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 .
Remarks
This action is in response to the application received on 2/26/25. Claims 1-17 are pending in the application.
The drawings are objected to.
Claims 1-17 are rejected under 35 U.S.C. 101.
Claims 1-8 are rejected under 35 U.S.C. 112.
Claim(s) 1-7 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Sutherland et al. (US 2022/0309089).
Claims 8-17 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Asermely (US 12,340,612).
Drawings
The drawings (Figures 7-10) are objected to because they include text that is not legible. For example, Fig. 7 shows elements 702-708, however, it is not clear in the drawings what these items are meant to state. Figures 8-10 similarly have issues where elements include text that may be functional, but it is not legible. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 112
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 1-8 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.
Claim 1 recites the limitation "the classification block" in the “learning” limitation. There is insufficient antecedent basis for this limitation in the claim. The preceding limitation discloses classification blocks, however, this is plural while the recitation in the “learning” limitation is singular. For purposes of examination, this will be interpreted as “a classification block.”
Claim 1 recites the limitation "the user" in the “classifying” limitation. There is insufficient antecedent basis for this limitation in the claim. The preceding limitations discloses a user-selected document, however, this is referring to a document, not a user. For purposes of examination, this will be interpreted as “a user.”
Claim 2 recites the limitation "the document”. There is insufficient antecedent basis for this limitation in the claim. The preceding limitation discloses the user-selected document, however, it is unclear if this is meant to be a new document or the user-selected document. For purposes of examination, this will be interpreted as “a document.”
Claim 4 recites the limitation "the documents”. There is insufficient antecedent basis for this limitation in the claim. The preceding claims discloses the plurality of documents and the user-selected document, however, it is unclear if this is meant to be new documents or the previously recited documents. For purposes of examination, this will be interpreted as “documents.”
Claim 5 recites the limitations "the level of understanding” and “the user’s classification intent”. There is insufficient antecedent basis for this limitation in the claim.
Claim 7 recites the limitation "the method of classifying documents”. There is insufficient antecedent basis for this limitation in the claim. For purposes of examination, this will be interpreted as “a method of classifying documents.”
Claims 8 and 13 recite the limitation "the classification block" in the “displaying” limitation. There is insufficient antecedent basis for this limitation in the claim. For purposes of examination, this will be interpreted as “a classification block.”
Claims 8 and 13 recite the limitation "the user" in the “displaying” limitation. There is insufficient antecedent basis for this limitation in the claim. For purposes of examination, this will be interpreted as “a user.”
Claims 8 and 13 state that the AI model is a model “learned for association documents with classification blocks.” It is unclear if this is introducing new “association documents” or is meant to define the AI model as being trained for “associating documents with classification blocks.”
Claims 9 and 14 recite the limitation "the plurality of documents”. There is insufficient antecedent basis for this limitation in the claim. The preceding claim discloses the documents, however, it is unclear if this is meant to be new documents or the previously recited documents. For purposes of examination, this will be interpreted as “a plurality of documents.”
Claims 11 and 16 recite the limitations "the level of understanding” and “the user’s classification intent”. There is insufficient antecedent basis for this limitation in the claim.
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 1-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 2A, Prong One asks: Is the claim directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? See MPEP 2106.04 Part I. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. See MPEP 2106.04(a).
With respect to claim 1, the limitations of “assigning a user-selected document among the plurality of documents to classification blocks” and “classifying the plurality of documents”, 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, nothing in the claim element precludes the step from practically being performed in the mind. For example, “assigning” and “classifying” in the context of this claim encompasses the user mentally determining a category.
The limitation of “learning an AI model using the user-selected document assigned to the classification block”, 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, nothing in the claim element precludes the step from practically being performed in the mind. For example, “learning” in the context of this claim encompasses the user mentally learning about documents.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
At step 2a, prong two, this judicial exception is not integrated into a practical application. The claims recite a computing device, however, this is recited as a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Additionally, the claim recites “reading a plurality of documents” and “notifying whether the AI model classifies the plurality of documents.” These elements do not integrate the abstract idea into a practical application because they do not impose a meaningful limit on the judicial exception and provide only insignificant extra solution activity that is mere data gathering in conjunction with the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
With respect to “reading a plurality of documents”, the courts have found limitations directed towards data gathering to be well-understood, routine, and conventional. See MPEP 2106.05(d)(II). Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information).
With respect to “notifying whether the AI model classifies the plurality of documents”, the courts have found limitations directed towards storing to be well-understood, routine, and conventional. See MPEP 2106.05(d)(II). Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93.
Considering the additional elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. The claim is not patent eligible.
With respect to claims 2 and 4-7, the limitations further define the limitations above and do not provide additional elements.
With respect to claim 3, the claim recites “generating a new classification block corresponding to the classification block” which 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, nothing in the claim element precludes the step from practically being performed in the mind. For example, “generating” in the context of this claim encompasses the user mentally determining a new category.
With respect to claims 8 and 13, the limitations of “classifying documents selected by the user using the AI model”, 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, nothing in the claim element precludes the step from practically being performed in the mind. For example, “classifying” in the context of this claim encompasses the user mentally determining a category.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
At step 2a, prong two, this judicial exception is not integrated into a practical application. The claims recite a computing device, however, this is recited as a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Additionally, the claim recites “displaying an indication to represent whether an AI model can classify for the classification block selected by the user.” These elements do not integrate the abstract idea into a practical application because they do not impose a meaningful limit on the judicial exception and provide only insignificant extra solution activity that is mere data gathering in conjunction with the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
With respect to “displaying an indication to represent whether an AI model can classify for the classification block selected by the user”, the courts have found limitations directed towards storing to be well-understood, routine, and conventional. See MPEP 2106.05(d)(II). Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93.
Considering the additional elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. The claim is not patent eligible.
With respect to claims 9 and 14, the claim recites “generating a new classification block corresponding to the classification block” which 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, nothing in the claim element precludes the step from practically being performed in the mind. For example, “generating” in the context of this claim encompasses the user mentally determining a new category.
With respect to claims 10-12 and 15-17, the limitations further define the limitations above and do not provide additional elements.
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)(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.
Claim(s) 1-7 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Sutherland et al. (US 2022/0309089).
With respect to claim 1, Sutherland teaches an AI (Artificial Intelligence)-based document classification method performed by a computing device comprises:
reading a plurality of documents (Sutherland, pa 0136, Referring to FIG. 3, at step Sl00, the server device 20 may collect documents to be included in the training dataset 52 for training the machine learning model 50. The documents may be collected from the document DB 30.);
assigning a user-selected document among the plurality of documents to classification blocks (Sutherland, pa 0201, a random subset may be selected from available, unlabeled, documents to be manually classified. The manual classification may then be used for training the machine learning model 50 to setup the first underlying model of the system.);
learning an AI model using the user-selected document assigned to the classification block (Sutherland, pa 0162, At step the server device may classify the at least one document into at least two classes using the machine learning model);
notifying whether the AI model classifies the plurality of documents, wherein the AI model learned with the user-selected document in relation to the classification block (Sutherland, pa 0184, At step S304, the server device 20 may provide for display the document obtained at step S300 and the attention information obtained at step S302 … the server device 20 may further provide for display the classification result of the document (e.g., relevant or irrelevant; see also, step S202 of FIG. 6) and/or the category assigned to the document (e.g., classification with low credibility); and
classifying the plurality of documents using the AI model learned with the user- selected document assigned to the classification block, according to a request of the user (Sutherland, pa 0190, each of the documents classified by the ANN model is assigned to a "confident" category or a "unconfident" category, based on a confidence value representing how confident the ANN model is regarding its classification result for the document).
With respect to claim 2, Sutherland teaches the AI-based document classification method of claim 1, wherein the learning the AI model comprises:
learning the AI model the user-selected document with the classification block, when the user selects the document and assigns the document to the classification block (Sutherland, pa 0201, a random subset may be selected from available, unlabeled, documents to be manually classified. The manual classification may then be used for training the machine learning model 50 to setup the first underlying model of the system.).
With respect to claim 3, Sutherland teaches the AI-based document classification method of claim 1, further comprises:
generating a new classification block corresponding to the classification block, when the AI model classifies the plurality of documents into the classification block (Sutherland, pa 0172, At step S206, the server device 20 may assign, to each of the at least one document, based at least in part on the confidence value, one of at least two categories that are associated with different degrees of credibility of the classification performed by the machine learning model 50).
With respect to claim 4, Sutherland teaches the AI-based document classification method of claim 3, wherein the new classification block includes the documents assigned to the classification block (Sutherland, pa 0172, in case of assigning one of two categories (e.g., credible and uncredible; confident and unconfident, etc.), a document may be assigned a category with a higher degree of credibility if the confidence value for the classification result of that document exceeds a specified threshold value.) or excludes the documents assigned to the classification block.
With respect to claim 5, Sutherland teaches the AI-based document classification method of claim 1, wherein the notifying comprises:
determining an indication of the classification block to represent whether the AI model is capable of classification for the classification block or to represent the level of understanding of the user's classification intent by the AI model (Sutherland, pa 0186, The display of the document and the attention information at step S304 may facilitate the decision on whether the document indeed belongs to the class identified by the machine learning model 50 (e.g., whether the document indeed is relevant for the interest of the user).).
With respect to claim 6, Sutherland teaches the AI-based document classification method of claim 1, wherein the notifying comprises:
displaying a message to describe that the AI model is capable of classifying the classification block, in a classification interaction area (Sutherland, pa 0184, At step S304, the server device 20 may provide for display the document obtained at step S300 and the attention information obtained at step S302 … the server device 20 may further provide for display the classification result of the document (e.g., relevant or irrelevant; see also, step S202 of FIG. 6) and/or the category assigned to the document (e.g., classification with low credibility).
With respect to claim 7, Sutherland teaches the AI-based document classification method of claim 6, wherein the classification interaction area displays at least one of (i) a message explaining the method of classifying documents using the AI model (Sutherland, pa 0184, At step S304, the server device 20 may provide for display the document obtained at step S300 and the attention information obtained at step S302 … the server device 20 may further provide for display the classification result of the document (e.g., relevant or irrelevant; see also, step S202 of FIG. 6) and/or the category assigned to the document (e.g., classification with low credibility & pa 0185, at step S304, the attention information may be provided for display so as to display the one or more parts of the document in manners different from each other based on the significance of the respective part or parts indicated by the attention information.), (ii) a message for selecting the method of classifying documents using the AI model, or (iii) a message indicating that the AI model has completed document classification.
Claims 8-17 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Asermely (US 12,340,612).
With respect to claim 8, Asermely teaches an AI (Artificial Intelligence)-based document classification method performed by a computing device comprises:
displaying an indication to represent whether an AI model can classify for the classification block selected by the user (Asermely, Col. 2 Li. 60-65, The online document system may recognize component documents within a document package using a set of rules defining potential component documents that may appear within the received document package and one or more methods of recognizing each type of component document & Col. 11 Li. 44-52, the document recognition module 320 first determines an appropriate package template 410 to apply to the document package (for example automatically, based on a selection by an importing user… Then the document recognition module 320 applies each document identification rule 430 associated with the package template 410 to the document package to identify one or more component documents within the document package. & Col. 12 Li. 38-41, The unrecognized document module 340 may display to an importing user 130 (or other authorized user 130) an interface identifying unrecognized pages in the document package. Examiner note: displayed indication of classification is represented by the display of unrecognized pages. Documents of package have been classified appropriately according to the rules of the package, including the classification of “unrecognized.” Classification block is represented by the package template); and
classifying documents selected by the user using the AI model, when a request for document classification with respect to the classification block is received from the user (Asermely, Col. 2 Li. 49-52, the online document system can provide a user interface (UI) for a user to import document packages containing multiple different individual document files. & Col. 11 Li. 44-52, the document recognition module 320 first determines an appropriate package template 410 to apply to the document package (for example automatically, based on a selection by an importing user… Then the document recognition module 320 applies each document identification rule 430 associated with the package template 410 to the document package to identify one or more component documents within the document package. Examiner note: by identifying component documents according to rules, the system classifies documents.), wherein the AI model is a model learned for association documents with classification blocks (Asermely, Col. 13 Li. 23-32, the unrecognized document module 340 can use probabilistic methods (such as trained machine learning models) to supplement the generally deterministic document identification rules 430. For example, the unrecognized document module 340 may train a machine learning model to automatically assign (or make suggestions to assign) unrecognized pages based on logged sets of unrecognized pages and corresponding manual changes/assignments made for previous uploaded document packages associated with the same package template 410.), when the user assigns documents to the classification block (Asermely, Col. 11 Li. 44-52, the document recognition module 320 first determines an appropriate package template 410 to apply to the document package (for example automatically, based on a selection by an importing user…).
With respect to claim 9, Asermely teaches the AI-based document classification method of claim 8, further comprises:
generating a new classification block corresponding to the classification block (Asermely, Col. 15 Li. 22-25, a package administrator of the package template can update 870 the document identification rules of the package template based on the assignments of any identified unrecognized pages.), when the AI model classifies the plurality of documents into the classification block (Asermely, Col. 15 Li. 7-11, If there are one or more unrecognized pages, the online document system assigns 850 the unrecognized pages to documents and document stacks based on user input (a manual assignment) and/or a supplementary probabilistic identification method).
With respect to claim 10, Asermely teaches the AI-based document classification method of claim 9, wherein the new classification block includes the documents assigned to the classification block (Asermely, Col. 11 Li. 55-64, the sorting module 330 can assign each recognized component document to the appropriate document stack(s) 420 based on the package template 410 and split the component document out of the document package. The sorting module 330 can then determine if there are any unrecognized pages not associated with a component document and/or document stack in the document package. The unrecognized pages of a document package can be assigned to a temporary unrecognized page stack for resolution by the unrecognized document module 340.) or excludes the documents assigned to the classification block.
With respect to claim 11, Asermely teaches the AI-based document classification method of claim 8, wherein the displaying comprises:
determining an indication of the classification block to represent whether the AI model is capable of classification for the classification block or to represent the level of understanding of the user's classification intent by the AI model (Asermely, Col. 12 Li. 38-40, The unrecognized document module 340 may display to an importing user 130 (or other authorized user 130) an interface identifying unrecognized pages in the document package).
With respect to claim 12, Asermely teaches the AI-based document classification method of claim 8, wherein the displaying comprises:
displaying a message to describe that the AI model is capable of classifying the classification block, in a classification interaction area (Asermely, Col. 12 Li. 49-53, the unrecognized document module 340 also provides an importing user 130 (or other appropriate user(s) 130) an interface for reviewing the automatically recognized documents/document pages and overriding the default stack actions 425 or stack assignments for that document package).
With respect to claims 13-17, Asermely teaches a computing device performing an AI-based document classification method, wherein computing device comprising a processor (Asermely, Col. 15 Li. 52-56), with limitations similar to claims 8-12, and are rejected for the same reasons.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRITTANY N ALLEN whose telephone number is (571)270-3566. The examiner can normally be reached M-F 9 am - 5:00 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sherief Badawi can be reached at 571-272-9782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BRITTANY N ALLEN/ Primary Examiner, Art Unit 2169