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 AIA .
Status of Claims
This communication is a Final Office action in response to communications received on 10/20/2025. Claims 1, 12 and 20 have been amended. Therefore, claims 1-20 are currently pending and have been addressed below.
Response to Amendment
With respect to the Double Patenting Rejection for U.S. Patent No. 11/803,861 and Applicant’s remarks to file a terminal disclaimer, the rejection is held in abeyance.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11/803,861. Although the claims at issue are not identical, they are not patentably distinct from each other because:
Regarding claim 1, A method of matching a user with a representative for providing support to the user, the method comprising: ((11/803,861, claim 16) perform a method for matching a user to a representative for providing support to the user)
receiving user information relating to the user; ((11/803,861, claim 1) receiving user information relating to the user)
receiving issue-related information on a user-experienced issue of the user; ((11/803,861, claim 1) receiving issue-related information on a user-experienced issue)
storing, on a storage device, the user information and the issue-related information; ((11/803,861, claim 1) storing, on a storage device, the user information, the issue-related information)
calculating a plurality of representative rankings corresponding to a plurality of representatives based at least in part on a first success rate of the plurality of representatives in resolving issues that are similar to the user- experienced issue and an overall average time to resolve the issues; ((11/803,861, claim 1) calculating a plurality of representative rankings based at least in part on a first success rate of a plurality of other representatives in resolving similar technical difficulties, an overall average time to resolve the similar technical difficulties)
wherein the plurality of representative rankings are calculated based further in part on a time since each respective representative of the plurality of representatives handled a similar user-experienced issue; ((11/803,861, claim 1) calculating a plurality of representative rankings based at least in part on a first success rate of a plurality of other representatives in resolving similar technical difficulties)
automatically selecting a chosen representative from the plurality of representatives, based on the plurality of representative rankings; ((11/803,861, claim 1) automatically selecting for assignment to the user, a selected representative from the one or more representatives)
receiving user feedback from the user based on a user experience of the user with the chosen representative; and ((11/803,861, claim 1) receiving user feedback from the user based on a user experience of the user with the selected representative)
updating a representative profile of the chosen representative in real time based on a user satisfaction score from the user feedback, including updating a chosen representative ranking based on the user feedback and a length of time to resolve the user-experienced issue ((11/803,861, claim 1) updating a representative profile of the selected representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a selected representative ranking and a length of time to resolve the user-experienced issue).
Regarding claim 2, The method of claim 1, wherein the user information is received via a graphical user interface, further comprising: receiving interaction information related to a user interaction with the graphical user interface ((11/803,861, claim 1) receiving a help button selection from the user in the graphical user interface, the help button selection being responsive to the user encountering a technical difficulty; recording a first set of interaction information regarding a first user interaction of the user with the graphical user interface; after recording the first set of interaction information, presenting a list of help options to the user through the graphical user interface; recording a second set of interaction information regarding a second user interaction of the user with the graphical user interface after receiving the help button selection).
Regarding claim 3, The method of claim 2, further comprising: predicting a predicted issue based on a user profile of the user; ((11/803,861, claim 1) predicting a predicted issue based on the user profile)
computing a confidence level that the predicted issue is the user-experienced issue; ((11/803,861, claim 1) computing a confidence level that the predicted issue is the user-experienced issue)
updating the confidence level based on one or more responses received from the user comprising additional information relating to the user-experienced issue; and ((11/803,861, claim 1) updating the confidence level based on one or more responses received from the user comprising additional information relating to the user-experienced issue)
determining a likely resolution to the user-experienced issue based at least in part on the user information, the issue-related information, the user profile, and the interaction information related to the user interaction with the graphical user interface ((11/803,861, claim 1) determining a likely resolution to the technical difficulty based at least in part on the user information, the issue-related information, the user profile, and the interaction information related to the user interaction with the graphical user interface).
Regarding claim 4, The method of claim 3, further comprising: presenting to the user an option to select, in real time, between a highly-ranked representative in a tier that is above a representative threshold and a first- available representative, said first-available representative having a lower wait time than the highly-ranked representative but ranked lower than the highly-ranked representative; and ((11/803,861, claim 1) presenting to the user an option to select, in real time, between a highly-ranked representative in the tier that is above the representative threshold and a first- available representative, said first-available representative having a lower wait time than the highly-ranked representative but ranked lower than the highly-ranked representative);
in response to presenting the option, receiving a user input from the user whether to engage with the highly-ranked representative or the first-available representative ((11/803,861, claim 1) in response to presenting the option, receiving a user input from the user whether to engage with the highly-ranked representative or the first-available representative).
Regarding claim 5, The method of claim 1, wherein the user information is received from the user via a telephone interface ((11/803,861, claim 4) wherein the representative is a customer service representative. Examiner notes customer service representatives use telephone interfaces.)
Regarding claim 6, The method of claim 1, further comprising: determining a plurality of category scores for each of the plurality of representatives corresponding to a plurality of categories ((11/803,861, claim 1) selected representative ranking corresponding to the category of the user-experienced issue).
Regarding claim 7, The method of claim 6, wherein the plurality of categories comprises: an investments category, a retirement category, and an assets category ((11/803,861, claim 1) corresponding to the category of the user-experienced issue. Examiner notes the data identifying the category is simply a label for the data and is non-functional descriptive matter.)
Regarding claim 8, The method of claim 7, further comprising: determining a category of the plurality of categories that corresponds to the user-experienced issue ((11/803,861, claim 1) corresponding to the category of the user-experienced issue).
Regarding claim 9, The method of claim 1, further comprising: determining a time availability for a respective representative of the plurality of representatives based at least in part on a current status of the respective representative and an average time to complete for the respective representative ((11/803,861, claim 1) success rate of a plurality of other representatives in resolving similar technical difficulties, an overall average time to resolve the similar technical difficulties (11/803,861, claim 5) period of time since solving a similar issue to the user-experienced issue).
Regarding claim 10, The method of claim 1, wherein the user-experienced issue is associated with a tax application and the user information comprises tax information ((11/803,861, claim 1) receiving issue-related information on a user-experienced issue. Examiner notes the category of the issue is simply a label for the data and is non-functional descriptive matter).
Regarding claim 11, The method of claim 10, wherein the plurality of representatives comprises tax professionals ((11/803,861, claim 4) wherein the representative is a customer service representative)
Regarding claim 12, One or more non-transitory computer-readable media including computer- executable instructions that, when executed on at least one processor perform a method of matching a user with a representative for providing support to the user, the method comprising: receiving user information relating to the user via a graphical user interface; ((11/803,861, claim 16) One or more non-transitory computer-readable media storing that store computer-executable instructions that, when executed by at least one processor, perform a method for matching a user to a representative for providing support to the user, comprising: receiving issue-related information on user-experienced issue regarding use of a software application having a graphical user interface)
receiving issue-related information on a user-experienced issue of the user via the graphical user interface ((11/803,861, claim 1) receiving issue-related information on a user-experienced issue via the graphical user interface) calculating a plurality of representative rankings corresponding to a plurality of representatives based at least in part on a first success rate of the plurality of representatives in resolving issues that are similar to the user- experienced issue and an overall average time to resolve the issues; ((11/803,861, claim 1) calculating a plurality of representative rankings based at least in part on a first success rate of a plurality of other representatives in resolving similar technical difficulties, an overall average time to resolve the similar technical difficulties)
wherein the plurality of representative rankings are calculated based further in part on a time since each respective representative of the plurality of representatives handled a similar user-experienced issue; ((11/803,861, claim 1) calculating a plurality of representative rankings based at least in part on a first success rate of a plurality of other representatives in resolving similar technical difficulties)
automatically selecting a chosen representative from the plurality of representatives, based on the plurality of representative rankings; ((11/803,861, claim 1) automatically selecting for assignment to the user, a selected representative from the one or more representatives)
receiving user feedback from the user based on a user experience of the user with the chosen representative; and ((11/803,861, claim 1) receiving user feedback from the user based on a user experience of the user with the selected representative)
updating a representative profile of the chosen representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a chosen representative ranking based on the user feedback and a length of time to resolve the user- experienced issue ((11/803,861, claim 1) updating a representative profile of the selected representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a selected representative ranking and a length of time to resolve the user-experienced issue).
Regarding claim 13, The one or more non-transitory computer-readable media of claim 12, wherein the method further comprises: determining the category that corresponds to the user-experienced issue from a plurality of issue categories ((11/803,861, claim 1) corresponding to the category of the user-experienced issue).
Regarding claim 14, The one or more non-transitory computer-readable media of claim 13, wherein the chosen representative ranking is updated with respect to the category that corresponds to the user-experienced issue ((11/803,861, claim 1) updating a representative profile of the selected representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a selected representative ranking corresponding to the category of the user-experienced issue).
Regarding claim 15, The one or more non-transitory computer-readable media of claim 14, wherein the plurality of issue categories comprises: an investments category, a retirement category, and an assets category ((11/803,861, claim 1) corresponding to the category of the user-experienced issue. Examiner notes the data identifying the category is simply a label for the data and is non-functional descriptive matter.)
Regarding claim 16, The one or more non-transitory computer-readable media of claim 12, wherein the method further comprises: storing, on a storage device, the user information and the issue-related information ((11/803,861, claim 1) storing, on a storage device, the user information, the issue-related information).
Regarding claim 17, The one or more non-transitory computer-readable media of claim 12, wherein the method further comprises: determining an amount of time since a last experience in resolving a class of issues that are similar to the user-experienced issue for the chosen representative; and ((11/803,861, claim 1) success rate of a plurality of other representatives in resolving similar technical difficulties, an overall average time to resolve the similar technical difficulties (11/803,861, claim 5) period of time since solving a similar issue to the user-experienced issue).
further updating the representative profile of the chosen representative based at least in part on the time since the last experience in resolving the class of issues that are similar to the user-experienced issue ((11/803,861, claim 1) updating a representative profile of the selected representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a selected representative ranking and a length of time to resolve the user-experienced issue).
Regarding claim 18, The one or more non-transitory computer-readable media of claim 17, wherein the method further comprises: determining a frequency of experience in resolving the class of issues that are similar to the user-experienced issue for the chosen representative, ((11/803,861, claim 1) calculating a plurality of representative rankings based at least in part on a first success rate of a plurality of other representatives in resolving similar technical difficulties)
wherein the representative profile is updated based further in part on the frequency of resolving the class of issues that are similar to the user-experienced issue ((11/803,861, claim 1) updating a representative profile of the selected representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a selected representative ranking corresponding to the category of the user-experienced issue based on the user feedback and a length of time to resolve the user-experienced issue)
Regarding claim 19, The one or more non-transitory computer-readable media of claim 12, wherein the method further comprises: comparing a wait time associated with the chosen representative with one or more wait times of other representatives of the plurality of representatives ((11/803,861, claim 1) a highly-ranked representative in the tier that is above the representative threshold and a first-available representative, said first-available representative having a lower wait time than the highly-ranked representative).
Regarding claim 20, A system comprising at least one processor and at least one non-transitory computer-readable media storing computer-executable instructions that, when executed by the at least one processor, perform a method for matching a user with a representative for providing support to the user, the method comprising: ((11/803,861, claim 16) One or more non-transitory computer-readable media storing that store computer-executable instructions that, when executed by at least one processor, perform a method for matching a user to a representative for providing support to the user)
receiving user information relating to the user via a graphical user interface; ((11/803,861, claim 1) receiving issue-related information on a user-experienced issue via the graphical user interface)
receiving issue-related information on a user-experienced issue of the user via the graphical user interface; ((11/803,861, claim 1) receiving issue-related information on a user-experienced issue)
storing, on a storage device, the user information and the issue-related information; ((11/803,861, claim 1) storing, on a storage device, the user information, the issue-related information)
calculating a plurality of representative rankings corresponding to plurality of representatives based at least in part on a first success rate of the plurality of representatives in resolving issues that are similar to the user- experienced issue and an overall average time to resolve the issues; ((11/803,861, claim 1) calculating a plurality of representative rankings based at least in part on a first success rate of a plurality of other representatives in resolving similar technical difficulties, an overall average time to resolve the similar technical difficulties)
wherein the plurality of representative rankings are calculated based further in part on a time since each respective representative of the plurality of representatives handled a similar user-experienced issue; ((11/803,861, claim 1) calculating a plurality of representative rankings based at least in part on a first success rate of a plurality of other representatives in resolving similar technical difficulties)
automatically selecting a chosen representative from the plurality of representatives, based on the plurality of representative rankings; ((11/803,861, claim 1) automatically selecting for assignment to the user, a selected representative from the one or more representatives)
receiving user feedback from the user based on a user experience of the user with the chosen representative; and ((11/803,861, claim 1) receiving user feedback from the user based on a user experience of the user with the selected representative)
updating a representative profile of the chosen representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a chosen representative ranking corresponding to the category of the user-experienced issue based on the user feedback and a length of time to resolve the user-experienced issue ((11/803,861, claim 1) updating a representative profile of the selected representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a selected representative ranking and a length of time to resolve the user-experienced issue).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception without a practical application and significantly more.
Step 1: Identifying Statutory Categories
When considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claims are directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (i.e., Step 1). In the instant case, claims 1-11 are directed to a method (i.e. a process). Claims 12-19 are directed to one or more non-transitory computer-readable media (i.e. an article of manufacture). Claim 20 is directed to a system (i.e. a machine). Thus, each of these claims fall within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A: Prong One: Abstract Ideas
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention recites an abstract idea. Independent claim 12, analogous to claims 1 and 20, recites: perform a method of matching a user with a representative for providing support to the user, the method comprising: receiving user information relating to the user; receiving issue-related information on a user-experienced issue of the user; calculating a plurality of representative rankings corresponding to a plurality of representatives based at least in part on a first success rate of the plurality of representatives in resolving issues that are similar to the user-experienced issue and an overall average time to resolve the issues; wherein the plurality of representative rankings are calculated based further in part on a time since each respective representative of the plurality of representatives handled a similar user-experienced issue; automatically selecting a chosen representative from the plurality of representatives, based on the plurality of representative rankings; receiving user feedback from the user based on a user experience of the user with the chosen representative; and updating a representative profile of the chosen representative based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a chosen representative ranking based on the user feedback and a length of time to resolve the user- experienced issue.
The limitations as drafted, is a process that, under its broadest reasonable interpretation, falls under at least the abstract groupings of:
Certain methods of organizing human activity (commercial or legal interactions (including 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)). As the claims discuss a method of matching a user with a representative for providing support to the user, receiving user information; receiving issue-related information on a user-experienced issue of the user; selecting a chosen representative from the plurality of representatives, based on the plurality of representative rankings; receiving user feedback from the user based on a user experience of the user; updating a representative profile based on a user satisfaction score from the user feedback, which is a clear business relation and one of certain methods of organizing human activity.
Mathematical concepts (mathematical relationships, mathematical formulas or equations and mathematical calculations (For example, independent claims 12 and 20 recites: “calculating a plurality of representative rankings corresponding to a plurality of representatives”; claims 1, 12 and 20 recite “a user satisfaction score”; claim 3 recites “ computing a confidence level that the predicted issue is the user-experienced issue”; claim 4 recites “a tier that is above a representative threshold”; claims 6 recites “determining a plurality of category scores”; claim 18 recites “determining a frequency of experience in resolving the class of issues”; claim 19 recites “comparing a wait time associated with the chosen representative with one or more wait times”).
Mental Processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion (claim 12, recites for example: “matching a user with a representative for providing support to the user”, “receiving user information relating to the user”, “receiving issue-related information on a user-experienced issue of the user”, “calculating a plurality of representative rankings corresponding to a plurality of representatives”, “selecting a chosen representative from the plurality of representatives”, “receiving user feedback from the user based on a user experience of the user with the chosen representative”, “updating a representative profile of the chosen representative based on a user satisfaction score”, “updating a chosen representative ranking based on the user feedback and a length of time to resolve the user-experienced issue.”; claim 3 recites “determining a likely resolution to the user-experienced issue based at least in part on the user information”.) Concepts performed in the human mind as mental processes because the steps of matching, receiving, calculating, selecting, updating, determining, and analyzing data mimic human thought processes of observation, evaluation, judgement and opinion, perhaps with paper and pencil, where data interpretation is perceptible in the human mind. See In re TLI Commc’ns LLCPatentLitig., 823 F.3d 607, 611 (Fed. Cir. 2016); FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1093-94 (Fed. Cir. 2016)).
Dependent claims add additional limitations, for example: (claim 2) receiving interaction information related to a user interaction; (claim 3) predicting a predicted issue based on a user profile of the user; computing a confidence level that the predicted issue is the user-experienced issue; updating the confidence level based on one or more responses received from the user comprising additional information relating to the user-experienced issue; and determining a likely resolution to the user-experienced issue based at least in part on the user information, the issue-related information, the user profile, and the interaction information related to the user interaction; (claim 4) presenting to the user an option to select between a highly-ranked representative in a tier that is above a representative threshold and a first-available representative, said first-available representative having a lower wait time than the highly-ranked representative but ranked lower than the highly-ranked representative; and in response to presenting the option, receiving a user input from the user whether to engage with the highly-ranked representative or the first-available representative; (claim 5) wherein the user information is received from the user; (claim 6) determining a plurality of category scores for each of the plurality of representatives corresponding to a plurality of categories; (claim 7) wherein the plurality of categories comprises: an investments category, a retirement category, and an assets category; (claim 8) determining a category of the plurality of categories that corresponds to the user- experienced issue; (claim 9) determining a time availability for a respective representative of the plurality of representatives based at least in part on a current status of the respective representative and an average time to complete for the respective representative; (claim 10) wherein the user-experienced issue is associated with a tax application and the user information comprises tax information; (claim 11) wherein the plurality of representatives comprises tax professionals; (claim 13) determining the category that corresponds to the user-experienced issue from a plurality of issue categories; (claim 14) the chosen representative ranking is updated with respect to the category that corresponds to the user-experienced issue; (claim 15) the plurality of issue categories comprises: an investments category, a retirement category, and an assets category; (claim 16) storing the user information and the issue-related information; (claim 17) determining an amount of time since a last experience in resolving a class of issues that are similar to the user-experienced issue for the chosen representative; and further updating the representative profile of the chosen representative based at least in part on the time since the last experience in resolving the class of issues that are similar to the user-experienced issue; (claim 18) determining a frequency of experience in resolving the class of issues that are similar to the user-experienced issue for the chosen representative, wherein the representative profile is updated based further in part on the frequency of resolving the class of issues that are similar to the user-experienced issue; (claim 19) comparing a wait time associated with the chosen representative with one or more wait times of other representatives of the plurality of representatives, but these only serve to further limit the abstract idea.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations of certain methods of organizing human activity, mathematical concepts, and mental processes but for the recitation of generic computer components, the claims recite an abstract idea.
Step 2A: Prong Two
This judicial exception is not integrated into a practical application because the claims merely describe how to generally “apply” the abstract idea. In particular, the claims only recite the additional elements (claim 1) storage device, real time; (claim 5) telephone; (claim 12) non-transitory computer-readable media including computer- executable instructions; processor; graphical user interface; real time; (claim 16) storage device; (claim 20) processor(s); non-transitory computer-readable media storing computer-executable instructions; graphical user interface; storage device. These additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components. Simply implementing the abstract idea on generic computer components is not a practical application of the abstract idea, as it adds the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f). The limitations generally link the abstract idea to a particular technological environment or field of use (such as computing, see MPEP 2106.05(h)). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception and generally link the abstract idea to a particular technological environment or field of use. Furthermore, claims 1-20 have been fully analyzed to determine whether there are additional elements recited that amount to significantly more than the abstract idea. The limitations fail to include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Thus, nothing in the claim adds significantly more to the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. The claims are ineligible. Therefore, since there are no limitations in the claim that transform the exception into a patent eligible application such that the claim amounts to significantly more than the exception itself, the claims are rejected under 35 USC 101 as being directed to non-statutory subject matter.
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 non-obviousness.
Claims 1-2, 5-9 and 12-20 are rejected under 35 U.S.C. 103 as being unpatentable over Hambridge et al. (US 2018/0330305 A1), hereinafter “Hambridge” and Kaufman et al. (US 2009/0122972 A1), hereinafter “Kaufman”.
Regarding claim 1, Hambridge teaches A method of matching a user with a representative for providing support to the user, the method comprising: receiving user information relating to the user; (Hambridge, para 0008, at least one best available candidate (Examiner note representative) to respond to the issue can be determined, the best available candidate selected from the pool of candidates. Such processes can ensure that the issue is resolved in a very timely and effective manner; Hambridge, para 0025, receive issue information from one or more of the client devices);
receiving issue-related information on a user-experienced issue of the user; (Hambridge, para 0025, receive issue information from one or more of the client devices);
storing, on a storage device, the user information and the issue-related information; (Hambridge, para 0023, the issue information can be stored to a computer readable storage medium (e.g., memory elements) within the on-call management system);
calculating a plurality of representative rankings corresponding to a plurality of representatives based at least in part on a first success rate of the plurality of representatives in resolving issues that are similar to the user- experienced issue and an overall … to resolve the issues; (Hambridge, para 0041, assign a weighted score to each of the location data, skills data, online activity data, work schedule data, engagement policies (Hambridge, para 0052, the engagement policies includes a record of success of the candidate in resolving issues). Further, the on-call management can determine a total score based on the weighted scores. For instance, the on-call management system can determine the total score to be a sum of the weighted scores, though the present arrangements are not limited in this regard. The on-call management application can rank the candidates based on the total score, and choose the candidate having the highest ranking (e.g., highest total score ), or the candidates having the highest rankings, as the selected candidates. Based at least on the weighted scores, and optionally weighted scores, the ranking for each candidate can represent an availability of the candidate to respond to the issue. Based on the weighted score, the ranking for each candidate also can represent the capability of the candidate to respond to the issue.);
wherein the plurality of representative rankings are calculated based further in part on a ... each respective representative of the plurality of representatives handled a similar user-experienced issue; (Hambridge, teaches the on-call management system analyzes and ranks representatives to respond to an issue, including a record of success of the representative in resolving issues (Hambridge, para 0041 and 0052)... Hambridge, para 0009, teaches information corresponding to the respective representative can indicate a variety of other information. For example, the information can indicate skills (e.g., skill set), activity patterns, behavioral patterns, and so on. Thus the selection process can ensure that the representatives are well qualified to resolve the issue. Further, Hambridge, para 0027, teaches each user profile can include a myriad of information pertaining to a respective representative. For example, a user profile can include the candidate's skill sets and/or certifications, historical information related to how the candidate has responded, working patterns of the representative, activity patterns, previous patterns of behavior, and so on. Various patterns can be determined by capturing various data.... For example, the client devices can include an application that monitors such patterns and updates the representative’s profile based on such monitoring); automatically selecting a chosen representative from the plurality of representatives, based on the plurality of representative rankings; (Hambridge, Abstract, A pool of candidates (Examiner note representative) to respond to an issue can be determined. For each of a plurality of candidates, information corresponding to a respective candidate can be accessed and analyzed. Based on analyzing the information, at least one best available candidate to respond to the issue can be determined; para 0041, when selecting the candidates, the on-call management application can, for each candidate in the candidate pool, assign a weighted score... The on-call management application can rank the candidates based on the total score, and choose the candidate having the highest ranking);
updating a representative profile of the chosen representative in real time based on a user satisfaction score from the user feedback, including updating a chosen representative ranking based on the user feedback and a … to resolve the user-experienced issue (Hambridge, para 0060-0061, Based on feedback, the on-call management application can update the user profile of the candidate to indicate the user's skill set for that type of issue. This can be used by the on-call management application when determining the weighted score for future issues. Hambridge, para 0027, updates the candidate’s user profile on historical information related to how the candidate has responded to past on-call notifications (e.g., electronic messages and/or phone calls)).
Yet, Hambridge does not appear to explicitly teach and in the same field of endeavor Kaufman teaches average time ... time since (Kaufman teaches time throughout, see at least Figures 3H-3I; Kaufman, Figures 10 and 11a, teaches length of time of call; Figure 11a teaches average time spent talking) receiving user feedback from the user based on a user experience of the user with the chosen representative; and (Kaufman, para 0132-0133, teaches customers may be able to provide feedback at the end of the call; and feedback in regards to customers may be implemented) length of time (Kaufman, Figures 10 and 11a, teaches length of time of call. For example, Kaufman, Figure 10, teaches agent spent 8 minutes and 51 seconds on call).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Hambridge with average time ... time since … receiving user feedback from the user based on a user experience of the user with the chosen representative; and … length of time as taught by Kaufman with the motivation for the incoming call to be assigned to top-ranked or optimal agents (Kaufman, para 0072). The Hambridge invention, now incorporating the Kaufman invention, has all the limitations of claim 1.
Regarding Claim 2, Hambridge, now incorporating Kaufman, teaches The method of claim 1, wherein the user information is received via a graphical user interface, further comprising: receiving interaction information related to a user interaction with the graphical user interface (Hambridge, para 0027, capturing various data generated by one or more client devices; Further, Kaufman teaches user interfaces throughout, see at least para 0034, the computing machine is capable of displaying a user interface).
Regarding Claim 5, Hambridge, now incorporating Kaufman, teaches The method of claim 1, wherein the user information is received from the user via a telephone interface (Hambridge, para 0022, the Public Switched Telephone Network (PSTN)).
Regarding Claim 6, Hambridge, now incorporating Kaufman, teaches The method of claim 1, further comprising: determining a plurality of category scores for each of the plurality of representatives corresponding to a plurality of categories (Hambridge, para 0041 and 0049, When selecting the candidates, the on-call management application can, for each candidate in the candidate pool 160, assign a weighted score to each of the location data, skills data, online activity data, work schedule data, engagement policies and sensor data, respectively.)
Regarding Claim 7, Hambridge, now incorporating Kaufman, teaches The method of claim 6, wherein the plurality of categories comprises: an investments category, a retirement category, and an assets category (Hambridge, para 0049, Examiner notes the category of skills data is based on the skills of the respective candidate, and how closely the skills match a skill set (category) anticipated to be required to resolve the issue. For example, if the issue is a problem with a PHP query being used to access a database, and the candidate's skills data indicates the candidate is an expert in PHP, the on-call management application can determine a high value for the weighted score, for example 10. If the candidate's skills data does not indicate that the candidate is an expert in PHP, but indicates that the candidate manages databases, the on-call management application can determine a different value for the weighted score, for example 7. If, however, the candidate's skills data does not list expertise or experience with databases or PHP, but indicates the candidate has experience in hardware configuration, the on-call management application can determine a different value for the weighted score, for example 1. Again, the on-call management application can determine the weighted score based on any of a myriad of skills data and issues, and the present arrangements are not limited in this regard.
Examiner notes the data identifying the category is simply a label for the data and is non-functional descriptive matter. Data identifying a category adds little, if anything, to the claimed acts or steps and thus does not serve to distinguish over the prior art. Any differences related merely to the meaning and information conveyed through labels (i.e., the specific type of information) which does not explicitly alter or impact the steps of the system or method does not patentably distinguish the claimed invention from the prior art in terms of patentability.
Regarding Claim 8, Hambridge, now incorporating Kaufman, teaches The method of claim 7, further comprising: determining a category of the plurality of categories that corresponds to the user- experienced issue (Hambridge, para 0049, Examiner notes the category of skills data is based on the skills of the respective candidate, and how closely the skills match a skill set (category) anticipated to be required to resolve the issue. Examiner notes Applicant’s own specification merely mentions categories once).
Regarding Claim 9, Hambridge, now incorporating Kaufman, teaches The method of claim 1, further comprising: determining a time availability for a respective representative of the plurality of representatives based at least in part on a current status of the respective representative and an average time to complete for the respective representative (Hambridge, para 0009, the candidate presently is working, and thus presently available (Examiner notes current status of representative) Kaufman, Figures 8 and 9, teaches agents available to take a call; and average time spend handling calls).
Regarding claim 12, Hambridge teaches One or more non-transitory computer-readable media including computer- executable instructions that, when executed on at least one processor perform a method of matching a user with a representative for providing support to the user, the method comprising: receiving user information relating to the user via a graphical user interface; (Hambridge, para 0008, at least one best available candidate (Examiner note representative) to respond to the issue can be determined, the best available candidate selected from the pool of candidates. Such processes can ensure that the issue is resolved in a very timely and effective manner; Hambridge, para 0025, receive issue information from one or more of the client devices; Hambridge, para 0015, a “computer readable storage medium” is not a transitory, propagating signal per se);
receiving issue-related information on a user-experienced issue of the user via the graphical user interface; (Hambridge, para 0025, receive issue information from one or more of the client devices);
calculating a plurality of representative rankings corresponding to a plurality of representatives based at least in part on a first success rate of the plurality of representatives in resolving issues that are similar to the user- experienced issue and an overall … to resolve the issues; (Hambridge, para 0041, assign a weighted score to each of the location data, skills data, online activity data, work schedule data, engagement policies (Hambridge, para 0052, the engagement policies includes a record of success of the candidate in resolving issues). Further, the on-call management can determine a total score based on the weighted scores. For instance, the on-call management system can determine the total score to be a sum of the weighted scores, though the present arrangements are not limited in this regard. The on-call management application can rank the candidates based on the total score, and choose the candidate having the highest ranking (e.g., highest total score ), or the candidates having the highest rankings, as the selected candidates. Based at least on the weighted scores, and optionally weighted scores, the ranking for each candidate can represent an availability of the candidate to respond to the issue. Based on the weighted score, the ranking for each candidate also can represent the capability of the candidate to respond to the issue.);
wherein the plurality of representative rankings are calculated based further in part on a ... each respective representative of the plurality of representatives handled a similar user-experienced issue; (Hambridge, teaches the on-call management system analyzes and ranks representatives to respond to an issue, including a record of success of the representative in resolving issues (Hambridge, para 0041 and 0052)... Hambridge, para 0009, teaches information corresponding to the respective representative can indicate a variety of other information. For example, the information can indicate skills (e.g., skill set), activity patterns, behavioral patterns, and so on. Thus the selection process can ensure that the representatives are well qualified to resolve the issue. Further, Hambridge, para 0027, teaches each user profile can include a myriad of information pertaining to a respective representative. For example, a user profile can include the candidate's skill sets and/or certifications, historical information related to how the candidate has responded, working patterns of the representative, activity patterns, previous patterns of behavior, and so on. Various patterns can be determined by capturing various data.... For example, the client devices can include an application that monitors such patterns and updates the representative’s profile based on such monitoring.);
automatically selecting a chosen representative from the plurality of representatives, based on the plurality of representative rankings; (Hambridge, Abstract, A pool of candidates (Examiner note representative) to respond to an issue can be determined. For each of a plurality of candidates, information corresponding to a respective candidate can be accessed and analyzed. Based on analyzing the information, at least one best available candidate to respond to the issue can be determined; para 0041, when selecting the candidates, the on-call management application can, for each candidate in the candidate pool, assign a weighted score... The on-call management application can rank the candidates based on the total score, and choose the candidate having the highest ranking);
updating a representative profile of the chosen representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a chosen representative ranking based on the user feedback and a … to resolve the user- experienced issue (Hambridge, para 0060-0061, Based on feedback, the on-call management application can update the user profile of the candidate to indicate the user's skill set for that type of issue. This can be used by the on-call management application when determining the weighted score for future issues. Hambridge, para 0027, updates the candidate’s user profile on historical information related to how the candidate has responded to past on-call notifications (e.g., electronic messages and/or phone calls)). Yet, Hambridge does not appear to explicitly teach and in the same field of endeavor Kaufman teaches average time ... time since (Kaufman teaches time throughout, see at least Figures 3H-3I; Kaufman, Figures 10 and 11a, teaches length of time of call; Figure 11a teaches average time spent talking) receiving user feedback from the user based on a user experience of the user with the chosen representative; and (Kaufman, para 0132-0133, teaches customers may be able to provide feedback at the end of the call; and feedback in regards to customers may be implemented) length of time (Kaufman, Figures 10 and 11a, teaches length of time of call. For example, Kaufman, Figure 10, teaches agent spent 8 minutes and 51 seconds on call).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Hambridge with average time ... time since … receiving user feedback from the user based on a user experience of the user with the chosen representative; and … length of time as taught by Kaufman with the motivation for the incoming call to be assigned to top-ranked or optimal agents (Kaufman, para 0072). The Hambridge invention, now incorporating the Kaufman invention, has all the limitations of claim 12.
Regarding Claim 13, Hambridge, now incorporating Kaufman, teaches The one or more non-transitory computer-readable media of claim 12, wherein the method further comprises: determining the category that corresponds to the user-experienced issue from a plurality of issue categories (Hambridge, para 0049, Examiner notes the category of skills data is based on the skills of the respective candidate, and how closely the skills match a skill set (category) anticipated to be required to resolve the issue. Examiner notes Applicant’s own specification merely mentions categories once).
Regarding Claim 14, Hambridge, now incorporating Kaufman, teaches The one or more non-transitory computer-readable media of claim 13, wherein the chosen representative ranking is updated with respect to the category that corresponds to the user-experienced issue (Hambridge, para 0060-0061, Based on feedback, the on-call management application can update the user profile of the candidate to indicate the user's skill set for that type of issue. This can be used by the on-call management application when determining the weighted score for future issues.)
Regarding Claim 15, Hambridge, now incorporating Kaufman, teaches . The one or more non-transitory computer-readable media of claim 14, wherein the plurality of issue categories comprises: an investments category, a retirement category, and an assets category (Hambridge, para 0049, Examiner notes the category of skills data is based on the skills of the respective candidate, and how closely the skills match a skill set (category) anticipated to be required to resolve the issue. For example, if the issue is a problem with a PHP query being used to access a database, and the candidate's skills data indicates the candidate is an expert in PHP, the on-call management application can determine a high value for the weighted score, for example 10. If the candidate's skills data does not indicate that the candidate is an expert in PHP, but indicates that the candidate manages databases, the on-call management application can determine a different value for the weighted score, for example 7. If, however, the candidate's skills data does not list expertise or experience with databases or PHP, but indicates the candidate has experience in hardware configuration, the on-call management application can determine a different value for the weighted score, for example 1. Again, the on-call management application can determine the weighted score based on any of a myriad of skills data and issues, and the present arrangements are not limited in this regard.
Examiner notes the data identifying the category is simply a label for the data and is non-functional descriptive matter. Data identifying a category adds little, if anything, to the claimed acts or steps and thus does not serve to distinguish over the prior art. Any differences related merely to the meaning and information conveyed through labels (i.e., the specific type of information) which does not explicitly alter or impact the steps of the system or method does not patentably distinguish the claimed invention from the prior art in terms of patentability.
Regarding Claim 16, Hambridge, now incorporating Kaufman, teaches The one or more non-transitory computer-readable media of claim 12, wherein the method further comprises: storing, on a storage device, the user information and the issue-related information (Hambridge, para 0023, the issue information can be stored to a computer readable storage medium (e.g., memory elements) within the on-call management system).
Regarding Claim 17, Hambridge, now incorporating Kaufman, teaches The one or more non-transitory computer-readable media of claim 12, wherein the method further comprises: determining an amount of time since a last experience in resolving a class of issues that are similar to the user-experienced issue for the chosen representative; and further updating the representative profile of the chosen representative based at least in part on the time since the last experience in resolving the class of issues that are similar to the user-experienced issue (Hambridge, para 0054, frequency at which the candidate has been requested to respond to previous issues and/or a last time the candidate was requested to respond to a previous issue; Hambridge, para 0052, the candidate has participated in resolving issues at least a first threshold number of times, and has been successful at resolving such issues; Hambridge, para 0027, updates the candidate’s user profile on historical information related to how the candidate has responded to past on-call notifications (e.g., electronic messages and/or phone calls)).
Regarding Claim 18, Hambridge, now incorporating Kaufman, teaches The one or more non-transitory computer-readable media of claim 17, wherein the method further comprises: determining a frequency of experience in resolving the class of issues that are similar to the user-experienced issue for the chosen representative, wherein the representative profile is updated based further in part on the frequency of resolving the class of issues that are similar to the user-experienced issue (Hambridge, para 0052, the candidate (Examiner notes representative) has participated in resolving issues at least a first threshold number of times, and has been successful at resolving such issues at least a first threshold percentage of the times; Hambridge, para 0027, updates the candidate’s user profile on historical information related to how the candidate has responded to past on-call notifications (e.g., electronic messages and/or phone calls)).
Regarding Claim 19, Hambridge, now incorporating Kaufman, teaches The one or more non-transitory computer-readable media of claim 12, wherein the method further comprises: comparing a wait time associated with the chosen representative with one or more wait times of other representatives of the plurality of representatives (Hambridge, para 0008, at least one best available candidate to respond to the issue can be determined, the best available candidate selected from the pool of candidates can ensure that the issue is resolved in a timely and effective manner; Further, Kaufman, para 0003, teaches shortest wait time for a call).
Regarding claim 20, Hambridge teaches A system comprising at least one processor and at least one non-transitory computer-readable media storing computer-executable instructions that, when executed by the at least one processor, perform a method for matching a user with a representative for providing support to the user, the method comprising: (Hambridge, para 0008, at least one best available candidate (Examiner note representative) to respond to the issue can be determined, the best available candidate selected from the pool of candidates. Such processes can ensure that the issue is resolved in a very timely and effective manner; Hambridge, para 0025, receive issue information from one or more of the client devices; Hambridge, para 0015, a “computer readable storage medium” is not a transitory, propagating signal per se);
receiving user information relating to the user via a graphical user interface; (Hambridge, para 0025, receive issue information from one or more of the client devices);
receiving issue-related information on a user-experienced issue of the user via the graphical user interface; (Hambridge, para 0025, receive issue information from one or more of the client devices);
storing, on a storage device, the user information and the issue-related information; (Hambridge, para 0023, the issue information can be stored to a computer readable storage medium (e.g., memory elements) within the on-call management system).
calculating a plurality of representative rankings corresponding to plurality of representatives based at least in part on a first success rate of the plurality of representatives in resolving issues that are similar to the user- experienced issue and an overall … to resolve the issues; (Hambridge, para 0041, assign a weighted score to each of the location data, skills data, online activity data, work schedule data, engagement policies (Hambridge, para 0052, the engagement policies includes a record of success of the candidate in resolving issues). Further, the on-call management can determine a total score based on the weighted scores. For instance, the on-call management system can determine the total score to be a sum of the weighted scores, though the present arrangements are not limited in this regard. The on-call management application can rank the candidates based on the total score, and choose the candidate having the highest ranking (e.g., highest total score ), or the candidates having the highest rankings, as the selected candidates. Based at least on the weighted scores, and optionally weighted scores, the ranking for each candidate can represent an availability of the candidate to respond to the issue. Based on the weighted score, the ranking for each candidate also can represent the capability of the candidate to respond to the issue.);
wherein the plurality of representative rankings are calculated based further in part on a ... each respective representative of the plurality of representatives handled a similar user-experienced issue; (Hambridge, teaches the on-call management system analyzes and ranks representatives to respond to an issue, including a record of success of the representative in resolving issues (Hambridge, para 0041 and 0052)... Hambridge, para 0009, teaches information corresponding to the respective representative can indicate a variety of other information. For example, the information can indicate skills (e.g., skill set), activity patterns, behavioral patterns, and so on. Thus the selection process can ensure that the representatives are well qualified to resolve the issue. Further, Hambridge, para 0027, teaches each user profile can include a myriad of information pertaining to a respective representative. For example, a user profile can include the candidate's skill sets and/or certifications, historical information related to how the candidate has responded, working patterns of the representative, activity patterns, previous patterns of behavior, and so on. Various patterns can be determined by capturing various data.... For example, the client devices can include an application that monitors such patterns and updates the representative’s profile based on such monitoring);
automatically selecting a chosen representative from the plurality of representatives, based on the plurality of representative rankings; (Hambridge, Abstract, A pool of candidates (Examiner note representative) to respond to an issue can be determined. For each of a plurality of candidates, information corresponding to a respective candidate can be accessed and analyzed. Based on analyzing the information, at least one best available candidate to respond to the issue can be determined; para 0041, when selecting the candidates, the on-call management application can, for each candidate in the candidate pool, assign a weighted score... The on-call management application can rank the candidates based on the total score, and choose the candidate having the highest ranking);
updating a representative profile of the chosen representative in real time based on a user satisfaction score from the user feedback and a category of the user-experienced issue, including updating a chosen representative ranking corresponding to the category of the user-experienced issue based on the user feedback and a … to resolve the user-experienced issue (Hambridge, para 0060-0061, Based on feedback, the on-call management application can update the user profile of the candidate to indicate the user's skill set for that type of issue. This can be used by the on-call management application when determining the weighted score for future issues. Hambridge, para 0027, updates the candidate’s user profile on historical information related to how the candidate has responded to past on-call notifications (e.g., electronic messages and/or phone calls)).
Yet, Hambridge does not appear to explicitly teach and in the same field of endeavor Kaufman teaches average time ... time since (Kaufman teaches time throughout, see at least Figures 3H-3I; Kaufman, Figures 10 and 11a, teaches length of time of call; Figure 11a teaches average time spent talking) receiving user feedback from the user based on a user experience of the user with the chosen representative; and (Kaufman, para 0132-0133, teaches customers may be able to provide feedback at the end of the call; and feedback in regards to customers may be implemented) length of time (Kaufman, Figures 10 and 11a, teaches length of time of call. For example, Kaufman, Figure 10, teaches agent spent 8 minutes and 51 seconds on call).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Hambridge with average time ... time since … receiving user feedback from the user based on a user experience of the user with the chosen representative; and … length of time as taught by Kaufman with the motivation for the incoming call to be assigned to top-ranked or optimal agents (Kaufman, para 0072). The Hambridge invention, now incorporating the Kaufman invention, has all the limitations of claim 20.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Hambridge, Kaufman and Cunningham et al. (US 2011/0270770 A1), hereinafter “Cunningham”.
Regarding Claim 3, Hambridge, now incorporating Kaufman, teaches The method of claim 2, further comprising. Yet, Hambridge and Kaufman do not appear to teach, and in the same field of endeavor Cunningham teaches: predicting a predicted issue based on a user profile of the user; computing a confidence level that the predicted issue is the user-experienced issue; updating the confidence level based on one or more responses received from the user comprising additional information relating to the user-experienced issue; and determining a likely resolution to the user-experienced issue based at least in part on the user information, the issue-related information, the user profile, and the interaction information related to the user interaction with the graphical user interface (Cunningham, Abstract, teaches a prediction indicator and a confidence indicator in a customer service environment… the prediction indicator and the confidence indicator exceeding a predetermined threshold. Further, Cunningham, Para 0016, discloses analyzing an unresolved problem by the trained analysis module to produce a prediction indicator and a confidence indicator for unresolved problems in customer service. Cunningham, para 0031, successfully predict issues of customers based on historical indicators. Cunningham, Figure 1, training model learns characteristics of indicators; refines model to improve; Fig 4, para 0047 and 0051; discloses confident level in predicted class, for example 1 being 100% confident, 0.15 not being very confident at all. Examiner notes Cunningham, para 0052-0071, discloses the data collection as information is gathered and input/updated into prediction model, which therefore updates the prediction model and the confidence level, as in para 0047 teaches the confidence level is based on the prediction.) It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Hambridge and Kaufman with predicting a predicted issue based on a user profile of the user; computing a confidence level that the predicted issue is the user-experienced issue; updating the confidence level based on one or more responses received from the user comprising additional information relating to the user-experienced issue; and determining a likely resolution to the user-experienced issue based at least in part on the user information, the issue-related information, the user profile, and the interaction information related to the user interaction with the graphical user interface as taught by Cunningham with the motivation to successfully predict issues of customers based on historical indicators (Cunningham, para 0031). The Hambridge and Kaufman invention, now incorporating the Cunningham invention, has all the limitations of claim 3.
Claims 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Hambridge, Kaufman and Wang et al. (US 2018/0114274 A1), hereinafter “Wang”.
Regarding Claim 10, Hambridge, now incorporating Kaufman, teaches The method of claim 1, wherein the user-experienced issue is associated with a … and the user information comprises (Hambridge, para 0049, Examiner notes the category of skills data is based on the skills of the respective candidate, and how closely the skills match a skill set (category) anticipated to be required to resolve the issue. For example, if the issue is a problem with a PHP query being used to access a database, and the candidate's skills data indicates the candidate is an expert in PHP, the on-call management application can determine a high value for the weighted score, for example 10. If the candidate's skills data does not indicate that the candidate is an expert in PHP, but indicates that the candidate manages databases, the on-call management application can determine a different value for the weighted score, for example 7. If, however, the candidate's skills data does not list expertise or experience with databases or PHP, but indicates the candidate has experience in hardware configuration, the on-call management application can determine a different value for the weighted score, for example 1. Again, the on-call management application can determine the weighted score based on any of a myriad of skills data and issues, and the present arrangements are not limited in this regard.)
Yet Hambridge and Kaufman do not appear to explicitly teach and in the same field of endeavor Wang teaches tax application and tax information (Wang, Abstract, A system for explaining tax questions for an electronic tax return preparation program).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Hambridge and Kaufman with tax application and tax information as taught by Wang with the motivation for generating explanation assets for tax questions for an electronic tax return preparation program (Hambridge, para 0003). The Hambridge and Kaufman invention, now incorporating the Wang invention, has all the limitations of claim 10.
Regarding Claim 11, Hambridge, now incorporating Kaufman and Wang, teaches The method of claim 10, wherein the plurality of representatives comprises tax professionals (Hambridge, para 0039, the skills data 222 for each candidate can be determined by processing the candidate's respective user profile. The skills data 222 can indicate, for each candidate in the candidate pool, particular areas of expertise of the candidate and/or certifications of the candidate in one or more particular areas of expertise. Wang, para 0006, a computer-implemented method for explaining tax questions for an electronic tax return preparation program includes a computing device executing a tax agent).
Response to Arguments
Applicant’s arguments filed on 10/20/2025 have been fully considered but they are not persuasive.
Regarding 35 U.5.C. § 101 rejections: Examiner has updated the 101 rejections in light of the most recent claim amendments. Applicant’s arguments have been fully considered but are found unpersuasive and Examiner maintains the 101 rejection.
With respect to Applicant’s remarks on Step 2A- Prong I, Examiner respectfully disagrees and notes Applicant generally makes the argument without reciting any specific claim limitations. Examiner respectfully notes the claims fall under abstract ideas of certain methods of organizing human activity, mathematical concepts, and mental processes. See above for complete 101 analysis.
With respect to Applicant’s remarks on Step 2A – Prong 2 and Step 2B, Examiner respectfully disagrees. As an initial matter, “updating a representative profile” is not technical in nature, and is not a technical solution to a technical problem. Further, the judicial exception is not integrated into a practical application because the claims merely describe how to generally “apply” the abstract idea. In particular, the claims only recite the additional elements – (claim 1) storage device, real time; (claim 5) telephone; (claim 12) non-transitory computer-readable media including computer- executable instructions; processor; graphical user interface; real time; (claim 16) storage device; (claim 20) processor(s); non-transitory computer-readable media storing computer-executable instructions; graphical user interface; storage device. These additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components and generally link the abstract idea to a particular technological environment or field of use (such as computing, see MPEP 2106.05(h)). Simply implementing the abstract idea on generic computer components is not a practical application of the abstract idea. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea; the computer elements merely add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f). Further, Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Each step does no more than require a generic
computer to perform generic computer functions. The claims do not, for example, purport to improve the functioning of the computer itself. In addition, the claims do not affect an improvement in any other
technology or technical field. The specification spells out different generic equipment and parameters that might be applied using the concept and the particular steps such conventional processing would entail based on the concept of information access. Thus, the claims at issue amount to nothing significantly more than instructions to apply the abstract idea using some unspecified, generic computer(s). Therefore, Applicants remarks are found unpersuasive and Examiner maintains the 101 rejection.
Regarding 35 U.S.C. § 103 rejections. With respect to the prior art rejections, Applicants arguments have been fully considered but are found unpersuasive. Examiner has updated the rejections in light of the most recent claim amendments. With respect to Applicants remarks: “1. The cited art does not teach the claimed wherein the plurality of representative rankings are calculated based further in part on a time since each respective representative of the plurality of representatives handles a similar user-experienced issue... 2. The cited art does not teach the claimed updating a selected representative ranking corresponding to the category of the user-experienced issue based on the user feedback and a length of time to resolve the user-experienced issue... 3. Any modification of Hambridge to teach representative rankings based on tie since representatives handled a similar issue or a length of time to resolve the issue would impermissibly change the principle of operation of Hambridge... “
Examiner respectfully disagrees.
Examiner respectfully notes the limitation in claim 1: “calculating a plurality of representative rankings corresponding to a plurality of representatives based at least in part on a first success rate of the plurality of representatives in resolving issues that are similar to the user-experienced issue and an overall average time to resolve the issues” is taught by a combination of Hambridge and Kaufman. Examiner notes Hambridge teaches it is known to determine the best available candidate (representative) to respond to an issue and to ensure the issue is resolved in a timely and effective manner (See at least Hambridge, para 0008). Hambridge further teaches the on-call management system teaches analyzing and ranking representatives to respond to the issue, including a record of success of the representative in resolving issues (Hambridge, para 0041 and 0052). Kaufman, which also teaches determining the best agent available, is relied on to explicitly teach “average time”. Kaufman teaches time throughout, see at least Figures 3H-3I, and Kaufman, Figure 11a teaches average time spent talking. Further, Examiner respectfully notes using historical metrics to route a call to an ideal agent/representative is known. See at least Hambridge, para 0027, teaches historical information on how the representative (agent) has responded, activity patterns and past patterns of behavior of agent... Various patterns can be determined by capturing data generated by one or more devices... the devices can include an application that monitors such patterns and update the representative profile based on such monitoring. Further, see at least Kaufman, para 0115 and 0117, which also teaches using past or historical metrics and pattern matches to match the ideal allocation (agent). Therefore Applicants remarks are found unpersuasive and Examiner has updated and maintains the 103 rejections for all claims.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/R.R.N./Examiner, Art Unit 3629
/LYNDA JASMIN/Supervisory Patent Examiner, Art Unit 3629