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 .
DETAILED ACTION
The office action sent in response to Applicant’s communication received on 6/28/2024 for the application number 18757818. The office hereby acknowledges receipt of the following placed of record in the file: Specification, Abstract, Oath/Declaration and claims.
Status of the claims
Claims 1-14 are presented for examination.
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.
Claim limitation “8-13 ” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Claims 8-13 includes web crawler, preprocessing module, statistical analysis module, assessment module and reporting module. Claim 11 included performance module and claim 12 includes security testing module. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
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 1-14 are rejected under 101.
Claim 1 includes:
A method for assessing and enhancing the quality of Arabic language content on a website, the method comprising: i. Actively scanning the website to collect Arabic language text; ii. Preprocessing the collected text to normalize formatting and remove irrelevant content; iii. Processing the preprocessed text using a deep learning model trained on a corpus of correct Arabic usage to detect errors in the text, wherein the errors relate to at least one of spelling, contextual, grammatical, morphological, semantic, stylistic, linguistic politeness, separation and merging, punctuation, names, and quotations, iv. Generating statistical data on the frequency and types of detected errors, v. Analyzing the statistical data to assess at least one of the data integrity and security risks of the website and vi. Outputting a report comprising at least the detected errors, their locations in the text, and the generated statistical data.
Steps i is a data gathering step
Steps ii, iii, iv, v, and vi are mental steps. A human who knows the language would be able to remove punctuations etc. from the language and look for the spelling mistakes, grammatical errors etc. . Based on the mistakes human can do the statistical analysis and determines the integrity and the security of the source the data was obtained from and create a report of the mistakes
Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. The claim recites at least a method and hence a process. Thus, the claim is , recites a statutory categories of invention. (Step 1: YES).
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. As discussed above, the broadest reasonable interpretation of steps (a)-(c) that those steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. Steps ii, iii, iv, v, and vi are mental steps. A human who knows the language would be able to remove punctuations etc. from the language and look for the spelling mistakes, grammatical errors etc. . Based on the mistakes human can do the statistical analysis and determines the integrity and the security of the source the data was obtained from and create a report of the mistakes Hence, these steps can be performed by a human, using “observation, evaluation, judgment, [and] opinion,” because they involve making doing analysis on the given data which are mental tasks humans routinely do,' ” and thus can practically be performed in the human mind, In re Killian, 45 F.4th 1373, 1379 (Fed. Cir. 2022). Therefore, these limitations are considered together as a abstract idea for further analysis. (Step 2A, Prong One: YES).
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This 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. See MPEP 2106.04(d). Claim requires Actively scanning the website to collect Arabic language text which is a data gathering activity. The limitations of deep learning model provide nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05. At Step 2A, Prong Two, the second additional element in step “using a deep neural network,” was found to represent no more than mere instructions to apply the judicial exception on a computer using generic computer components. The analysis under Step 2A, Prong Two is carried through to Step 2B. Further, step i was found to be insignificant extra-solution activity. However, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. See MPEP 2106.05, subsection I.A. At Step 2B, the re-evaluation of the insignificant extra-solution activity consideration takes into account whether or not the extra-solution activity is well understood, routine, and conventional in the field. See MPEP 2106.05(g). Here, Actively scanning the website to collect Arabic language text mere data gathering that is recited at a high level of generality, and as discussed in the disclosure, is well-understood (The system operates by first employing a web crawler to scan the target websites and collect Arabic text content systematically. ). Therefore, this limitation remains insignificant extra solution activity even upon reconsideration and does not amount to significantly more. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, and therefore do not provide an inventive concept (Step 2B: NO). The claim is not eligible.
Claims 2-5, 7, 9-13 can be performed by human mind since human can look at the website/online content and make determination based on that. Additionally, human can provide recommendation to correct errors in the content.
Claim 6 add additional element of transformer model as deep learning model. However as discussed for claim 1, transformer model is a computer component which is implements in place of human mind to perform mental activity.
Regarding claims 8 and 14, analysis analogous to claim 1, are applicable.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
And
KSR, 550 U.S. at 418, 82 USPQ2d at 1396. Exemplary rationales that may support a conclusion of obviousness include:
(A) Combining prior art elements according to known methods to yield predictable results;
(B) Simple substitution of one known element for another to obtain predictable results;
(C) Use of known technique to improve similar devices (methods, or products) in the same way;
(D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results;
(E) "Obvious to try" – choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success;
(F) Known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art;
(G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention.
See MPEP § 2143 for a discussion of the rationales listed above along with examples illustrating how the cited rationales may be used to support a finding of obviousness. See also MPEP § 2144 - § 2144.09 for additional guidance regarding support for obviousness determination.
Claims 1-2, 6-9 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Phyu ( Exploring the Impact of Error Type Features Integration on Transformer-based Myanmar Spelling Correction) and further in view of Dixon (US 20120185942) and further in view of Ahmad ( US 20250077774)
Regarding claim 8, Phyu teaches a system for assessing and enhancing the quality of Arabic language content on a website, the system comprising:
A web crawler configured to scan and collect text from the website ( collect text, Introduction)
A preprocessing module to normalize and clean the collected text ( remove emoji, punctuation etc., Under model development)
A deep learning model for detecting and classifying errors in the text, trained on a corpus of correct Arabic usage ( error type classification, Experimental results)
A statistical analysis module to generate data on error frequency and types ( frequency of error type, Table VI)
A reporting module to output a report detailing the detected errors, their locations, and the statistical data ( Table V-VIII) .
Phyu does not teach v. An assessment module to analyze data integrity and security risks based on the statistical data
However, Dixon teaches An assessment module to analyze data integrity and security risks based on the statistical data ( heuristic determines the potential reputation issue ( risk and integrity and security) , Para 0193; wherein heuristic includes spelling errors, Claim 24-25; further determines reputation, Para 0248)
It would have been obvious having the teachings of Phyu to further include the concept of Dixon before effective filing date to make the user informed about the reputation of the website ( Para 0006, Dixon)
Phyu does not explicitly teach collect Arabic text and determining spelling mistakes and v. An assessment module to analyze data integrity and security risks based on the statistical data
However, Ahmad teaches Arabic text and determine the error of the Arabic text ( plotting percentage of error character, Para 0111)
It would have been obvious having the concept of Phyu and Dixon to further include the concept of Ahmad before effective filing date to substitute Arabic for Myanmar language in Phyu so that the spell checks can be done for Arabic also and the results would have been predictable to generate Arabic content ( Abstract, Ahmad)
Regarding claim 2, Ahmad as above in claim 1, teaches wherein preprocessing the collected text further comprises:
Segmenting the text into analyzable units , and
Normalizing diacritics and orthographic variations specific to the Arabic language ( components such as URLs, symbols, punctuation marks, white spaces, diacritics, and Kashida characters are removed, producing a normalized sequence. This sequence is then further refined by consolidating characters that appear in varied forms into single form of character. The consolidated sequence undergoes tokenization, generating multiple tokens, Abstract)
Regarding claim 6, Phyu as above in claim 1, wherein the deep learning model is a Transformer model trained on a large dataset of Arabic text, capable of suggesting corrections for the detected errors ( transformer model, Introduction)
Regarding claim 7, Phyu as above in claim 1, teaches wherein the statistical data generated is utilized to create visual representations such as graphs and charts for easier interpretation and analysis ( report, Table I-VII) .
Regarding claim 9, Phyu as above in claim 8, teaches a user interface for displaying the report, configuring system settings, and visualizing statistical data ( report, Table I-VII) .
Regarding claim 14, Phyu teaches a non-transitory computer-readable medium storing instructions that, when executed by a processor, cause a computer to perform the method of claim 1 ( models )
Regarding claim 1, arguments analogous to claim 1, are applicable.
Claims 3 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Phyu ( Exploring the Impact of Error Type Features Integration on Transformer-based Myanmar Spelling Correction) and further in view of Dixon (US 20120185942) and further in view of Ahmad ( US 20250077774) and further in view of Lund (EP 4180993 )
Regarding claim 10, Phyu modified by Ahmad and as above in claim 8, does not explicitly teach teaches tools for search engine optimization, including keyword density analysis, meta tag evaluation, and link health monitoring
However, Lund teaches tools for search engine optimization, including keyword density analysis, meta tag evaluation, and link health monitoring ( Example SEO insights can include, but is not limited to, visibility in search engine results, keyword monitoring, search engine analytics, content optimization, target page optimization, competitor analysis, target page metrics, particular SEO-related issues (e.g., focus issues), low-value backlinks, duplicative content, and misspellings, Para 0005)
It would have been obvious having the teachings of Phyu and Dixon and Ahmad to further include the concept of Lund before effective filing date to inform the user about the potential issues with the website (Abstract, Lund)
Regarding claim 3, arguments analogous to claim 10, are applicable. In addition, Lund teaches alt attributes ( Example SEO insights can include, but is not limited to, visibility in search engine results, keyword monitoring, search engine analytics, content optimization, target page optimization, competitor analysis, target page metrics, particular SEO-related issues (e.g., focus issues), low-value backlinks, duplicative content, and misspellings, Para 0005, Fig 1-3)
Claims 4-5, and 11-13 are rejected under 35 U.S.C. 103 as being unpatentable over Phyu ( Exploring the Impact of Error Type Features Integration on Transformer-based Myanmar Spelling Correction) and further in view of Dixon (US 20120185942) and further in view of Ahmad ( US 20250077774) and further in view of Gorny (US 20170324760)
Regarding claim 11, Phyu modified by Dixon and Ahmad as above in claim 8, teaches a performance monitoring module to track metrics such as page load speed, content load speed, and server error
However, Gorny teaches a performance monitoring module to track metrics such as page load speed, content load speed, and server error ( Website performance characteristics may include median load time and/or speed percentile, such as may be measured by third-party services like ALEXA, and the like, Para 0055; erroneous web page, repair server, Para 0004, 009)
It would have been obvious having the concept of Phyu and Dixon and Ahmad to further include the concept of Gorny to inform the user about the vulnerabilities of the website and give the solution to fix it ( Para 0008-0010, Gorny)
Regarding claim 12, Phyu modified by Dixon and Ahmad as above in claim 8, security testing module for automated vulnerability scanning and penetration testing
However, Gorny teaches security testing module for automated vulnerability scanning and penetration testing
( security testing methods may include, but are not limited to, sequel injection testing, phantom web page testing, open source security testing, penetration testing, cross-site scripting (XSS) testing, carriage return and line feed injection testing, Para 0005)
It would have been obvious having the concept of Phyu and Dixon and Ahmad to further include the concept of Gorny to inform the user about the vulnerabilities of the website and give the solution to fix it ( Para 0008-0010, Gorny)
Regarding claim 13, Phyu modified by Dixon and Ahmad as above in claim 8, does not teach
wherein the reporting module provides actionable recommendations for improving the quality, performance, and security of the website
However, Gorny teaches wherein the reporting module provides actionable recommendations for improving the quality, performance, and security of the website (valuation driven action, Para 0009-0010, 0076, 0076, Fig 3)
It would have been obvious having the concept of Phyu and Dixon and Ahmad to further include the concept of Gorny to inform the user about the vulnerabilities of the website and give the solution to fix it ( Para 0008-0010, Gorny)
Regarding claim 4, arguments analogous to claim 11, are applicable.
Regarding claim 5, arguments analogous to claim 12, are applicable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 12184685 B2
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Richa Sonifrank whose telephone number is (571)272-5357. The examiner can normally be reached M-T 7AM - 5:30PM.
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/Richa Sonifrank/Primary Examiner, Art Unit 2654
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