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 Claim
This action is in reply in response to application filed on 14 of February 2025.
Claims 1-15 are currently pending and are rejected as described below.
Claim Rejections - 35 USC § 101
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 therefore, subject to the conditions and requirements of this title.
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machines, article of manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception.
The claims are then analyzed to determine whether the claims are directed to a judicial exception. MPEP §2106.04(a). In determining, whether the claims are directed to a judicial exception, the claims are analyzed to evaluate whether the claims recite a judicial exception (Prong One of Step 2A), and whether the claims recite additional elements that integrate the judicial exception into a practical application (Prong Two of Step 2A). See 2019 Revised Patent Subject Matter Eligibility Guidance (“PEG” 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50-57 (Jan. 7, 2019)).
With respect to 2A Prong 1, claim 11 recites “a user terminal; and an information processing device configured to: acquire an experience value of a user from the user terminal; determine a skill level of the user based on the experience value, wherein the skill level of the user is either skilled or unskilled; extract support candidates based on experience values of other users in response to determining that the skill level of the user is unskilled; and output information regarding the support candidates to the user terminal”. Claims 1 and 6 disclose similar limitations as Claim 11, and therefore recite an abstract idea.
More specifically, claims 1, 6, and 11 are directed to “Certain Methods of Organizing Human Activity” in particular “managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)”, and “Mental Processes” in particular “concepts performed in the human mind (including an observation, evaluation, judgment, opinion)” as discussed in MPEP §2106.04(a)(2), and in the 2019-01-08 Revised Patent Subject Matter Eligibility Guidance. Accordingly, the claims recite an abstract idea.
Dependent claims 2-5, 7-10, and 12-15 further recite abstract idea(s) contained within the independent claims, and do not contribute to significant more or enable practical application. Thus, the dependent claims are rejected under 101 based on the same rationale as the independent claims.
Under Prong Two of Step 2A of the Alice/Mayo test, the examiner acknowledges that Claims 1, 6, and 11 recite additional elements yet the additional elements do not integrate the abstract idea into a practical application. In order for the judicial exception to be “integrated into a practical application”, an additional element or a combination of additional elements in the claim “will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.” PEG, 84 Fed. Reg. 54 (Jan. 7, 2019). The courts have identified examples in which a judicial exception has not been integrated into a practical application when “an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.” PEG, 84 Fed. Reg. 55 (Jan. 7, 2019); MPEP § 2106.05(h). The claims are directed to an abstract idea.
In particular, claims 1, 6, and 11 recite additional elements boldened and underlined above. These are generic computer components recited as performing generic computer functions that are mere instructions to apply an exception, because it does no more than merely invoke computers or machinery as a tool to perform an existing process. Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
With respect to step 2B, claims 1, 6, and 11do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The claim recites the additional elements described above. These are generic computer components recited as performing generic computer functions that are mere instructions to apply an exception, because it does no more than merely invoke computers or machinery as a tool to perform an existing process, as evidenced by at least in Pages 3-4 “FIG. 1 is a block diagram illustrating a work support system 100 according to an embodiment. The work support system 100 includes a server 1, a user terminal 2, and a supporter terminal 3. The server 1, the user terminal 2, and the supporter terminal 3 are communicatively connected to each other via a network. For example, the network is configured with one or more networks among various networks such as the Internet, a mobile communication network, and a local area network (LAN). The one or more networks may include a wireless network or a wired network. The work support system 100 may also refer to a system including at least two apparatuses among the server 1, the user terminal 2, and the supporter terminal 3. The server 1 is a device that collects data and processes the collected data (e.g., a controller). The server 1 is communicatively connected to the user terminal 2 and the supporter terminal 3 via the network. The server 1 receives various data from the user terminal 2 and the supporter terminal 3, and outputs various data to the user terminal 2 and the supporter terminal 3. The server 1 is an example of an information processing device. An example of the configuration of the server 1 will be described later. The server 1 may be a server used in a cloud service. The user terminal 2 is an apparatus that can communicate with other electronic apparatuses. The user terminal 2 is an apparatus used by a drafter of a workflow (e.g., a personal computer (PC), a smartphone, a tablet terminal, or the like, but is not limited thereto). The user of the user terminal 2 uses a workflow service and an inquiry service via the user terminal 2. The user of the user terminal 2 may be read as a drafter, an applicant, a worker, or a person. The supporter terminal 3 is an apparatus that can communicate with other electronic apparatuses. The supporter terminal 3 is an apparatus used by a supporter. The supporter terminal 3 may be a user device (e.g., a PC, a smartphone, a tablet terminal, or the like). The user of the supporter terminal 3 may include a supporter, a support candidate, a skilled person, a checker, an approver, or another person associated with the organization”.
Claims 2-5, 7-10, and 12-15 do not disclose additional elements, further narrowing the abstract ideas of the independent claims and thus not practically integrated under prong 2A as part of a practical application or under 2B not significantly more for the same reasons and rationale as above.
After considering all claim elements, both individually and in combination, Examiner has determined that the claims are directed to the above abstract ideas and do not amount to significantly more. See Alice Corporation Pty. Ltd. v. CLS Bank International, No. 13–298.
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 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 1-15 are rejected under 35 U.S.C. 103 as being obvious by the combination of US 20170344927 to Coletta et. al. (hereinafter referred to as “Coletta”) in view of US 20220375015 to Botteril et. al. (hereinafter referred to as “Botteril”).
(A) As per Claims 1, 6, and 11:
Coletta expressly discloses:
acquire an experience value of a user; (Coletta ¶19 the client device may receive a selection of one or more parameters relating to processing the employee information to determine a set of skill proficiency levels for an employee).
determine a skill level of the user based on the experience value, wherein the skill level of the user is either skilled or unskilled; (Coletta ¶22 the cloud server may determine that a task performed greater than a threshold amount of time prior to determining the skill proficiency level corresponds to an employee being associated with a lower skill proficiency level (i.e. unskilled)).
output information regarding the support candidates; (Coletta ¶27 the cloud server may determine, for a third employee who also previously worked at Company A, a higher skill proficiency level than had the third employee not previously worked at Company A).,
cause a display device to display information regarding at least one of (a) the skill level of the user, or (b) the support candidates; (Coletta ¶71 cloud server 220 causes client device 210-3 to provide the updated employee profile and a skill proficiencies report for display).
Although Coletta teaches a cloud server that causes the client device to provide a user interface to input employee information associated with a set of employees a company, it doesn’t expressly disclose extracting support candidates based on experience values based on user unskilled level, however Botteril teaches:
extract support candidates based on experience values of other users in response to determining that the skill level of the user is unskilled; (Botteril ¶83, 94 a low grade on such post-course assessments may indicate to the employer that the user may need to be re-trained in the skill or skills due to lack of retention. A mentor may be assigned to the user prior to initiating delivery of course content. For example, the mentor placement engine may identify a mentor that is a “best match” for the user, according to characteristics of the user defined in the user metadata for the user stored in the user profile data store 330 and according to characteristics of the mentor defined in mentor metadata for the mentor stored in the mentor data store 338. In some embodiments, this match may be determined by processing the user's characteristics and multiple mentors' respective characteristics in order to identify which mentor is most characteristically similar to the user, as pertains to the course in which the student is enrolled. For example, statistical methods or artificial intelligence models such as machine learning models may be executed to process the mentor metadata and the user data to generate a number of similarity scores for each user-mentor pair, and the mentor corresponding to the highest similarity score may be identified as the “best match” for the user. The mentor and user may collaborate to define success criteria for the course, and the mentor may provide guidance (e.g., derived from the mentor's practical experience) to the user as they progress through the course).
It would be obvious to one of ordinary skill in the art at the time of the claimed invention was filed to have modified Coletta’s cloud server to cause client devices to provide the updated employee profile and a skill proficiencies report for display and have a low grade on such post-course assessments may indicate to the employer that the user may need to be re-trained in the skill or skills due to lack of retention of Botteril as both are analogous art which teaches cloud server that determine that a task performed greater than a threshold amount of time prior to determining the skill proficiency level corresponds to an employee being associated with a lower skill proficiency level as taught in Coletta and have the mentor placement engine identify a mentor that is a “best match” for the user, according to characteristics of the user defined in the user metadata and according to characteristics of the mentor defined in mentor metadata as taught in Botteril.
Coletta teaches a method in ¶5.
(B) As per Claims 2, 7, and 12:
Although Coletta teaches a cloud server that causes the client device to provide a user interface to input employee information associated with a set of employees a company, it doesn’t expressly disclose a workflow of a plurality of workflows, however Botteril teaches:
wherein the experience value is the experience value for a workflow of a plurality of workflows; (Botteril ¶90 FIG. 4 shows an illustrative process flow of a method 400 by which, based on the goals and abilities of a user, the user may be provided with experiential training, and may subsequently be validated and provided with credentials confirming that they have acquired one or more skills and/or associated practical experience via the experiential training).
It would be obvious to one of ordinary skill in the art at the time of the claimed invention was filed to have modified Coletta’s cloud server to cause client devices to provide the updated employee profile and a skill proficiencies report for display and have a process flow of a method of Botteril as both are analogous art which teaches cloud server that determine that a task performed greater than a threshold amount of time prior to determining the skill proficiency level corresponds to an employee being associated with a lower skill proficiency level as taught in Coletta and have the user be provided with experiential training, and may subsequently be validated and provided with credentials confirming that they have acquired one or more skills and/or associated practical experience via the experiential training as taught in Botteril.
(C) As per Claims 3, 8, and 13:
Although Coletta teaches a cloud server that causes the client device to provide a user interface to input employee information associated with a set of employees a company, it doesn’t expressly disclose determining a priority level of the support candidates based on support candidates however Botteril teaches:
determine a priority level of the support candidates based on user information associated with the support candidates; output information indicating the priority level of the support candidates; (Botteril ¶84 the mentor placement engine 316 may analyze characteristics of a user and characteristics of a number of mentors within the mentor pool of the mentor data store 338. For example, the mentor placement engine 316 may perform a statistical analysis or apply an artificial intelligence model, such as a machine learning model, to characteristics of the user retrieved from the user profile data store 330 and to characteristics of mentors retrieved from the mentor data store, and may identify a “best match” between the user and one of the mentors that is found to have relevant characteristics that are most similar to those of the user. Alerts may be sent to the user's user device 306 and the mentor's mentor device 304 by the content management servers 310 via the web servers 308 and communication networks 320, the alerts indicating the match between the user and the mentor).
It would be obvious to one of ordinary skill in the art at the time of the claimed invention was filed to have modified Coletta’s cloud server to cause client devices to provide the updated employee profile and a skill proficiencies report for display and have the mentor placement engine analyze characteristics of a user and characteristics of a number of mentors within the mentor pool of the mentor data store of Botteril as both are analogous art which teaches cloud server that determine that a task performed greater than a threshold amount of time prior to determining the skill proficiency level corresponds to an employee being associated with a lower skill proficiency level as taught in Coletta and have alerts sent to the user's user device and the mentor's device by the content management servers via the web servers and communication networks, the alerts indicating the match between the user and the mentor as taught in Botteril.
(D) As per Claims 4, 9, and 14:
Coletta expressly discloses:
acquire work history information associated with the user; determine the skill level based on the work history information; (Coletta ¶54 when cloud server 220 determines that an employee completed a role at a time failing to satisfy a threshold recency (e.g., greater than 12 months prior to determining a skill proficiency level for the employee), cloud server 220 may reduce the particular skill proficiency level).
(E) As per Claims 5, 10, and 15:
Coletta expressly discloses:
update the experience value of a user based on changes to the work history information associated with the user; (Coletta ¶66 cloud server 220 may periodically update a proficiency level of an employee, and may provide updated information associated with an updated proficiency level. For example, cloud server 220 may determine that an employee classification is to be adjusted from a first skill proficiency level to a second skill proficiency level based on an updated duration (e.g., after an employee works at a role for a period of time), an updated recency (e.g., after a period of time has elapsed from an employee completing work at a role), or the like).
output the updated experience value of the user; (Coletta ¶66 cloud server 220 may automatically receive updated information from the human resources system, and may update the classification of the employee based on receiving the updated information. In this way, cloud server 220 automatically maintains up to date skill proficiency information for a set of employees, permitting staffing decisions to be made more rapidly than utilizing questionnaires or survey results).
cause the display device to display information regarding the skill level of the user; (Coletta ¶71 loud server 220 may generate an updated employee profile without requiring validation. As shown by reference number 550, cloud server 220 causes client device 210-3 to provide the updated employee profile and a skill proficiencies report for display).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
D. Bañeres and J. Conesa, "eOrient@ -- A Recommender System to Address Life-Long Learning and Promote Employability," 2016 International Conference on Intelligent Networking and Collaborative Systems (INCoS), Ostrava, Czech Republic, 2016, pp. 351-356
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATHEUS R STIVALETTI whose telephone number is (571)272-5758. The examiner can normally be reached on M-F 8:30-5:30.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao Wu can be reached on (571)272-6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-1822.
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/MATHEUS RIBEIRO STIVALETTI/Primary Examiner, Art Unit 3623 7/2/2026
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