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 .
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 judicial exception(s) without significantly more.
[STEP 1] The claim recites at least one step or structure. Thus, the claim is to a process or product, which is one of the statutory categories of invention (Step 1: YES).
[STEP2A PRONG I] The claim(s) 1, 12 and 18 recite(s):
1.An artificial intelligence-based (AI-based) method for identifying error cause, the method comprising:
responding to a user's upload operation of at least one draft paper file for at least one target question, wherein the draft paper file comprises one or more problem-solving ideas or problem-solving steps generated by the user for the target question;
acquiring at least one current user error cause generated by an error cause analysis model based on the at least one of the problem-solving idea or the problem-solving step; and determining an error cause analysis result of the draft paper file according to the current user error cause, and
displaying the error cause analysis result on an answer page of the target question.
12. An artificial intelligence-based (Al-based) apparatus for identifying error cause, the apparatus comprising:
an operation response assembly, configured to respond to a user's upload operation of at least one draft paper file for at least one target question, wherein the draft paper file comprises one or more problem-solving ideas or problem-solving steps generated by the user for the target question;
an error cause acquisition assembly, configured to acquire at least one current user error cause generated by a trained error cause analysis model based on the at least one of the problem-solving idea or the problem-solving step; and
a result generation assembly, configured to determine an error cause analysis result of the draft paper file according to the current user error cause, and display the error cause analysis result on an answer page of the target question.
18. An electronic device, comprising:
at least one processor; and
a memory communicatively connected with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program are executed by the at least one processor to enable the at least one processor to perform acts comprising:
responding to a user's upload operation of at least one draft paper file for at least one target question, wherein the draft paper file comprises one or more problem-solving ideas or problem-solving steps generated by the user for the target question;
acquiring at least one current user error cause generated by an error cause analysis model based on the at least one of the problem-solving idea or the problem-solving step; and determining an error cause analysis result of the draft paper file according to the current user error cause, and
displaying the error cause analysis result on an answer page of the target question.
The non-highlighted aforementioned limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation between people but for the recitation of generic computer components. That is, other than reciting “electronic device”, “memory” and “processor” nothing in the claim element precludes the step from practically being performed between people. For example, but for the recited language, the step in the context of this claim encompasses a teacher observing students’ essay submission, determining an error on at least one of the problem-solving idea or step and displaying to the user the cause of the error.
If a claim limitation, under its broadest reasonable interpretation, covers managing interactions between people, then it falls within the “Organization of Human Activity” grouping of abstract ideas. In this particular case, the claims limitation is akin to the activities a teacher would perform when they received a draft paper from a student, analyzing the paper, determining what error is contained in the draft paper and providing feedback to the student.
Accordingly, the claim recites a judicial exception, and the analysis must therefore proceed to Step 2A Prong Two.
[STEP2A PRONG II] This judicial exception is not integrated into a practical application. In particular, the claim only recites the additional element(s) – “artificial intelligence”, “electronic device”, “processor”, “memory”.
The “artificial intelligence”, “electronic device”, “processor”, “memory” .in the aforementioned steps are recited at a high-level of generality such that it amounts no more than generally linking the use of a judicial exception to a particular a particular technological environment or field of use.
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. (Step 2A: YES).
[STEP2B] The claim does 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 element of using a processor to perform the aforementioned steps amounts to no more than mere instructions to apply the exception using a generic computer component, which cannot provide an inventive concept (for example, see paragraph 71-72 evidence of generic computing element, 94 the use of commercially available ChatGPT4 or open-source models such as Llama).
As noted previously, the claim as a whole merely describes how to generally “apply” the aforementioned concept in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
The claim is not patent eligible. (Step 2B: NO).
Claim(s) 2-11, 13-17 and 19-20 are dependent on supra claim(s) and includes all the limitations of the claim(s). Therefore, the dependent claim(s) recite(s) the same abstract idea. For example, claims 2-4, 8-11, 13-15 are abstract idea directed to the treatment of the error cause; claims 5-7 and 19-20 are abstract ideas directed to providing display to the user’s upload operation or displaying knowledge analysis. These claims recite no additional limitations. Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “an operation response assembly configured to”, “an error cause acquisition assembly“, “a result generation assembly“ in claim 12; “an error cause pool locator”, “error cause type determiner”, “a first result determiner”, “second result determiner”, in claim 13; “an error cause type acquirer”, “a third result determiner”, “a knowledge point determiner”, “a fourth result determiner” in claim 14.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
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 11, 12-17 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. The limitation of claims 12-14 have been determined to be a computer-implemented means plus function accordingly the specification must disclose an algorithm (or structure) for performing the claimed specific computer function. For claim 12, the specification is silent on the corresponding algorithm for the limitation “an operation response assembly configured to”, “an error cause acquisition assembly“, “a result generation assembly“. A review of specification paragraph 13-15, 83-90 only provides the same language that can be found in the claim 12 or only provide a description of a desired result, and without describing the algorithm or structure that achieve that claimed result. As such, it does not meet the requirement of disclosing the algorithm (or structure) for performing the function of “an operation response assembly configured to”, “an error cause acquisition assembly “, “a result generation assembly “.
A review of the limitation of claim 13 also contains the same issues. The specification as currently provided does not provide a description of the structure and computer algorithm necessary to the interpretation of the claimed “an error cause pool locator”, “error cause type determiner”, “a first result determiner”, “second result determiner” as a computer-implemented means plus function. The specification paragraph 31-34 only provides a description of a desired result, and without describing the algorithm or structure that achieve that claimed result. As such, it does not meet the requirement of disclosing the algorithm (or structure) for performing the function of“an error cause pool locator”, “error cause type determiner”, “a first result determiner”, “second result determiner”.
Similarly, claim 14 also contains the same issues. The specification as currently provided does not provide a description of the structure and computer algorithm necessary to the interpretation of the claimed “an error cause type acquirer”, “a third result determiner”, “a knowledge point determiner”, “a fourth result determiner”. The specification paragraph 36-39 only provides a description of a desired result, and without describing the algorithm or structure that achieve that claimed result. As such, it does not meet the requirement of disclosing the algorithm (or structure) for performing the function of “an error cause type acquirer”, “a third result determiner”, “a knowledge point determiner”, “a fourth result determiner”. Claim 15-17 are also rejected due to its dependency to a rejected subject matter.
Claim 11 are also rejected under 35 U.S.C 112(b) 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. In this particular case, it is unclear what the applicant meant by “pushing the associated question”. A review of the specifications on paragraph 20 and 66 do not provide clarification of the phrase. At best that the examiner understood “pushing the associated question” can be interpreted as either removing the questions or adding the questions. Accordingly, clarification on claim 11 is needed.
Claims 12-17 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. When a claim containing a computer-implemented 35 U.S.C. 112(f) claim limitation is found to be indefinite under 35 U.S.C. 112(b) for failure to disclose sufficient corresponding structure (e.g., the computer and the algorithm) in the specification that performs the entire claimed function, it will also lack written description under section 112(a) (see MPEP 2181 IV). As such, the limitation of claim 12-17 are also rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. Please review the rejection of claim 12-17 under 35 U.S.C 112(b) above.
Claim Rejections - 35 USC § 102
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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 12, 17-19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Liu et al1
Claim 1: The Liu et al reference provides a teaching of an artificial intelligence-based (AI-based) method for identifying error cause (abstract), the method comprising:
responding to a user's upload operation of at least one draft paper file for at least one target question, wherein the draft paper file comprises one or more problem-solving ideas or problem-solving steps generated by the user for the target question (see page 5 section 3.3 examples of 13 different papers submitted for review);
acquiring at least one current user error cause generated by an error cause analysis model based on the at least one of the problem-solving idea or the problem-solving step (see page 13 last 4 paragraph of different errors that the AI reviewed detect. In this case, the paper lacks any details of the proposed algorithm); and
determining an error cause analysis result of the draft paper file according to the current user error cause (see page 9 paragraph 3-6 breakdown of the error analysis),, and displaying the error cause analysis result on an answer page of the target question (see page 9 paragraph 3-6 being displayed back to the user as a feedback on their paper).
Claim 12: The Liu et al reference provides a teaching of an artificial intelligence-based (Al-based) apparatus for identifying error cause, the apparatus comprising:
an operation response assembly, configured to respond to a user's upload operation of at least one draft paper file for at least one target question, wherein the draft paper file comprises one or more problem-solving ideas or problem-solving steps generated by the user for the target question (see page 5 section 3.3 examples of 13 different papers submitted for review);
an error cause acquisition assembly, configured to acquire at least one current user error cause generated by a trained error cause analysis model based on the at least one of the problem-solving idea or the problem-solving step (see page 13 last 4 paragraph of different errors that the AI reviewed detect. In this case, the paper lacks any details of the proposed algorithm); and
a result generation assembly, configured to determine an error cause analysis result of the draft paper file according to the current user error cause (see page 9 paragraph 3-6 breakdown of the error analysis), and display the error cause analysis result on an answer page of the target question (see page 9 paragraph 3-6 being displayed back to the user as a feedback on their paper).
Claim 18: While the Liu et al is silent on the disclosure of at least one processor; and a memory communicatively connected with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program are executed by the at least one processor to enable the at least one processor; the examiner takes the position that Liu’s disclosure of the use of LLM and ChatGPT ( page 4 paragraph 2 and page 5 paragraph 3) inherently requires a processor, memory and a program that performs recited function)to perform acts comprising:
responding to a user's upload operation of at least one draft paper file for at least one target question (see page 5 section 3.3 examples of 13 different papers submitted for review), wherein the draft paper file comprises one or more problem-solving ideas or problem-solving steps generated by the user for the target question (see page 12 last paragraph – page 13 first paragraph as an example of a paper that discusses statistical model for noisy pairwise comparisons);
acquiring at least one current user error cause generated by an error cause analysis model based on the at least one of the problem-solving idea or the problem-solving step (see page 13 last 4 paragraph of different errors that the AI reviewed detect. In this case, the paper lacks any details of the proposed algorithm); and
determining an error cause analysis result of the draft paper file according to the current user error cause (see page 9 paragraph 3-6 breakdown of the error analysis), and displaying the error cause analysis result on an answer page of the target question (see page 9 paragraph 3-6 being displayed back to the user as a feedback on their paper).
Claim 6, 17 and 19: The Liu reference provides a teaching of wherein the responding to a user's upload operation of at least one draft paper file for at least one target question comprises:
responding to the user's answer operation for the target question, to take an electronic draft paper as the draft paper file when the electronic draft paper is detected (see page 16 paragraph 5); and
responding to the user's upload operation of the electronic draft paper (see page 20 paragraph 1-2).
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) 2-5, 8-11, 13-16 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al in view of Hunter WO 2018/226106
Claim 2 and 13: The Liu et al reference is silent on the teaching of wherein the determining an error cause analysis result of the draft paper file according to the current user error cause comprises:
locating an error cause pool corresponding to the target question, wherein the error cause pool is a directed graph with target questions, error cause types, candidate user error causes, candidate error cause analysis, and candidate error cause knowledge points as various hierarchical nodes, and subordinate relationships between hierarchical nodes as directed edges; the error cause pool comprises a plurality of candidate user error causes under the same target question and the candidate error cause analysis corresponding to the plurality of candidate user error causes;
in response to determining that the current user error cause of the target question exists in the error cause pool, determining an error cause type of the current user error cause; wherein the error cause type comprises knowledge point error cause and non- knowledge point error cause;
in response to a first determination that the error cause type of the current user error cause is the knowledge point error cause, identifying at least one candidate error cause knowledge point corresponding to the current user error cause in the error cause pool, and taking an identified candidate error cause knowledge point as the error cause analysis result of the draft paper file; and
in response to a second determination that the error cause type of the current user error cause is the non-knowledge point error cause, identifying the candidate error cause analysis corresponding to the current user error cause in the error cause pool, and taking an identified candidate error cause analysis as the error cause analysis result of the draft paper file.
However, the Hunter reference provides a teaching of:
locating an error cause pool corresponding to the target question, wherein the error cause pool is a directed graph with target questions, error cause types, candidate user error causes, candidate error cause analysis, and candidate error cause knowledge points as various hierarchical nodes, and subordinate relationships between hierarchical nodes as directed edges; the error cause pool comprises a plurality of candidate user error causes under the same target question and the candidate error cause analysis corresponding to the plurality of candidate user error causes (see page 8 paragraph 4);
in response to determining that the current user error cause of the target question exists in the error cause pool, determining an error cause type of the current user error cause; wherein the error cause type comprises knowledge point error cause and non- knowledge point error cause (see page 8 paragraph 5);
in response to a first determination that the error cause type of the current user error cause is the knowledge point error cause, identifying at least one candidate error cause knowledge point corresponding to the current user error cause in the error cause pool, and taking an identified candidate error cause knowledge point as the error cause analysis result of the draft paper file (see paragraph 4 paragraph 5); and
in response to a second determination that the error cause type of the current user error cause is the non-knowledge point error cause, identifying the candidate error cause analysis corresponding to the current user error cause in the error cause pool, and taking an identified candidate error cause analysis as the error cause analysis result of the draft paper file (see paragraph 4 paragraph 6).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the with the feature of locating an error cause pool corresponding to the target question, wherein the error cause pool is a directed graph with target questions, error cause types, candidate user error causes, candidate error cause analysis, and candidate error cause knowledge points as various hierarchical nodes, and subordinate relationships between hierarchical nodes as directed edges; the error cause pool comprises a plurality of candidate user error causes under the same target question and the candidate error cause analysis corresponding to the plurality of candidate user error causes;
in response to determining that the current user error cause of the target question exists in the error cause pool, determining an error cause type of the current user error cause; wherein the error cause type comprises knowledge point error cause and non- knowledge point error cause;
in response to a first determination that the error cause type of the current user error cause is the knowledge point error cause, identifying at least one candidate error cause knowledge point corresponding to the current user error cause in the error cause pool, and taking an identified candidate error cause knowledge point as the error cause analysis result of the draft paper file; and
in response to a second determination that the error cause type of the current user error cause is the non-knowledge point error cause, identifying the candidate error cause analysis corresponding to the current user error cause in the error cause pool, and taking an identified candidate error cause analysis as the error cause analysis result of the draft paper file, as taught by the Hunter reference, in order to provides a better feedback that assesses the writer ‘s skill (see page 1 paragraph 4).
Claim 3, 14: The Liu reference is silent on the teaching of wherein the determining an error cause analysis result of the draft paper file according to the current user error cause further comprises:
in response to determining that the current user error cause of the target question does not exist in the error cause pool, acquiring an error cause type of the current user error cause generated by the error cause analysis model;
in response to the second determination that the error cause type of the current user error cause is the non-knowledge point error cause,
acquiring the error cause analysis result of the draft paper file generated by the error cause analysis model based on the current user error cause; in response to the first determination that the error cause type of the current user error cause is the knowledge point error cause,
acquiring a first error cause knowledge point that has knowledge correlation with the current user error cause generated by the error cause analysis model, wherein the knowledge correlation is determined based on a subordinate relationship between the current user error cause, the target question and a question knowledge point; and
taking a candidate error cause knowledge point matching with the first error cause knowledge point in an error cause knowledge point graph as the error cause analysis result of the draft paper file.
However, the Hunter reference provides a teaching of
in response to determining that the current user error cause of the target question does not exist in the error cause pool, acquiring an error cause type of the current user error cause generated by the error cause analysis model (see page 6 paragraph 2);
in response to the second determination that the error cause type of the current user error cause is the non-knowledge point error cause (see page 6 paragraph 4),
acquiring the error cause analysis result of the draft paper file generated by the error cause analysis model based on the current user error cause; in response to the first determination that the error cause type of the current user error cause is the knowledge point error cause (see page 6 paragraph 5),
acquiring a first error cause knowledge point that has knowledge correlation with the current user error cause generated by the error cause analysis model, wherein the knowledge correlation is determined based on a subordinate relationship between the current user error cause, the target question and a question knowledge point (see page 7 paragraph 3); and
taking a candidate error cause knowledge point matching with the first error cause knowledge point in an error cause knowledge point graph as the error cause analysis result of the draft paper file (see page 8 first paragraph).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Liu reference with the feature of:
in response to determining that the current user error cause of the target question does not exist in the error cause pool, acquiring an error cause type of the current user error cause generated by the error cause analysis model;
in response to the second determination that the error cause type of the current user error cause is the non-knowledge point error cause,
acquiring the error cause analysis result of the draft paper file generated by the error cause analysis model based on the current user error cause; in response to the first determination that the error cause type of the current user error cause is the knowledge point error cause,
acquiring a first error cause knowledge point that has knowledge correlation with the current user error cause generated by the error cause analysis model, wherein the knowledge correlation is determined based on a subordinate relationship between the current user error cause, the target question and a question knowledge point; and
taking a candidate error cause knowledge point matching with the first error cause knowledge point in an error cause knowledge point graph as the error cause analysis result of the draft paper file, as taught by the Hunter reference, in order to provides a better feedback that assesses the writer ‘s skill (see page 1 paragraph 4).
Claim 4 and 15: The Liu reference is silent on the teaching of wherein the taking a candidate error cause knowledge point matching with the first error cause knowledge point in an error cause knowledge point graph as the error cause analysis result of the draft paper file comprises:
acquiring a candidate error cause knowledge point matching with the first error cause knowledge point from the error cause knowledge point graph as a second error cause knowledge point; acquiring historical answer data of the target question, wherein the historical answer data comprises a first knowledge point set learned by learners who correctly answered the target question, and
a second knowledge point set learned by learners who incorrectly answered the target question;
taking at least one candidate error cause knowledge point that exists in the first knowledge point set but not in the second knowledge point set as a third error cause knowledge point; and
taking the second error cause knowledge point and the third error cause knowledge point as the error cause analysis result of the draft paper file.
However, the Hunter references provide a teaching of wherein the taking a candidate error cause knowledge point matching with the first error cause knowledge point in an error cause knowledge point graph as the error cause analysis result of the draft paper file comprises:
acquiring a candidate error cause knowledge point matching with the first error cause knowledge point from the error cause knowledge point graph as a second error cause knowledge point (see page 11 paragraph 1) ;
acquiring historical answer data of the target question, wherein the historical answer data comprises a first knowledge point set learned by learners who correctly answered the target question, and a second knowledge point set learned by learners who incorrectly answered the target question (see page 11 paragraph 3 );
taking at least one candidate error cause knowledge point that exists in the first knowledge point set but not in the second knowledge point set as a third error cause knowledge point (see page 12 first full paragraph); and
taking the second error cause knowledge point and the third error cause knowledge point as the error cause analysis result of the draft paper file (see page 12 second paragraph).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Liu reference with the feature of acquiring a candidate error cause knowledge point matching with the first error cause knowledge point from the error cause knowledge point graph as a second error cause knowledge point; acquiring historical answer data of the target question, wherein the historical answer data comprises a first knowledge point set learned by learners who correctly answered the target question, and a second knowledge point set learned by learners who incorrectly answered the target question; taking at least one candidate error cause knowledge point that exists in the first knowledge point set but not in the second knowledge point set as a third error cause knowledge point; and taking the second error cause knowledge point and the third error cause knowledge point as the error cause analysis result of the draft paper file, as taught by the Hunter reference, in order to provides a better feedback that assesses the writer ‘s skill (see page 1 paragraph 4).
Claim 5 and 16: The Liu reference provides a teaching of wherein the non-knowledge point error cause comprises at least one of carelessness (see page 8 paragraph 4).
Claim 8: The Liu reference is silent on the teaching of after the determining an error cause analysis result of the draft paper file according to the current user error cause, further comprising: updating the current user error cause, the error cause analysis result, and the first error cause knowledge point generated by the error cause analysis model into the error cause pool.
However, the Hunter reference provides a teaching of updating the current user error cause, the error cause analysis result, and the first error cause knowledge point generated by the error cause analysis model into the error cause pool (see page 21 paragraph 2).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Liu reference with the feature of updating the current user error cause, the error cause analysis result, and the first error cause knowledge point generated by the error cause analysis model into the error cause pool, as taught by the Hunter reference, in order to provides a better feedback that assesses the writer ‘s skill (see page 1 paragraph 4).
Claims 9 and 20: The Liu et al reference provides a teaching of before the responding to a user's upload operation of at least one draft paper file for at least one target question, the acts further comprising:
acquiring one or more of a standard answer of the target question or a user's answer content for the target question (see page 27 paragraph 4 utilizing answer checklist to evaluate the user’s answer), and
updating the draft paper file by taking the one or more of the standard answer of the target question or the user's answer content for the target question as part of the draft paper file (see page 30 last three paragraph).
Claim 10: The Liu reference is silent on the teaching of before the acquiring at least one current user error cause generated by an error cause analysis model based on the at least one of the problem-solving idea or the problem-solving step, further comprising:
acquiring historical problem-solving information, wherein the historical problem- solving information comprises a historical user error cause, a historical error cause type, and a historical error cause analysis result corresponding to one or more users' answer content for one or more target questions in one or more subjects; and
inputting the historical user error cause, the historical error cause type, and the historical error cause analysis result into a large language model, training the large language model in a supervised manner until an output result of the large language model meets a preset result for the historical user error cause, the historical error cause type, and the historical error cause analysis result, and taking the trained large language model as the error cause analysis model.
However, the Hunter reference provides a teaching of acquiring historical problem-solving information, wherein the historical problem- solving information comprises a historical user error cause, a historical error cause type, and a historical error cause analysis result corresponding to one or more users' answer content for one or more target questions in one or more subjects (see page 24 second paragraph); and
inputting the historical user error cause, the historical error cause type, and the historical error cause analysis result into a large language model, training the large language model in a supervised manner until an output result of the large language model meets a preset result for the historical user error cause, the historical error cause type, and the historical error cause analysis result, and taking the trained large language model as the error cause analysis model (see page 24 paragraph 5).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Liu reference with the feature of before the acquiring at least one current user error cause generated by an error cause analysis model based on the at least one of the problem-solving idea or the problem-solving step, further comprising: acquiring historical problem-solving information, wherein the historical problem- solving information comprises a historical user error cause, a historical error cause type, and a historical error cause analysis result corresponding to one or more users' answer content for one or more target questions in one or more subjects; and inputting the historical user error cause, the historical error cause type, and the historical error cause analysis result into a large language model, training the large language model in a supervised manner until an output result of the large language model meets a preset result for the historical user error cause, the historical error cause type, and the historical error cause analysis result, and taking the trained large language model as the error cause analysis model, as taught by the Hunter reference, in order to provides a better feedback that assesses the writer ‘s skill (see page 1 paragraph 4).
Claim 11: The Liu reference is silent on the teaching of determining associated questions respectively related to the at least one candidate error cause knowledge point, the first error cause knowledge point, the second error cause knowledge point and the third error cause knowledge point corresponding to the current user error cause; and pushing the associated questions.
However, the Hunter reference provides a teaching of determining associated questions respectively related to the at least one candidate error cause knowledge point, the first error cause knowledge point (see page 26 paragraph 8), the second error cause knowledge point and the third error cause knowledge point corresponding to the current user error cause (see page 26 paragraph 9); and pushing the associated questions (see 27 paragraph 2-3).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Liu reference with the feature of determining associated questions respectively related to the at least one candidate error cause knowledge point, the first error cause knowledge point, the second error cause knowledge point and the third error cause knowledge point corresponding to the current user error cause; and pushing the associated questions, as taught by the Hunter reference, in order to provides a better feedback that assesses the writer ‘s skill (see page 1 paragraph 4).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al in view of Hunter WO 2018/226106 and further in view of Shujie EP 4625368 A1
Claim 7: The Liu reference is silent on thea provides a teaching of after the determining an error cause analysis result of the draft paper file according to the current user error cause, and displaying the error cause analysis result on an answer page of the target question, further comprising:
displaying the second error cause knowledge point and the third error cause knowledge point on a bottom area of an answer area, wherein the answer page comprises the answer area; and
in response to a user's click operation on any error cause knowledge point among the second error cause knowledge point or the third error cause knowledge point in the bottom area, displaying knowledge analysis content corresponding to a clicked error cause knowledge point on the answer page wherein the knowledge analysis content comprises one or more of video content or graphic content.
However, the Shujie reference provides a teaching of displaying the second error cause knowledge point and the third error cause knowledge point on a bottom area of an answer area, wherein the answer page comprises the answer area (page 27 first complete paragraph); and
in response to a user's click operation on any error cause knowledge point among the second error cause knowledge point or the third error cause knowledge point in the bottom area, displaying knowledge analysis content corresponding to a clicked error cause knowledge point on the answer page wherein the knowledge analysis content comprises one or more of video content or graphic content (see page 28 paragraph 3).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Liu reference with the feature of displaying the second error cause knowledge point and the third error cause knowledge point on a bottom area of an answer area, wherein the answer page comprises the answer area; and in response to a user's click operation on any error cause knowledge point among the second error cause knowledge point or the third error cause knowledge point in the bottom area, displaying knowledge analysis content corresponding to a clicked error cause knowledge point on the answer page wherein the knowledge analysis content comprises one or more of video content or graphic content, as taught by the Shujie reference, in order to allow the user with multiple answers method (see paragraph 3 first paragraph).
Conclusion
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/ROBERT J UTAMA/Primary Examiner, Art Unit 3715
1 Liu et al. “ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing” Jun 2023. https://doi.org/10.48550/arXiv.2306.00622