of keys and values based on the weights of the edges in the graph according to an automated graph partitioning algorithm, to thus programmatically determine which keys from a document correspond to which values, even when the key-value association unit has no advance knowledge of the layout of the particular document (column 1, lines 55-67):
a plurality of nodes that each represent a string of characters included in the one or more documents (a key-value association unit can automatically identify which “keys” and which “values” detected in an electronic document correspond to one another. the key-value association unit can identify pairings of keys and values based on the weights of the edges in the graph according to an automated graph partitioning algorithm, to thus programmatically determine which keys from a document correspond to which values, even when the key-value association unit has no advance knowledge of the layout of the particular document (column 1, lines 55-67); and
a plurality of edges that each connect two or more of the plurality of nodes, wherein at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes (The graph 126 may be a weighted bipartite graph with a first set of nodes corresponding to the keys, and a second set of nodes corresponding to the values. Each node from the first set of nodes (representing the keys) may include an edge to each of the second set of nodes (representing the values) (column 6, lines 61-67)
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al to include: updating the user interface to display at least one value associated with the at least one key name, wherein the at least one value is obtained from a document graph that represents the one or more documents using:
a plurality of nodes that each represent a string of characters included in the one or more documents; and a plurality of edges that each connect two or more of the plurality of nodes, wherein at least one of the plurality of edges connects a first node of the plurality of nodes with a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes.
The reason for doing so would be to accurately identify key values in a document.
Gao et al in view of Adams et al fails to teach a plurality of edges that each connect two or more of the plurality of nodes, wherein a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes
Ball et al teaches a plurality of edges that each connect two or more of the plurality of nodes (combinations of nodes and/or edges to identify combinations of nodes and/or edges that are similar to the substructure. For example, a combination of nodes and/or edges that are similar to the substructure may match or include a target substructure that was searched for by the search tool (paragraph 0075), wherein a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes (the “node branch diff” focuses on angle distribution of branches extented from one node, and thus represents a feature for a single node. For example, as shown in FIG. 8C, the node A's branches could be characterized as [180°, 270°], and the node B's branches could be characterized as [90°, 270°]. The similarity (“sim”) between node A and node B may be defined as an inner product of normalized length (distance) distribution along the circle, and the difference (“diff”) can obtained as: diff=1−sim (paragraph 0077).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al in view of Adams et al to include: a plurality of edges that each connect two or more of the plurality of nodes, wherein a second node of the plurality of nodes based on the first node of the plurality of nodes being within a threshold distance and within a threshold angle from the second node of the plurality of nodes
The reason for doing so would be to allow a user to accurately view key pairs of a document by looking at the key names and associated values.
Regarding claim 18, Gao et al in view of Adams et al further in view of Ball et al teaches wherein each of the plurality of nodes further represents a location of the string of characters in the one or more documents (Adams et al: he actual text may not have been yet identified (e.g., such as when the text recognition/localization unit(s) 214 have detected regions/locations including the text, but not the actual text itself), and thus at circle (7C) the key-value association unit 119 may cause the text recognition/localization unit(s) 214 to identify the actual text of the keys and values. For example, the key-value association unit 119 may send a request to the text recognition/localization unit(s) 214 that includes (or identifies) the particular regions of interest to be analyzed for text recognition. The resulting text could be returned to the key-value association unit 119, stored as document data 220 (column 10, lines 60-67).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify Gao et al in view of Adams et al to include: wherein each of the plurality of nodes further represents a location of the string of characters in the one or more documents.
The reason for doing so would be to allow a user to identify key pairs of a document by looking at the key names and associated values.
Allowable Subject Matter
Claims 3-5, 11-13, 19 and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL L BURLESON whose telephone number is (571)272-7460.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Akwasi Sarpong can be reached on 571 270-3438 The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Michael Burleson
Patent Examiner
Art Unit 2683
Michael Burleson
July 25, 2026
/MICHAEL BURLESON/
/AKWASI M SARPONG/SPE, Art Unit 2681 7/31/2026
Prosecution Insights