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 .
Status of Claims
This action is responsive to Applicant’s claims filed 09/19/2024.
Claims 1-24 are currently pending and have been examined here.
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 1-24 are rejected under 35 U.S.C. § 101. The claims are drawn to ineligible patent subject matter, because the claims are directed to a recited judicial exception to patentability (an abstract idea), without claiming something significantly more than the judicial exception itself.
Claims are ineligible for patent protection if they are drawn to subject matter which is not within one of the four statutory categories, or, if the subject matter claimed does fall into one of the four statutory categories, the claims are ineligible if they recite a judicial exception, are directed to that judicial exception, and do not recite additional elements which amount to significantly more than the judicial exception itself. Alice Corp. v. CLS Bank Int'l, 375 U.S. ___ (2014). Accordingly, claims are first analyzed to determine whether they fall into one of the four statutory categories of patent eligible subject matter. Then, if the claims fall within one of the four statutory categories, it must be determined whether the claims are directed to a judicial exception to patentability (i.e., a law of nature, a natural phenomenon, or an abstract idea). In determining whether a claim is directed to a judicial exception, the claim is first analyzed to determine whether the claim recites a judicial exception. If the claim does not recite one of these exceptions, the claim is directed to patent eligible subject matter under 35 U.S.C. 101. If the claim recites one of these exceptions, the claim is then analyzed to determine whether the claim recites additional elements that integrate the exception into a practical application of that exception. Claims which integrate the exception into a practical application of that exception are directed to patent eligible subject matter under 35 U.S.C. 101. If the claim fails to integrate the exception into a practical application of that exception, the claim is directed to an abstract idea. Finally, if the claims are directed to a judicial exception to patentability, the claims are then analyzed determine whether the claims are directed to patent eligible subject matter by reciting meaningful limitations which transform the judicial exception into something significantly more than the judicial exception itself. If they do not, the claims are not directed towards eligible subject matter under 35 U.S.C. § 101.
Regarding independent claims 1 and 13 the claims are directed to one of the four statutory categories (a machine, a process, and an article of manufacture, respectively.) The claimed invention of independent claims 1 and 13 is directed to a judicial exception to patentability, an abstract idea. The claims include limitations which recite elements which can be properly characterized under at least one of the following groupings of subject matter recognized as abstract ideas by MPEP 2106.04(a):
Mathematical Concepts: mathematical relationships, mathematical formulas or equations, and mathematical calculations;
Certain methods of organizing human activity: fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes: concepts performed in the human mind (including an observation, evaluation, judgment, opinion)
Claims 1 and 13, as a whole, recite the following limitations:
receiving. . . a plurality of pieces of content; (claims 1, 13; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could receive this information; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers)
recognizing. . . if a candidate for a job title is present in each piece of content to generate a set of recognized job title candidates; (claims 1, 13; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could recognize whether a candidate for a job title is present in content; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers)
classifying. . . a job title for each of the set of recognized job title candidates to generate at least one job title; (claims 1, 13; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could classify a job title to generate a job title; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers)
extracting. . . one or more candidate skills from the plurality of pieces of content; (claims 1, 13; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could extract skills from content; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers)
classifying. . . a skill from the one or more candidate skills; (claims 1, 13; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could classify skills; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers)
assigning. . . an occupation to the at least one job title and the skill; (claims 1, 13; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could assign an occupation to a job title; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers)
and generating. . . a job ontology including the job title, the skill, and the assigned occupation. (claims 1, 13; the broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could generate a job ontology in this manner; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers)
The above elements, as a whole, recite mental processes since, but for the requirement to implement these steps in the field of use of machine learning and using a set of generic computer components, the entirety of the above steps could be performed by a human using their mind, pen and paper, and simple observation, evaluation, and judgment. Furthermore, the above elements, as a whole, recite certain methods of organizing human activity in the form of business relations and marketing or sales activities since the steps outlined above for generating a job ontology would be performed by job search and job matching companies performing services for their customers and by those looking to match prospective employees with employers.
Moving forward, the above recited abstract idea is not integrated into a practical application.
The added limitations do not represent an integration of the abstract idea into a practical application because:
the claims represent mere instructions to implement an abstract idea on a computer, and merely use a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
the claims merely add insignificant extra-solution activity to the judicial exception (activity which can be characterized as incidental to the primary purpose or product that is merely a nominal or tangential addition to the claim). See MPEP 2106.05(g) and/or
the claims represent mere general linking of the use of the judicial exception to a particular technological environment or field of use. See MPEP 2016.05(h)
Beyond those limitations which recite the abstract idea, the following limitations are added:
. . . at a computer system. . (claims 1, 13; the broadest reasonable interpretation of this limitation represents mere instructions to implement the abstract idea on a generic computer used as a tool in its ordinary capacity; alternatively, the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to a particular computer environment or field of use)
. . . by a job title machine learning recognizer of the computer system. . . (claims 1, 13; the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of machine learning; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using machine learning since the claims merely invoke machine learning as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of machine learning without indicating how the solution is actually achieved)
. . . by a machine learning skill extractor of the computer system. . . (claims 1, 13; the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of machine learning; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using machine learning since the claims merely invoke machine learning as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of machine learning without indicating how the solution is actually achieved)
. . . by a machine learning skills classifier of the computer system. . . (claims 1, 13; the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of machine learning; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using machine learning since the claims merely invoke machine learning as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of machine learning without indicating how the solution is actually achieved)
A system, comprising: (claim 13; the broadest reasonable interpretation of this limitation represents mere instructions to implement the abstract idea on a generic computer used as a tool in its ordinary capacity; alternatively, the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to a particular computer environment or field of use)
a computer system having a processor and memory and a plurality of instructions that configure to processor to: (claim 13; the broadest reasonable interpretation of this limitation represents mere instructions to implement the abstract idea on a generic computer used as a tool in its ordinary capacity; alternatively, the broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to a particular computer environment or field of use)
The claims, as a whole, are directed to the abstract idea(s) which they recite. The claim limitations do not present improvements to another technological field, nor do they improve the functioning of a computer or another technology. Nor do the claim limitations apply the judicial exception with, or by use of a particular machine. The claims do not effect a transformation or reduction of a particular article to a different state or thing. See MPEP 2106.05(c). None of the hardware in the claims "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment' that is, implementation via computers” such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP 2106.05(e); Alice Corp. v. CLS Bank Int’l (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)). Therefore, because the claims recite a judicial exception (an abstract idea) and do not integrate the judicial exception into a practical application, the claims, as a whole, are directed to the judicial exception.
Turning to the final prong of the test (Step 2B), independent claims 1 and 13 do not include additional elements that are sufficient to amount to significantly more than the judicial exception, because there are no meaningful limitations which transform the exception into a patent eligible application.
As outlined above, the claim limitations do not present improvements to another technological field, nor do they improve the functioning of a computer or another technology. Nor do the claim limitations apply the judicial exception with, or by use of a particular machine. The claims do not effect a transformation or reduction of a particular article to a different state or thing. See MPEP 2106.05(c). None of the hardware in the claims "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment' that is, implementation via computers” such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP 2106.05(e); Alice Corp. v. CLS Bank Int’l (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
Furthermore, no specific limitations are added which represent something other than what is well-understood, routine, and conventional activity in the field. See MPEP 2106.05(d). Besides performing the abstract idea itself, the generic computer components only serve to perform the court-recognized well-understood computer functions of receiving or transmitting data over a network, performing repetitive calculations, electronic record keeping, and storing and retrieving information in memory. See MPEP 2106.05(d). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Their collective functions merely provide conventional computer implementation. The specification details any combination of a generic computer system program to perform the method. Generically recited computer elements do not add a meaningful limitation to the abstract idea because they would be routine in any computer implementation and because the Alice decision noted that generic structures that merely apply the abstract ideas are not significantly more than the abstract ideas. Therefore, independent claims 1 and 13 are rejected under 35 U.S.C. §101 as being directed to ineligible subject matter.
Claims 2-12 and 14-24, recite the same abstract idea as their respective independent claims.
The following additional features are added in the dependent claims:
Claims 2 and 14:
maintaining the job ontology by adding a new job title into the job ontology.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could maintain a job ontology by adding a new job title to it; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers.
Claims 3 and 15:
wherein adding the new job title into the job ontology further comprises classifying, using the job title machine learning classifier of the computer system, the new job title, comparing, the new job title with the plurality of job titles in the job ontology and updating the job ontology with the new job title when the new job title is not similar to one of the job titles already contained in the job ontology.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could classify a new job title, compare it to those in an ontology, and add it if it is not similar thereto; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers. Please see analysis above regarding the implementation of this step using a machine learning classifier.
Claims 4 and 16:
wherein recognizing if the job title candidate is present further comprises using a jobspanBERT model to generate the set of recognized job title candidates.
The broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of a jobspanBERT model; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using a jobspanBERT model since the claims merely invoke a jobspanBERT model as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of a jobspanBERT model without indicating how the solution is actually achieved
Claims 5 and 17:
wherein classifying the job title further comprises using a neural network that receives input from the jobspanBERT model.
The broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of a neural network and jobspanBERT model; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using a neural network and jobspanBERT model since the claims merely invoke a neural network and jobspanBERT model as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of a neural network and jobspanBERT model without indicating how the solution is actually achieved
Claims 6 and 18:
wherein extracting one or more candidate skills further comprises extracting the one or more candidate skills using a support vector machine classifier and a RoBERTa model.
The broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of an SVM and a RoBERTa model; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using an SVM and a RoBERTa model since the claims merely invoke an SVM and a RoBERTa model as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of an SVM and a RoBERTa model without indicating how the solution is actually achieved
Claims 7 and 19:
wherein classifying the skill further comprises classifying the skill using a fuzzy skill classifier.
The broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of a fuzzy skill classifier; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using a fuzzy skill classifier since the claims merely invoke a fuzzy skill classifier as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of a fuzzy skill classifier without indicating how the solution is actually achieved
Claims 8 and 20:
wherein classifying the skill further comprises scoring the skill to generate a skill score, determining a softness of the skill to generate a skill softness and determining a skill source tag.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could score a skill, determine a skill softness, and determine a skill source tag; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers.
Claims 9 and 21:
wherein classifying the skill further comprises generating a fuzzy skill dictionary to store, for each skill, the skill, the skill score, the skill softness, a skill type and a skill source tag.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could generate a fuzzy skill dictionary to store this information; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers. The broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of a fuzzy skill dictionary; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using a fuzzy skill dictionary since the claims merely invoke a fuzzy skill dictionary as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of a fuzzy skill dictionary without indicating how the solution is actually achieved
Claims 10 and 22:
further comprising assigning a job title to the skill using a k nearest neighbor process.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could assign a job title to a skill using k-nearest neighbors; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers. The broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of k-nearest neighbors; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using k-nearest neighbors since the claims merely invoke k-nearest neighbors as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of k-nearest neighbors without indicating how the solution is actually achieved
Claims 11 and 23:
wherein assigning the occupation to the job title and the skill further comprises using a k nearest neighbor process with semantic similarity.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could assign an occupation to a job title and skill using a k-nearest neighbor with semantic similarity; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers. The broadest reasonable interpretation of this limitation represents mere general linking of the abstract idea to the particular computer environment or field of use of k-nearest neighbors; furthermore, the broadest reasonable interpretation of this limitation merely amounts to the requirement to “apply” the abstract idea using k-nearest neighbors since the claims merely invoke k-nearest neighbors as a tool in its ordinary capacity to perform its functions, and, since the claim merely recites the idea of a solution or outcome of the use of k-nearest neighbors without indicating how the solution is actually achieved
Claims 12 and 24:
further comprising preprocessing the plurality of pieces of content into a set of chunks before recognizing if a job title is present.
The broadest reasonable interpretation of this limitation recites mental processes since a human using their mind, pen and paper, and simple observation, evaluation, and judgment could preprocess information into chunks in this manner; alternatively, the broadest reasonable interpretation of this limitation recites certain methods of organizing human activity in the form of commercial interactions such as business relations and sales activities since commercial job search and job matching companies would perform this step in performing services for their customers and this step would further be performed by those looking to match prospective employees with employers.
The above limitations do not represent a practical application of the recited abstract idea. The claim limitations do not present improvements to another technological field, nor do they improve the functioning of a computer or another technology. Nor do the claim limitations apply the judicial exception with, or by use of a particular machine. The claims do not effect a transformation or reduction of a particular article to a different state or thing. See MPEP 2106.05(c). None of the hardware in the claims "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment' that is, implementation via computers” such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See MPEP 2106.05(e); Alice Corp. v. CLS Bank Int’l (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)). Therefore, because the claims recite a judicial exception (an abstract idea) and do not integrate the judicial exception into a practical application, the claims are also directed to the judicial exception.
Furthermore, the added limitations do not direct the claim to significantly more than the abstract idea. No specific limitations are added which represent something other than what is well-understood, routine, and conventional activity in the field. See MPEP 2106.05(d). Accordingly, none of the dependent claims 2-12 and 14-24, individually, or as an ordered combination, are directed to patent eligible subject matter under 35 U.S.C. 101.
Please see MPEP §2106.05(d)(II) for a discussion of elements that the Courts have recognized as well-understood, routine, conventional, activity in particular fields.
Please see MPEP §2106 for examination guidelines regarding patent subject matter eligibility.
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, 10-13, and 22-24 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Yerastov et al. (U.S. PG Pub. No. 20230004941; hereinafter "Yerastov").
As per claim 1, Yerastov teaches:
A method, comprising:
Yerastov teaches a system and method for automatically generating job descriptions (job ontologies). (Yerastov: abstract)
receiving, at a computer system, a plurality of pieces of content;
Yerastov teaches a set of job description documents in a job description dataset which may be received by the system. (Yerastov: paragraph [0033-34])
recognizing, by a job title machine learning recognizer of the computer system, if a candidate for a job title is present in each piece of content to generate a set of recognized job title candidates;
Yerastov teaches that job description sections may be analyzed using a machine learning algorithm, wherein section may be identified (a candidate for a job tile) and a job title section may be recognized in each document, wherein the job title may be classified if it is recognized. (Yerastov: paragraph [0046-48, 42-43, 55-57])
classifying, by a job title machine learning classifier of the computer system, a job title for each of the set of recognized job title candidates to generate at least one job title;
Yerastov teaches that job description sections may be analyzed using a machine learning algorithm, wherein section may be identified (a candidate for a job tile) and a job title section may be recognized in each document, wherein the job title may be classified if it is recognized. (Yerastov: paragraph [0034, 46-48, 42-43, 55-57, 130-131])
extracting, by a machine learning skill extractor of the computer system, one or more candidate skills from the plurality of pieces of content;
Yerastov teaches that a machine learning model may be used to extract selected phrases corresponding to skills which are to be included in the job description. (Yerastov: paragraph [0107])
classifying, by a machine learning skills classifier of the computer system, a skill from the one or more candidate skills;
Yerastov further teaches that a machine learning model in the form of a fuzzy classifier may be used to identify and classify phrases which correspond to skills within the documents. (Yerastov: paragraph [0078, 80, 87, 101])
assigning, by the computer system, an occupation to the at least one job title and the skill;
Yerastov teaches that a job category comprising an occupation (here, nursing) may be assigned to the job title and the skills generated. (Yerastov: paragraph [0129-130])
and generating, by the computer system, a job ontology including the job title, the skill, and the assigned occupation.
Yerastov teaches that a job description may be generated which includes the job title, the job category, the responsibilities, and the skills of the job. (Yerastov: paragraphs [0127-133])
As per claim 10, Yerastov teaches all of the limitations of claim 1, as outlined above, and further teaches:
further comprising assigning a job title to the skill using a k nearest neighbor process.
Yerastov further teaches that a K-nearest neighbor approach may be used to determine which job titles correspond with which skills and assigning the skill to the job title based on semantic similarities between skills and job titles. (Yerastov: paragraph [0105, 111, 117-120, 131-132])
As per claim 11, Yerastov teaches all of the limitations of claim 10, as outlined above, and further teaches:
wherein assigning the occupation to the job title and the skill further comprises using a k nearest neighbor process with semantic similarity.
Yerastov further teaches that a K-nearest neighbor approach may be used to determine which job titles correspond with which skills and assigning the skill to the job title based on semantic similarities between skills and job titles. (Yerastov: paragraph [0105, 111, 117-120, 131-132])
As per claim 12, Yerastov teaches all of the limitations of claim 1, as outlined above, and further teaches:
further comprising preprocessing the plurality of pieces of content into a set of chunks before recognizing if a job title is present.
Yerastov further teaches that the sections of documents may be processed into chunks before determining whether a job title is present. (Yerastov: paragraph [0052])
As per claim 13, Yerastov teaches the limitations of this claim which are substantially identical to those of claim 1, as outlined above, and further teaches:
A system, comprising:
Yerastov teaches a system and method for automatically generating job descriptions (job ontologies). (Yerastov: abstract)
a computer system having a processor and memory and a plurality of instructions that configure to processor to:
Yerastov teaches the implementation of the system and method using a computer with a processor which executes code stored in a physical memory in order to perform the functions of the system. (Yerastov: paragraph [0135-142], Fig. 7)
As per claims 22-24, Yerastov teaches the limitations of these claims which are substantially identical to those of claims 10-12, and claims 22-24 are rejected for the same reasons as claims 10-12, as outlined above.
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.
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.
Claims 2-3 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Yerastov in view of Vontobel et al. (U.S. PG Pub. No. 20220327487; hereinafter "Vontobel").
As per claim 2, Yerastov teaches all of the limitations of claim 1, as outlined above, but does not appear to explicitly teach:
maintaining the job ontology by adding a new job title into the job ontology.
Vontobel, however, teaches that, upon receiving a job title, the system may make a check as to whether there exists an ontology for this job title by matching it to known titles with known ontologies, and, if not is found, the system may enter the new title into the database by assigning it to a job code which is most similar. (Vontobel: paragraph [0060, 72, 111-112]) Vontobel teaches combining the above elements with the teachings of Yerastov for the benefit of providing a way to combine multiple datasets of job titles and skills and related features, to use machine learning techniques to enrich the combined data, and to merge these items into a single ontology, combining an ontology with automatically assessed, as well as manually reported, skills, experiences, and job titles into user profiles, and providing a system which automatically matches the skills and aspirations of users with the ones automatically and/or manually detected in new job listings and projects. (Vontobel: paragraph [0048]) Therefore, before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Vontobel with the teachings of Yerastov to achieve the aforementioned benefits.
As per claim 3, Yerastov in view of Vontobel teaches all of the limitations of claim 2, as outlined above, and further teaches:
wherein adding the new job title into the job ontology further comprises classifying, using the job title machine learning classifier of the computer system, the new job title, comparing, the new job title with the plurality of job titles in the job ontology and updating the job ontology with the new job title when the new job title is not similar to one of the job titles already contained in the job ontology.
Vontobel, as outlined above, teaches that, upon receiving a job title, the system may make a check as to whether there exists an ontology for this job title by matching it to known titles with known ontologies, and, if not is found, the system may enter the new title into the database by assigning it to a job code which is most similar. (Vontobel: paragraph [0060, 72, 111-112]) The motivation to combine Vontobel persists.
As per claims 14-15, Yerastov in view of Vontobel teaches the limitations of these claims which are substantially identical to those of claims 2-3, and claims 14-15 are rejected for the same reasons as claims 2-3, as outlined above.
Claims 4-5 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Yerastov in view of Decorte, Jens-Joris, et al. ("Jobbert: Understanding job titles through skills." arXiv preprint arXiv:2109.09605 (2021); hereinafter "Decorte")
As per claim 4, Yerastov teaches all of the limitations of claim 1, as outlined above, but does not appear to explicitly teach:
wherein recognizing if the job title candidate is present further comprises using a jobspanBERT model to generate the set of recognized job title candidates.
Decorte, however, teaches the use of a JobBert model to generate a set of job title candidates based on semantic similarities. (Decorte: "2. Job Title Representation Learning") Decorte teaches combining the above elements with the teachings of Yerastov for the benefit of not needing extensive sets of job titles that are labeled in a model, not needed a continuous data labeling effort, and not confining systems to static information. (Decorte: page 2, bullet points (a)-(c)) Therefore, before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Decorte with the teachings of Yerastov to achieve the aforementioned benefits.
As per claim 5, Yerastov in view of Decorte teaches all of the limitations of claim 2, as outlined above, and further teaches:
wherein classifying the job title further comprises using a neural network that receives input from the jobspanBERT model.
Decorte further teaches the use of a JobBert model to generate a set of job title candidates based on semantic similarities, wherein the output of the BERT model is input into a multilayer perceptron model, a neural network. (Decorte: "2. Job Title Representation Learning") The motivation to combine Decorte persists.
As per claims 16-17, Yerastov in view of Decorte teaches the limitations of these claims which are substantially identical to those of claims 4-5, and claims 16-17are rejected for the same reasons as claims 4-5, as outlined above.
Novelty/Non-obviousness
Regarding the novelty/non-obviousness of claims 6 and 18, and their dependents, the prior art does not appear to teach, in the context of the systems and methods for generating job ontologies, and in ordered combination with the recited elements of the claims, that a RoBERTa model and a support vector machine classifier may be used to extract one or more candidate skills in the extracting skills step of the independent claims.
Conclusion
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/EMMETT K. WALSH/Primary Examiner, Art Unit 3628