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 .
Claims 1-4, and 6-9 are presented for examination.
Allowable Subject Matter
Claims 4 and 9 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
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: “text data extracting means”, “component extracting means”, “semantic content searching means”, “code extracting means”, “inferring means” and “means that generates an executable program code” in claim 1, “updating means” in claim 4.
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 § 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.
Claim(s) 1, and 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 7765097 B1) in view of Antunes (US 20190102390 A1) further in view of Mai (US 20200218722 A1).
Regarding Claim 1, Yu (US 7765097 B1) teaches
An automatic program code generation device comprising:
text data extracting means that extracts text data as a sentence or sentences (Col 3: ln 48-61, A document converter (102) corresponds to a component that includes functionality to extract instructions from the document) Examiner Comments: The instructions from the document is interpreted to the claimed “sentence or sentences;
semantic content inferring means that refers to [a first trained model] in which the extracted individual components of the sentence or sentences and a semantic content thereof are associated with each other (Col 5: ln 22-28, the pattern matcher (110) is connected to a concept map (112) in accordance with one or more embodiments of the invention. A concept map (112) is a semantic model. Specifically, the concept map (112) shows the semantic relationships between concepts. In one or more embodiments of the invention, a concept map (112) describes at least two types of relationships; Col 4: ln13-24, The root has children of a node representing a noun phrase and a node representing a verb phase),
and infers a semantic content highly relevant to the component extracted by the component extracting means (Col 5: ln 10-20, the pattern matcher (110) uses the words in the manifest associated with a concept to determine whether the concept is a potential match. For example, a concept corresponding to the mathematical operator "add" may have a manifest that identifies the words of "sum", "combine", "add", etc. that are potential matches for the concept "add.");
and code extracting means that refers to [a second trained model] in which the inferred semantic content and program code basic syntax are associated with each other, and extracts highly relevant program code basic syntax based on the semantic content inferred by the semantic content inferring means (Col 5: ln 64 – Col 6: ln 4, the mapping rules repository (116) correlate instances in the instantiated concept map with the code that should be outputted based on the instances. For example, the mapping rules repository (116) may include for an "add" function, the entry "for each parameter, output the parameter's identifier (e.g., field_1) and insert a "+" symbol between all parameters).
Yu did not specifically teach
component extracting means that extracts individual components of the sentence or sentences including a verb, a noun, and a case marker by a morphological analysis on the extracted text data;
and means that: generates an executable program code by assigning to the extracted program code basic (i) a noun or a noun phrase extracted, or (ii) a data item or data related to individual components of the sentence or sentences extracted by the component extracting means, and executes the generated program code,
a first trained model
a second trained model.
However, Antunes (US 20190102390 A1) teaches
component extracting means that extracts individual components of the sentence or sentences including a verb, a noun, and a case marker by a morphological analysis on the extracted text data (Para 0060, In one embodiment, tokenization of a query comprises splitting a string of characters into a set of pieces referred to as tokens. In one embodiment, the method in step 301 splits a string of characters based on white space or punctuation; Para 0062, In one embodiment, the stemming operation condenses a token into its root word; Para 0064, the method tags each token according to a part of speech in English, or in a local language (e.g., Portuguese). Thus, the method may assign labels of, for example, “noun,” “verb,” “adjective, “adverb,” etc., to each token … the method may utilize hidden Markov models or other machine-learning based POS tagging methods; Para 0072, the method removes all tokens corresponding to stop words. In a first embodiment, the method may utilize a dictionary of stop words (e.g., “a”, “an”, “the”, “on”, etc.). Alternatively, or in conjunction with the foregoing, the method may allow for user-defined stop words) Examiner Comments: The stop words serve as case makers in English. The stemming and POS tagging perform morphological analysis to extract verbs, nouns, and stop words as casemakers from the text;
and means that: generates an executable program code by assigning to the extracted program code basic (i) a noun or a noun phrase extracted, or (ii) a data item or data related to individual components of the sentence or sentences extracted by the component extracting means (Para 0046, a database statement may generated of the form “SELECT product_name, quantity FROM sales WHERE sale_date IS 2017 GROUP BY month.” Notably, the database statement is illustrated as a pseudocode statement and may differ depending on the type of database used, the type of database being of any relational database) Examiner Comments: The generated SQL is executable program code created by assigning extracted nouns like “product_name” and data items like “2017” to the basic SQL syntax clauses,
and executes the generated program code (Para 0007, executing a search on the data source using the structured query, the execution of the search resulting a result set).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined Yu’s teaching to Antunes in order to enable providing robust natural language processing of search queries or providing robust mapping of natural language queries to structured search instructions to reduce complexity and improve performance in the data visualizations, providing access to remote data sources and providing adequate visualization of search results based on identified data (Antunes [Summary]).
Yu and Antunes did not specifically teach
a first trained model
a second trained model.
However, Mai (US 20200218722 A1) teaches
a first trained model (abstract, converting the query into a second sequence of words by using a first machine learning mode)
a second trained model (abstract, obtaining a result for the query by applying a second machine learning model to a combination of the first sequence of words and the second sequence of words).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined Yu and Antunes’ to Mai’s in order to improve a search result for a query by only using bigrams sampled from sentences and training to select the best bigram from sentences without the ground truth bigram using weak supervision and reinforcement learning, by receiving a query where the query has a first sequence of words, the query converts into a second sequence of words by using a first machine learning model
Regarding Claim 6, is a non-transitory computer-readable medium claim corresponding to the device claim above (Claim 1) and, therefore, is rejected for the same reasons set forth in the rejection of Claim 1.
Claim(s) 2 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 7765097 B1) in view of Antunes (US 20190102390 A1) and Mai (US 20200218722 A1) further in view of Wroczynski (US 20160062982 A1).
Regarding Claim 2, Yu, Antunes and Mai teach
The automatic program code generation device according to claim 1, wherein the semantic content inferring means refers to the first trained model in which the extracted individual components of the sentence or sentences and the semantic content thereof are associated with each other with [an association degree of three or more levels], and the code extracting means refers to the second trained model in which the inferred semantic content and the program code basic syntax are associated with each other with [an association degree of three or more levels] (Yu [Col 5: ln 29-37, The first type of relationship is an inheritance hierarchy in which a child (or multiple children) is derived from at least one parent. Specifically, a child in the hierarchy is a type of the parent. For example, the word "add" is a type of math function. In one or more embodiments of the invention, the derived relationship is not necessarily a one-to-one or one-to-many relationship; Col 5: ln 38-44, The second type of relationship within a concept map is a containment relationship. Specifically, a parent is connected to a child if the parent requires the child as a parameter]).
Yu, Antunes and Mai did not specifically teach
an association degree of three or more levels.
However, Wroczynski (US 20160062982 A1) teaches
an association degree of three or more levels (Abstract, Embodiments also include a language decoder (LD) that generates information which is stored in a three-level framework (word, clause, phrase)).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined Yu, Antunes and Mai’s teaching to Wroczynski’s in order to provide a highly accessible platform for natural language processing by executing a word tagger module that receives tokenized words and assigns tags to the tokenized words using a reference dictionary of words with possible tags, and edits the responsible rule and executes the word tagger module using the edited rule (Wroczynski [Summary]).
Regarding Claim 7, is a non-transitory computer-readable medium claim corresponding to the device claim above (Claim 2) and, therefore, is rejected for the same reasons set forth in the rejection of Claim 2.
Claim(s) 3 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 7765097 B1) in view of Yoon (US 20200026488 A1) and Mai (US 20200218722 A1) further in view of Wroczynski (US 20160062982 A1) and Bird (US 12159211 B2).
Regarding Claim 3, Yu, Antunes, Mai and Wroczynski teach
The automatic program code generation device according to claim 2.
Yu, Antunes, Mai and Wroczynski did not teach
wherein the semantic content inferring means and the code extracting means use the association degree corresponding to weighting factors of respective outputs of nodes in a neural network of artificial intelligence.
However, Bird (US 12159211 B2) teaches
wherein the semantic content inferring means and the code extracting means use the association degree corresponding to weighting factors of respective outputs of nodes in a neural network of artificial intelligence (Col 7: ln 32-46, The ordered sequences of tokens include masked tokens which are used to train the model to predict the entire content from the context in which they appear. In this manner, the weights of the model encode information about the syntax and semantics of each programming language learned from the training dataset. The pre-trained neural encoder transformer model 308 outputs a probability distribution for each of the tokens in the source code vocabulary 310).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have combined Yu, Antunes, Mai and Wroczynski’s teaching to Bird’s in order to provide suggestions to perform a merge rather indicates the existence of a merge conflict by merge command when a conflict is detected, and allows the user to resolve the conflict by combining the changes or selecting one of the changes (Bird [Summary]).
Regarding Claim 8, is a non-transitory computer-readable medium claim corresponding to the device claim above (Claim 3) and, therefore, is rejected for the same reasons set forth in the rejection of Claim 3.
Response to Arguments
Applicant’s arguments with respect to claims 1-4, and 6-9 have been considered but are moot because the arguments do not apply to the previous cited sections of the references used in the previous office action. The current office action is now citing additional references to address the newly added claimed limitations.
Conclusion
THIS ACTION IS MADE FINAL. 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 AMIR SOLTANZADEH whose telephone number is (571)272-3451. The examiner can normally be reached M-F, 9am - 5pm ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Wei Mui can be reached on (571) 272-3708. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AMIR SOLTANZADEH/Examiner, Art Unit 2191 /WEI Y MUI/Supervisory Patent Examiner, Art Unit 2191
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