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 .
Response to Amendment
Applicant's amendment filed on May 22, 2025 has been entered. Claims 1 – 20 have been amended. No claims have been canceled. No claims have been added. Claims 1 – 20 are still pending in this application, with claims 1, 8 and 15 being independent.
Response to Arguments
Applicant's arguments filed May 22, 2025 have been fully considered.
Regarding Claim Rejections under 35 USC § 101
The Applicant alleges: “
The Office Action rejected claims 1-20 under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception. Applicant respectfully traverses these rejections for at least the following reasons.
For example, Applicant submits that under Step 2A, Prong 2, Applicant's claim recites features that integrate the alleged abstract idea into a practical application. As noted in Applicant's Specification:
In at least one embodiment, for example, labeled text identified by an OCR model not being trained (which may be implemented using one or more neural networks) may be compared with labeled text (or the lack
of/missing labeled text) with a multimodal OCR model under training, in
order to identify missing or mislabeled objects within document 102a. In at
least one embodiment, modifications may be made to document 102a in
order to remove missing or mislabeled objects, which may allow for a
modified document to be used in a subsequent training round and
improve a multimodal OCR model as missing or mislabeled objects
may not bias training to unknown examples.
Id. at paragraph [0057] (emphasis added). In this way,
In at least one embodiment, multimodal OCR training system 110 may
implement multimodal data generator 120 to generate different versions of
documents to improve training and, ultimately, accuracy of a multimodal
OCR model implemented as one or more neural networks, by comparing
results of different neural networks, such as a multimodal OCR neural
network being trained and one or more other OCR neural networks, to
improve performance of text identification and reading order generated by a multimodal OCR neural network, which can consume less computing
resources (e.g., memory, disk-space and or other I/O bandwidth) and
improve speed (e.g., faster inferencing to identify text and reading order)
with greater accuracy.
Id. at paragraph [0056] (emphasis added).
As stated by the MPEP 2106.04(d), under Step 2A, Prong 2 "[t]his evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application," (Emphasis added), and
[o]ne way to determine integration into a practical application is when the
claimed invention improves the functioning of a computer or improves
another technology or technical field. To evaluate an improvement to a
computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement.
MPEP 2106.04(d)(1) and 2106.05(a), (emphasis added).
The claimed system provides significant technical advantages including improved computing efficiency and speed in identifying text in documents multiple data modalities by comparing and removing unlabeled text. Applicant therefore respectfully submits that the claims recite statutory subject matter and respectfully request withdrawal of these rejections.
Examiner’s response:
The Examiner respectfully disagrees.
The claimed limitations, read as a whole, can be interpreted as a cognitive process of comparing labeled and unlabeled portions of text in the document to identify patterns, and then, adding basic human reasoning step of sorting, filtering or removing data—such as unlabeled text. Thus, the claimed limitation can be categorized as mental processes, mathematical concept, method of organizing human activity, or a combination thereof (see rejection below for details).
The additional elements (e.g., receive a document, neural networks, system, and processor) are mere instructions to implement an abstract idea uses a computer as a tool to perform an abstract idea.
Thus, the recited generic additional elements (e.g., receive a document, neural networks, system, and processor) perform no more than their basic computer function. Generic computer-implementation of a method is not a meaningful limitation that alone can amount to significantly more than an abstract idea. Moreover, when viewed as a whole with such additional element considered as an ordered combination, claims modified by adding a generic memory are nothing more than a purely conventional computerized implementation of an idea in the general field of computer processing and do not provide significantly more than an abstract idea.
Therefore, the § 101 rejection is still maintained.
Regarding Claim Rejections under 35 USC § 103
The Applicant’s argument (pages 6 – 7) is persuasive. The claims amendment overcomes the prior art of the record. After a further search, no reference is found. Therefore, the §103 rejection is removed.
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 a judicial exception (i.e. an abstract idea) without significantly more.
Regarding claims 1, 8 and 15:
Step 1:
Claims 1, 8 and 15 are directed towards a process, machine, manufacture or composition of matter which is/are statutory subject matter.
Step 2A:
Prong 1:
Claims 1, 8 and 15 are directed an idea for identifying text which is an abstract idea.
Consideration of the claimed elements:
Regarding claims 1, 8 and 15:
The claims in the instant application include:
receive a document comprising different portions corresponding to different data modalities including text;
cause one or more neural networks to identify one or more portions of text in the document based, at least in part, on:
comparing labeled text identified by one or more second neural networks to unlabeled text identified by one or more first neural networks; and
removing the unlabeled text from a multimodal data set comprising the different data modalities and used to update the one or more neural networks.
Regarding “cause one or more neural networks to identify one or more portions of text in the document based, at least in part, on: comparing labeled text identified by one or more second neural networks to unlabeled text identified by one or more first neural networks”, it can be interpreted as a cognitive process of comparing labeled and unlabeled portions of text in the document to identify patterns or a mathematical algorithm that could theoretically be performed mentally or with pen and paper, even if impractical. The claimed limitation can be categorized as mental processes or mathematical concept.
Regarding “removing the unlabeled text from a multimodal data set comprising the different data modalities and used to update the one or more neural networks”, it is a basic human reasoning step of sorting, filtering or removing data—such as unlabeled text. The claimed limitation can be categorized as mental processes or method of organizing human activity.
Prong 2:
The claims include additional elements of
receive a document comprising different portions corresponding to different data modalities including text;
neural networks;
system, processor.
Regarding “receive a document comprising different portions corresponding to different data modalities including text”, it is considered as data gathering of adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g.
Regarding “neural networks, system, and processor”, they are considered as to use a general computational hardware/software. It is considered as “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
They are mere instructions to implement an abstract idea uses a computer as a tool to perform an abstract idea.
Moreover, the claim limitations that are not indicative of integration into a practical application.
Thus, the recited generic additional element (e.g., receive a document, neural networks, system, and processor) perform no more than their basic computer function. Generic computer-implementation of a method is not a meaningful limitation that alone can amount to significantly more than an abstract idea. Moreover, when viewed as a whole with such additional element considered as an ordered combination, claims modified by adding a computational algorithm, a generic memory and processor are nothing more than a purely conventional computerized implementation of an idea in the general field of computer processing and do not provide significantly more than an abstract idea.
Accordingly, the claims are directed to an idea of itself, and therefore not patent eligible.
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception such as improvements to another technology or technical field, or other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
Moreover, the claim language that may be separate from the abstract idea (i.e., additional elements) include computer processors, computer-readable storage media.
The additional element (e.g., receive a document, neural networks, system, and processor) simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (WURC) - see MPEP 2106.05(d) and 2106.07(a)III.
Thus, the recited generic additional elements (e.g., receive a document, neural networks, system, and processor) perform no more than their basic computer function. Generic computer-implementation of a method is not a meaningful limitation that alone can amount to significantly more than an abstract idea. Moreover, when viewed as a whole with such additional element considered as an ordered combination, claims modified by adding a generic memory are nothing more than a purely conventional computerized implementation of an idea in the general field of computer processing and do not provide significantly more than an abstract idea.
Consequently, the identified additional elements taken into consideration individually or in combination fails to amount of significantly more than the abstract idea above.
Regarding claims 2 – 7, 9 – 14 and 16 – 20, the rejection is based on the same rationale described for claims 1, 8 and 15 because the claims include/inherit the same/similar type of problematic limitation(s) as claims 1, 8 and 15, wherein limitations regarding additional aspect for process; "are used ... ", “is identified …”, “store …”, “are trained …”, “removing …” and “provide …”, is/are of sufficient breadth that it would be substantially directed to or reasonably interpreted as a part of the “mental processes” as the abstract idea (similar to claim as stated above). It is noted that further additional limitation is merely generic/conventional computer component/steps to implement the abstract idea, which is, individually or in combination, not sufficient to amount to significantly more than the judicial exception. Therefore, the claimed invention as a whole is directed to an ineligible subject matter.
Claim Rejections - 35 USC § 102/103
The Applicant’s argument (pages 6 – 7) is persuasive. The claims amendment overcomes the prior art of the record. After a further search, no reference is found.
The closest reference Li et al. (US 2022/0269862) teaches systems and methods for weakly-supervised training a machine-learning model to perform named-entity recognition. All possible entity candidates and all possible rule candidates are automatically identified in an input data set of unlabeled text. An initial training of the machine-learning model is performed using labels assigned to entity candidates by a set of seeding rules as a first set of training data. The trained machine-learning model is then applied to the unlabeled text and a subset of rules from the rule candidates is identified that produces labels that most accurately match the labels assigned by the trained machine-learning model. The machine-learning model is then retrained using the labels assigned by the identified subset of rules as the second set of training data.
However, Li, alone or in a combination, fails to teach the claimed limitations in the independent claims.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to QIAN YANG whose telephone number is (571)270-7239. The examiner can normally be reached on Monday-Thursday 8am-6pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Bee can be reached on 571-270-5183. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/QIAN YANG/
Primary Examiner, Art Unit 2677
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