DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1, 8, 11, 14-16, and 19 have been amended.
Claims 1-20 are currently pending and have been examined.
Response to Applicant's Remarks
Double Patenting
Applicant’s remarks, see Page(s) 7, filed 20 July 2026, with respect to the double patenting rejections, have been fully considered and acknowledged. To ensure consistency of the record and compact prosecution, the double patenting rejection will remain in the office action. In view of the claim amendments, new grounds of double patenting rejection has been provided below.
35 U.S.C. § 101
Applicant’s remarks, see Page(s) 7-13, filed 20 July 2026, with respect to the 35 U.S.C. § 101 rejections, have been fully considered, but are not persuasive.
Applicant submits that the claims as a whole reflect an improvement to the functioning of a workspace reservation system and to the machine learning model itself, and therefore, are directed to significantly more than an abstract idea.
Examiner respectfully disagrees, as the claim limitations are not indicative of integration into a practical application, such as an improvement to the functioning of a computer or other technical field, as considered below in view of MPEP 2106. In particular, an improvement in the judicial exception itself (i.e., optimizing reservation recommendations) is not an improvement in technology. Applicant’s improvement in this case is not an improvement to the functioning of a computer, or to any other technology or technological field.
The following are examples of eligible subject matter based on technological improvements: see, e.g., McRO, 837 F.3d at 1315 ("The claimed process uses a combined order of specific rules that renders information into a specific format that is then used and applied to create desired results: a sequence of synchronized, animated characters."); Finjan, Inc. v. Blue Coat Sys., Inc., 879 F.3d 1299, 1304 (Fed. Cir. 2018) (finding patent eligible a claim drawn to a behavior-based virus scan that protects against viruses that have been "cosmetically modified to avoid detection by code-matching virus scans"); Enfish, 822 F.3d at 1330, 1333 (discussing patent eligible claims directed to "an innovative logical model for a computer database" that included a self-referential table allowing for greater flexibility in configuring databases, faster searching, and more effective storage); CardioNet, LLC v. InfoBionic, Inc., 955 F.3d 1358, 1368 (Fed. Cir. 2020) (explaining that the claims at issue focus on a specific means for improving cardiac monitoring technology; they are not "directed to a result or effect that itself is the abstract idea and merely invoke generic processes and machinery" (quoting McRO, 837 F.3d at 1314)).
In contrast, the claims of the current application are similar to gathering and analyzing information using conventional techniques and displaying the result (TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48), wherein the courts have indicated not to be sufficient to show an improvement to technology.
To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology (see MPEP 2106.05(a)).
Instead, the additional elements are recited at a high-level of generality such that in conjunction with the abstract limitations, they amount to no more than:
mere instructions to apply the exception using generic computer components (i.e., generic computer components performing generic computer functions). In their broadest reasonable interpretation, the additional element(s) comprise(s) only a processor, instructions in memory, a display, a receiver, and a transmitter, being used to implement the functions of the abstract idea. Accordingly, the claims do not amount to more than a recitation of the words "apply it" (or an equivalent) or more than mere instructions to implement an abstract idea or other exception in a generic computing environment (see MPEP 2106.05(f) Mere Instructions to Apply an Exception).
generally linking the use of the judicial exception to a particular technological environment or field of use.
Additionally, in regards to the additional elements, ‘a machine learning model’ and ‘updating the machine learning model…’, see Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025). In that case, similar to here, “[t]he requirements that the machine learning model be ‘iteratively trained’ or dynamically adjusted in the Machine Learning Training patents do not represent a technological improvement” because “[i|terative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning.” Id. at 1212.
Thus, even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim(s) is/are directed to the judicial exception.
Applicant further submits that the claims provide a specific practical application analogous to that found eligible in Example 37 of the 2019 Revised Patent Subject Matter Eligibility Guidance.
Examiner respectfully disagrees, as the claim limitations of the present application are not similar to those found to be patent eligible under 35 U.S.C. § 101 in Example 37 of the USPTO Subject Matter Eligibility Examples. Specifically, the claims of Example 37 recite the combination of additional elements of receiving, via a GUI, a user selection to organize each icon based on the amount of use of each icon, a processor for performing the determining step, and automatically moving the most used icons to a position on the GUI closest to the start icon of the computer system based on the determined amount of use. The additional elements recite a specific manner of automatically displaying icons to the user based on usage which provides a specific improvement over prior systems, resulting in an improved user interface for electronic devices.
In contrast, the presented claims determine preferences based on feedback and provide a workspace recommendation in a GUI, this is similar to gathering and analyzing information using conventional techniques and displaying the result (TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48), wherein the courts have indicated not to be sufficient to show an improvement to technology.
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 16, 18, and 19 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 16 and 17 of U.S. Patent No. 12,361,337. Although the claims at issue are not identical, they are not patentably distinct from each other.
Claim 16 is anticipated by claim 16 of U.S. Patent No. 12,361,337.
Claim 18 is anticipated by claim 17 of U.S. Patent No. 12,361,337.
Claim 19 is anticipated by claim 16 of U.S. Patent No. 12,361,337.
Claim 16 of App. No. 19/240,627
Claim 16 of U.S. Patent No. 12,361,337
A system, comprising: one or more memories; and one or more processors configured to execute instructions stored in the one or more memories to:
(The apparatus of claim 15)
An apparatus, comprising:
a memory; and
a processor configured to execute instructions stored in the memory to:
predict, by the processor based on previous workspace reservation requests, that a user of a software platform will initiate a workspace reservation process at a first time;
determine, by a machine learning model processing records of communications facilitated over one or more communication software services of a software platform, learned personnel preferences of a user of a workspace reservation system,
determine learned personnel preferences of the user using a first machine learning model trained based on records of multi-user communications facilitated over one or more communication modalities by software of the software platform and accessed from within a first data store of the software platform to identify a relationship pattern for the user using one or more of the records of the multi-user communications,
wherein the learned personnel preferences include a whitelist of nearby persons and a blacklist nearby persons;
wherein the learned personnel preferences include a whitelist of persons the user wants to be near during workspace reservations and a blacklist of persons the user does not want to be near during workspace reservations that are generated and updated based on records of past workspace reservations;
determine, by the machine learning model processing records of past workspace reservations by the user, learned workspace preferences of the user;
determine learned workspace preferences of the user using a second machine learning model trained based on the records of past workspace reservations and workspace configurations accessed from within a second data store of the software platform to identify a workspace preference pattern for the user using one or more of the records of the past workspace reservations and the workspace configurations;
determine scores for each of multiple candidate workspaces identified for the user from amongst available workspaces at a premises based on weights representing numerical values defined according to rankings of relationships determined based on the learned personnel preferences and the learned workspace preferences;
determine a recommended workspace for the user as a candidate workspace of the multiple candidate workspaces corresponding to a highest one of the scores;
transmit, for display within a graphical user interface rendered at a device of the user, an indication of a recommended workspace determined for the user based on the learned personnel preferences and the learned workspace preferences;
transmit data that, when processed at a reservation device, is configured to cause a display of an indication of the recommended workspace within a graphical user interface output at the reservation device prior to the first time;
receive, from the device of the user via the graphical user interface, direct feedback and indirect feedback associated with the learned personnel preferences and the learned workspace preferences, wherein the direct feedback indicates one or more names to add to or remove from one of the whitelist of nearby persons or the blacklist of nearby persons;
receive direct and indirect feedback from the user about the learned workspace preferences and the learned personnel preferences, wherein the direct feedback includes names to add or remove from the blacklist and the whitelist;
update one or more of the weights based on a selection, by the user, of a workspace indicated within the graphical user interface;
update the learned workspace preferences based on the feedback from the user and based on feedback from multiple users across multiple reservation sessions.
update the machine learning model based on the direct feedback and the indirect feedback
wherein the processor is configured to execute the instructions to:
update one or both of the first machine learning model or the second machine learning model based on a selection by the user of the recommended workspace via the graphical user interface.
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.
Claim(s) 1-20 is/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.
Claim(s) 1, 11, and 16 recite(s) a system and series of steps for determining and recommending a workspace based on user data, which under broadest reasonable interpretation, is analogous to concepts performed in the human mind, such as observation, evaluation, judgment, opinion. These concepts are grouped as mental processes.
The limitation(s) of, ‘determining… learned personnel preferences of a user’; ‘determining… learned workspace preferences of the user’; ‘receiving… direct feedback and indirect feedback associated with the learned personnel preferences and the learned workspace preferences’, as drafted, recite a process that, under broadest reasonable interpretation, is/are mental processes. Accordingly, the claim(s) recite(s) an abstract idea.
The judicial exception is not integrated into a practical application. In particular, the claim(s) recite(s) the additional element(s) of ‘a machine learning model’, ‘updating the machine learning model…’, ‘one or more communication software services of a software platform’, ‘transmitting, for display within a graphical user interface rendered at a device of the user…’, ‘a non-transitory computer readable medium’, ‘one or more processors’, ‘one or more memories’. These additional elements are recited at a high-level of generality such that in conjunction with the abstract limitations, they amount to no more than:
mere instructions to apply the exception using generic computer components (i.e., generic computer components performing generic computer functions) (‘transmitting, for display within a graphical user interface rendered at a device of the user…’, ‘a non-transitory computer readable medium’, ‘one or more processors’, ‘one or more memories’). In their broadest reasonable interpretation, the additional element(s) comprise(s) only a processor, instructions in memory, a display, a receiver, and a transmitter, being used to implement the functions of the abstract idea. Accordingly, the claims do not amount to more than a recitation of the words "apply it" (or an equivalent) or more than mere instructions to implement an abstract idea or other exception in a generic computing environment (see MPEP 2106.05(f) Mere Instructions to Apply an Exception).
generally linking the use of the judicial exception to a particular technological environment or field of use (‘a machine learning model’, ‘updating the machine learning model…’, ‘one or more communication software services of a software platform’).
Additionally, in regards to the additional elements, ‘a machine learning model’ and ‘updating the machine learning model…’, see Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025). In that case, similar to here, “[t]he requirements that the machine learning model be ‘iteratively trained’ or dynamically adjusted in the Machine Learning Training patents do not represent a technological improvement” because “[i|terative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning.” Id. at 1212.
Thus, even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim(s) is/are directed to the judicial exception.
Claim(s) 2-10, 12-15, and 17-20 further recite(s) the system and series of steps for determining and recommending a workspace based on user data, which under broadest reasonable interpretation, is analogous to concepts performed in the human mind, such as observation, evaluation, judgment, opinion. These concepts are grouped as mental processes. Accordingly, the claim(s) recite(s) an abstract idea.
The judicial exception is not integrated into a practical application. In particular, the claim(s) recite(s) the additional element(s) of ‘one or more graphical user interfaces’, ‘a graphical user interface’, ‘a first machine learning model’, ‘a second machine learning model’, ‘a unified communications as a service (UCaaS) platform’. These additional elements are recited at a high-level of generality such that in conjunction with the abstract limitations, they amount to no more than:
mere instructions to apply the exception using generic computer components (i.e., generic computer components performing generic computer functions) (‘one or more graphical user interfaces’, ‘a graphical user interface’). In their broadest reasonable interpretation, the additional element(s) comprise(s) only a processor, instructions in memory, a display, a receiver, and a transmitter, being used to implement the functions of the abstract idea. Accordingly, the claims do not amount to more than a recitation of the words "apply it" (or an equivalent) or more than mere instructions to implement an abstract idea or other exception in a generic computing environment (see MPEP 2106.05(f) Mere Instructions to Apply an Exception).
generally linking the use of the judicial exception to a particular technological environment or field of use (‘a first machine learning model’, ‘a second machine learning model’, ‘a unified communications as a service (UCaaS) platform’).
Additionally, in regards to the additional elements, ‘a first machine learning model’ and ‘a second machine learning model’, see Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025). In that case, similar to here, “[t]he requirements that the machine learning model be ‘iteratively trained’ or dynamically adjusted in the Machine Learning Training patents do not represent a technological improvement” because “[i|terative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning.” Id. at 1212.
Thus, even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim(s) is/are directed to the judicial exception.
Furthermore, the claims recite(s) the additional elements of receiving and transmitting data over a network. These limitations are recited at a high level of generality (i.e., as a general means of receiving and transmitting data), and amount to mere data transmission, which is a form of insignificant extra-solution activity. Thus, the claim(s) is/are directed to the abstract idea.
As discussed above, the additional elements amount to mere data transmission, which is a form of insignificant extra-solution activity. As detailed in MPEP 2106, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the reception and transmission of data was considered to be extra-solution activity in Step 2A, and thus it is re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field.
The generic functions of receiving and transmitting data are considered to be well‐understood, routine, and conventional elements previously known to the industry, because the functions can be summarized as the generic computer functions of receiving or transmitting data over a network. This is similar to how ‘using the Internet to gather data’ was found to be a well-known, routine, and conventional function in the decision of Intellectual Ventures I LLC v. Symantec Corp. (Fed. Cir. 2015) (see MPEP 2106.05(d)(II) Elements That the Courts Have Recognized as Well-Understood, Routine, Conventional Activity in Particular Fields). Thus, these elements amount to well‐understood, routine, and conventional elements previously known to the industry, which does not add significantly more, and therefore remains insignificant extra-solution activity even upon reconsideration. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept, and therefore, the claim(s) is/are not eligible.
As analyzed above, the limitations as an ordered combination, are merely applying the abstract idea in a generic computing environment. In addition, the claims do not improve functionality of a computer or improve any other technology. Thus, claims 1-20 are ineligible as the claims do not recite additional elements which result in significantly more than the abstract idea itself.
Novelty/Non-Obviousness
The subject matter of claims 1-20 is not taught by the cited prior art and is considered novel. However, claims 1-20 remain rejected under 35 U.S.C. 101 as described above.
The closest prior art of record are Yeluguri (U.S. Pre-Grant Pub. No. 20210065069), Vashisht (U.S. Pre-Grant Pub. No. 20220053036), Cheng (U.S. Pre-Grant Pub. No. 20020188489), Daher (U.S. Pre-Grant Pub. No. 20170255880), Franc De Ferriere (U.S. Pre-Grant Pub. No. 20230049989), Löffler (U.S. Pre-Grant Pub. No. 20180308029), Just (U.S. Pre-Grant Pub. No. 20200302344), Decamp (U.S. Pre-Grant Pub. No. 20200218324), O’Keefe-Sally (U.S. Pre-Grant Pub. No. 20190228348), and Sood (“Spacematch: Using Environmental Preferences to Match Occupants to Suitable Activity-Based Workspaces”, 2020).
The cited prior art, taken either individually or in combination with other prior art of record, fails to teach or suggest wherein the learned personnel preferences include a whitelist of nearby persons and a blacklist of nearby persons and receiving, from the device of the user via the graphical user interface, direct feedback and indirect feedback associated with the learned personnel preferences and the learned workspace preferences, wherein the direct feedback indicates one or more names to add to or remove from one of the whitelist of nearby persons or the blacklist of nearby persons.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Wayne S Murray whose telephone number is (571)272-4306. The examiner can normally be reached M-F 8am-5pm ET.
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/Wayne S. Murray/Examiner, Art Unit 3628
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