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 .
This Office Action is in response to correspondence filed 14 April 2024 in reference to application 18/701,416. Claims 1-13 and 20-25 are pending and have been examined.
Response to Amendment
The preliminary amendment filed 14 April 2024 has been accepted and considered in this office action. Claims 1-13, 20-25 have been amended, and claims 14-19 cancelled.
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.
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: “a first obtaining device,” “a second obtaining device,” and “a determining device,” in claim 20, “a quantum circuit determining device” and “a predicting unit” in claim 21, “a processing unit” and “a predicting unit” in claim 22.
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 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 12 is 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 12 recites an equation
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which includes an exponent “T” which is not defined in a manner that one could understand the meaning of the equation, or how exactly the cost is actually calculated. Therefore claim 12 is indefinite.
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)(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.
Claim(s) 1, 2, 7, 9-13, and 20-25 is/are rejected under 35 U.S.C. 102(a))(1) as being anticipated by Meichanetzidis et al. (Grammer-Aware Question-Answering on Quantum Computers).
Consider claim 1, Meichanetzidis teaches A quantum circuit determining method for a text (abstract), comprising:
obtaining at least parts of speech of words in a text corpus (page 2, end of column 1, parser tags words with parts of speech);
obtaining relevancies between the words according to semanteme of the text corpus (figure 1, page 2, column 2- page 3 column 1, determining grammatical relationships between words in sentences, graphical diagrams); and
determining qubits and parameter-containing quantum logic gates of quantum circuits according to the parts of speech and the relevancies (page 3 column 1 – page 4, column 1, assigned qubits to words and us building PQCs using entangled gates to represent parameters, see figures 2 and 3 as well.).
Consider claim 2, Meichanetzidis teaches the method of claim 1, wherein said obtaining relevancies between the words according to semanteme of the text corpus comprises:
obtaining a first relevance characterizing a dominant feature of the text corpus according to the semanteme of the text corpus (see figure 1, dominant relationship: who linked to dies. This example is similar to those given in the instant spec at 0080-84); and
obtaining a second relevance characterizing a recessive feature of the text corpus according to the semanteme of the text corpus (see figure 1, recessive relationship: who linked to loves. This example is similar to those given in the instant spec at 0080-84).
Consider claim 7, Meichanetzidis teaches the method of claim 1, wherein before said determining qubits and parameter-containing quantum logic gates of quantum circuits according to the parts of speech and the relevancies the method further comprises:
graphically representing the text corpus according to the parts of speech of the words in the text corpus and the relevancies between the words (Figure 1, page 2, column 2- page 3 column 1, determining grammatical relationships between words in sentences, graphical diagrams).
Consider claim 9, Meichanetzidis teaches a text classifying method based on quantum circuits, wherein the method comprises:
constructing, according to the method of claim 1, quantum circuits for a text to be classified (see pages 2-4, determining PoS, relationships, and quantum circuits);
determining initialized parameter values of parameter-containing quantum logic gates in the quantum circuits according to meanings of the words in a text corpus (page 4, question answer section, training to determine parameter values, see column 2 into page 5 column 1 especially);
running the quantum circuits and obtaining a running result thereof (page 5, classical simulation section, running the circuits); and
obtaining a predictive classification result of the text corpus according to the running result (page 5 classical simulation section, predicting labels).
Consider claim 10, Meichanetzidis teaches The text classifying method of claim 9, wherein before said determining initialized parameter values of parameter-containing quantum logic gates according to meanings of the words in a text corpus, the method further comprises:
training the quantum circuits to obtain parameter values corresponding to meanings of the words and for determining the initialized parameter values (page 4, question answer section, training to determine parameter values, see column 2 into page 5 column 1 especially).
Consider claim 11, Meichanetzidis teaches The text classifying method of claim 10, wherein said training the quantum circuits to obtain parameter values corresponding to meanings of the words and for determining the initialized parameter values comprises:
determining initialized parameter values of parameter-containing quantum logic gates to be trained according to the meanings of the words in the text corpus, running the parameter-containing quantum logic gates to be trained and obtaining a running result thereof (page 4, column 2 to page 5 column 1, training, which includes setting initial values and running the circuits to obtain predictions);
obtaining the predictive classification result of the text corpus according to the running result ((page 4, column 2 to page 5 column 1, training, which includes setting initial values and running the circuits to obtain predictions));
correcting the initialized parameter values according to the predictive classification result to obtain updated parameter values, and then re-executing the running the quantum circuits and obtaining a running result thereof and obtaining the predictive classification result of the text corpus according to the running result until the predictive classification result is close to a true result (page 4, column 2 to page 5 column 1, adjusting parameters to minimize cost functions and re-running the circuits); and
obtaining the updated parameter value when the predictive classification result is close to the true result, for determining parameter values of the initialized parameter values (page 5 column 1, minimize error via a cost function. To minimize error e.).
Consider claim 12, Meichanetzidis teaches the text classifying method of claim 11, wherein said obtaining the predictive classification result of the text corpus according to the running result comprises:
obtaining a cost function corresponding to a real label according to the running result, and obtaining the predictive classification result of the text corpus according to the cost function is defined as follows:
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wherein, LO(P) characterizes the running result, L (P) characterizes the real label, and C (O) characterizes the cost function (appendix F, cost function may be cross entropy loss, which is known to be defined as
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, even as the specific example discussed in Meichanetzidis is a binary cross entropy. ).
Consider claim 13, Meichanetzidis teaches the text classifying method of claim 11, wherein said correcting the initialized parameter values according to the predictive classification result to obtain updated parameter values comprises:
correcting the initialized parameter values according to the predictive classification result based on synchronous perturbation stochastic approximation algorithm to obtain the updated parameter value (Appendix F, using synchronous perturbation stochastic approximation for optimization ).
Consider claim 20, Meichanetzidis teaches a quantum circuit determining device for a text (abstract), characterized by comprising:
a first obtaining device configured for obtaining parts of speech of the words in a text corpus (page 2, end of column 1, parser tags words with parts of speech);
a second obtaining device configured for obtaining relevancies between the words according to semanteme of the text corpus (figure 1, page 2, column 2- page 3 column 1, determining grammatical relationships between words in sentences, graphical diagrams); and
a determining device configured for determining qubits and parameter-containing quantum logic gates of quantum circuits according to the parts of speech and the relevancies (page 3 column 1 – page 4, column 1, assigned qubits to words and us building PQCs using entangled gates to represent parameters, see figures 2 and 3 as well.).
Consider claim 21, Meichanetzidis teaches a text classifying device, characterized by comprising:
a quantum circuit determining device configured for constructing quantum circuits for a text to be classified according to the method of claim 1 (see pages 2-4, determining PoS, relationships, and quantum circuits); and
a predicting unit configured for: determining initialized parameter values of parameter-containing quantum logic gates in the quantum circuits according to meanings of the words in a text corpus (page 4, question answer section, training to determine parameter values, see column 2 into page 5 column 1 especially), running the quantum circuits and obtaining a running result thereof, and obtaining a predictive classification result of the text corpus according to the running result (page 5, classical simulation section, running the circuits and predicting labels).
Consider claim 22, Meichanetzidis teaches a text classifying device, comprising:
a processing unit configured for converting a text corpus into a target quantum circuit according to parts of speech, meanings and relevancies of the words in the text corpus (see pages 2-4, determining PoS, relationships, and quantum circuits);
wherein the relevancies comprise relevancies between each word and other words in the text corpus (see Figure 1 for example, relationships between words represented by wires);
the processing unit is further configured for obtaining a running result of the target quantum circuit, wherein the running result comprises an output result of a qubit when the target quantum circuit is run each time (page 5, classical simulation section, running the circuits and qubits); and
a predicting unit configured for obtaining a predictive classification result of the text corpus according to the running result (page 5, classical simulation section, running the circuits and predicting labels).
Consider claim 23, Meichanetzidis teaches The text classifying device of claim 22, wherein the processing unit is further configured for:
determining a sentence syntax type corresponding to the text corpus according to the parts of speech and the relevancies of the words in the text corpus (page 2, end of column 1, parser tags words with parts of speech, generating grammatical reduction in column 2);
determining a target quantum framework according to the sentence syntax type, wherein the target quantum framework is a quantum framework corresponding to the sentence syntax type (figure 2 and 3, page 2 column 2 – page 3 col 2, building quantum circuits according to grammatical reductions);
determining an initial parameter of a logic gate in the target quantum framework according to meanings of the words in the text corpus (page 4, question answer section, training to determine parameter values, see column 2 into page 5 column 1 especially, also see Appendix E andF); and
setting a parameter of the logic gate in the target quantum framework according to the initial parameter, to complete a conversion of the target quantum circuit (page 4, question answer section, training to determine parameter values, see column 2 into page 5 column 1 especially, also see Appendix E and F).
Consider claim 24, Meichanetzidis teaches A computer-readable storage medium having a computer program stored therein, wherein the computer program is configured for implementing, when executed by a processor, the method of claim 1 (Page 5, column 2 using IBMQ quantum computers, which would include storage mediums, processors, and programs).
Consider claim 25, Meichanetzidis teaches An electronic device, characterized by comprising a processor and a memory, the memory is configured for storing one or more programs which implement, when executed by the processor, the method of claim 1 (Page 5, column 2 using IBMQ quantum computers, which would include storage mediums, processors, and programs).
Allowable Subject Matter
Claims 3-6, 8 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Consider claim 3, Meichanetzidis teaches the method of claim 1, but does not specifically teach wherein said determining qubits and parameter-containing quantum logic gates of quantum circuits according to the parts of speech and the relevancies comprises:
determining partial-qubits and the parameter-containing quantum logic gates that represent words with each part of speech;
processing the partial-qubits according to the first relevance to obtain entire qubits characterizing a structure of the text corpus, as the qubits of the quantum circuits; and
determining quantum logic gates characterizing the recessive feature of the text corpus according to the second relevance.
While Meichanetzidis teaches processing qubits to build quantum circuits to encode relevancies (see pages 3-4 and Appendix E), they do not suggest processing using partial qubits to encode parts of speech when combined with each and every other limitation of the claim and base claim. Therefore claim 3 contains allowable subject matter.
Claims 4-6 depend on and further limit claim 3 and therefore contain allowable subject matter as well.
Consider claim 8, Meichanetzidis teaches The method of claim 7, wherein said representing the text corpus graphically according to the parts of speech of the all words in the text corpus and the relevancies between the words comprises:
determining a structural initial graph of the text corpus according to the parts of speech of the words in the text corpus and the relevancies between the all words, wherein the words with different parts of speech in the structural initial graph are placed horizontally, and the relevancies between the words are represented by a U-shaped broken line (Figure 1, page 2, column 2- page 3 column 1, U shaped lines representing relevancies, broken off at each word).
However the prior art of record does not teach or fairly suggest the limitations of “simplifying the structural initial graph to obtain a structural sketch, wherein the all words with different parts of speech in the structural sketch are placed in a staggered manner, and the relevancies between the words are represented by a U-shaped broken line or a straight line.” Rather Meichanetzidis does not specifically simplify the diagrams before converting them to circuits, when combined with each and every other limitation of the claim, intervening claim, and base claim. Therefore claim 8 contains allowable subject matter.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Zeng et al. (Quantum Algorithms for Compositional Natural Language Processing) introduces the concepts of representing natural language sentences with quantum circuits.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DOUGLAS C GODBOLD whose telephone number is (571)270-1451. The examiner can normally be reached 6:30am-5pm Monday-Thursday.
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DOUGLAS GODBOLD
Examiner
Art Unit 2655
/DOUGLAS GODBOLD/Primary Examiner, Art Unit 2655