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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on October 16, 2025 has been entered.
Status of the Claims
Claims 1-20 were previously pending. Claims 1, 3, 9, 11-12, 18, and 20 were amended in the reply filed October 16, 2025. Claims 1-20 are currently pending.
Response to Arguments
Applicant's arguments filed with respect to the rejection made under § 101 have been fully considered but they are not persuasive. Applicant argues that the newly recited marker is not routine or conventional and also that it integrates the abstract idea into a practical application. Remarks, 8-9. However, the broadest reasonable interpretation of the marker includes abstract indications of how the travel planning process should be conducted (i.e., it is part of the abstract idea). "Examiners evaluate integration into a practical application by: (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application…" MPEP 2106.04(d) II. (emphasis added). An inventive concept "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself." Genetic Techs. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016). See also Alice Corp., 134 S. Ct. at 2355, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 78, 101 USPQ2d at 1968 (after determining that a claim is directed to a judicial exception, "we then ask, '[w]hat else is there in the claims before us?") (emphasis added)). Instead, an inventive concept is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception itself. Alice Corp., 134 S. Ct. at 2355, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966). Accordingly, the rejection is maintained.
Applicant's arguments filed with respect to the rejections made under § 103 have been fully considered but are not persuasive. Applicant argues that the references do not disclose the newly recited marker. Remarks, 10. However, Applicant does not offer a preferred construction of this broad term that would distinguish it from the prior art. With respect to Reis, it reads on both of the disclosed constraint labels (see ¶ 0035) and accommodation rankings (see ¶ 0043) that coordinate the booking process. Accordingly, the rejections are maintained.
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 non-statutory subject matter (abstract idea without significantly more). Claims are eligible for patent protection under § 101 if they are in one of the four statutory categories and not directed to a judicial exception to patentability. Alice Corp. v. CLS Bank Int'l, 573 U.S. 208 (2014). Claims 1-20, each considered as a whole and as an ordered combination, are directed to a judicial exception (i.e., an abstract idea) without significantly more.
MPEP 2106 Step 2A – Prong 1:
The claims recite an abstract idea reflected in the representative functions of the independent claims—including:
With respect to claims 1 & 11:
receiving a user input associated with a product offered;
retrieving at least one attribute of the product;
determining, using a first model of a plurality of models, a user intent associated with the user input;
generating, based on the at least one attribute and the user intent, a first response to the user input, wherein the first response includes a marker associated with a travel planning workflow;
triggering, based on the marker of the first response, the travel planning workflow; and
providing the first response to the user input.
With respect to claim 20:
receiving a user input associated with a product offered, wherein the user input includes a text input, the product includes at least one of a lodging, a means of transportation, and a destination activity;
retrieving at least one attribute of the product;
selecting a first model of a plurality of models based on the at least one attribute of the product;
determining, using the first model, a user intent associated with the user input;
generating, based on the at least one attribute and the user intent, a first response to the user input, wherein the first response includes a marker associated with a travel planning workflow;
triggering, based on the marker of the first response, the travel planning workflow; and
providing the first response to the user input.
These limitations taken together qualify as a method of organizing human activities because they recite collecting, analyzing, and outputting information for the planning travel behaviors of people and structuring the related transactional/commercial relationships with travel product service providers (i.e., in the terminology of the 2019 Revised Guidance, commercial interactions (including marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities). Additionally, it recites mental processes (e.g., a travel agent observing user input and products, evaluating them to determine a user intent, and arriving at a judgment on a response).
It shares similarities with other abstract ideas held to be non-statutory by the courts (see Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363 (Fed. Cir. 2015)—tailoring sales information presented to a user based on, e.g., user data or time data, similar because at another level of abstraction the claims could be characterized as tailoring travel product response information presented to a user based on, e.g., user input data or product offering data; Smart Sys. Innovations v. Chicago Transit Authority, 873 F.3d 1364 (Fed. Cir. 2017)—formation of financial transactions in a particular field (i.e., mass transit) and data collection related to such transactions, similar because at another level of abstraction the claims could be characterized as formation of booking transactions in a particular field (i.e., travel products) and data collection related to such transactions).
These cases describe significantly similar aspects of the claimed invention, albeit at another level of abstraction. See Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1240-41 (Fed. Cir. 2016) ("An abstract idea can generally be described at different levels of abstraction. As the Board has done, the claimed abstract idea could be described as generating menus on a computer, or generating a second menu from a first menu and sending the second menu to another location. It could be described in other ways, including, as indicated in the specification, taking orders from restaurant customers on a computer.").
MPEP 2106 Step 2A – Prong 2:
This judicial exception is not integrated into a practical application because there are no meaningful limitations that transform the exception into a patent eligible application. The elements merely serve to provide a general link to a technological environment (e.g., computers and the Internet) in which to carry out the judicial exception (conversational user interface (UI), booking application that includes a travel booking application and is associated with a database, machine learning including a large language model (LLM) wherein the one or more ML models are dynamically selected from the plurality of ML models based on an availability of resources of the one or more ML models, processor, memory, non-transitory computer-readable storage medium—all recited at a high level of generality).
To elaborate, the limitation that the one or more ML models are dynamically selected from the plurality of ML models based on an availability of resources of the one or more ML models is considered generic because there are no technical specifics as to what the ML model is or how it operates, and choosing one based on an availability of resources would be equally applicable in any conceivable processing environment or with any type of data. Materially with respect to the Alice inquiry, it is not significantly different from, e.g., selecting a larger memory when more data storage is needed. Thus, it is still merely being used as a generic computing tool and only serves to set forth a general link to a particular technological environment. "[T]he only thing the claims disclose about the use of machine learning is that machine learning is used in a new environment." Recentive Analytics, inc. v. Fox. Corp., Fed Cir. No. 2023-2437 (Apr. 18, 2025), slip op. at 13. "The requirements that the machine learning model be 'iteratively trained' or dynamically adjusted in the Machine Learning Training patents do not represent a technological improvement." Id. at 12 (emphasis added).
Although these elements have and execute instructions to perform the abstract idea itself (e.g., modules, program code, etc. to automate the abstract idea), this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." Aside from such instructions to implement the abstract idea, they are solely used for generic computer operations (e.g., receiving, storing, retrieving, transmitting data), employing the computer as a tool. See FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1096 (Fed. Cir. 2016) ("[T]he use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent-eligible subject matter.") (citing DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245,1256 (Fed. Cir. 2014)) (emphasis added).
The claims only manipulate abstract data elements into another form. They do not set forth improvements to another technological field or the functioning of the computer itself and instead use computer elements as tools to improve the functioning of the abstract idea identified above. Looking at the additional limitations and abstract idea as an ordered combination and as a whole 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. Rather than any meaningful limits, their collective functions merely provide generic computer implementation of the abstract idea identified in Prong One. None of the additional elements recited "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Alice Corp., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
At the levels of abstraction described above, the claims do not readily lend themselves to a finding that they are directed to a nonabstract idea. Therefore, the analysis proceeds to step 2B. See BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1349 (Fed. Cir. 2016) ("The Enfish claims, understood in light of their specific limitations, were unambiguously directed to an improvement in computer capabilities. Here, in contrast, the claims and their specific limitations do not readily lend themselves to a step-one finding that they are directed to a nonabstract idea. We therefore defer our consideration of the specific claim limitations’ narrowing effect for step two.") (citations omitted).
MPEP 2106 Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the same reasons as presented in Step 2A Prong 2 (i.e., they amount to nothing more than a general link to a particular technological environment and instructions to apply it there). Moreover, the additional elements recited are known and conventional computing elements (conversational user interface (UI), booking application that includes a travel booking application and is associated with a database, machine learning including a large language model (LLM) wherein the one or more ML models are dynamically selected from the plurality of ML models based on an availability of resources of the one or more ML models, processor, memory, non-transitory computer-readable storage medium—see Specification ¶¶ 0027, 41-42, 60, 81, 92, 97, 108 describing these at a high level of generality and in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy the statutory disclosure requirements).
The Federal Circuit has recognized that "an invocation of already-available computers that are not themselves plausibly asserted to be an advance, for use in carrying out improved mathematical calculations, amounts to a recitation of what is 'well-understood, routine, [and] conventional.'" SAP Am., Inc. v. InvestPic, LLC, 890 F.3d 1016, 1023 (Fed. Cir. 2018) (alteration in original) (citing Mayo v. Prometheus, 566 U.S. 66, 73 (2012)). Apart from the instructions to implement the abstract idea, they only serve to perform well-understood functions (e.g., receiving, storing, retrieving, transmitting data—see Specification above as well as Alice Corp.; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016); and Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) covering the well-known nature of these basic computer functions).
"The use and arrangement of conventional and generic computer components recited in the claims—such as a database, user terminal, and server— do not transform the claim, as a whole, into 'significantly more' than a claim to the abstract idea itself. We have repeatedly held that such invocations of computers and networks that are not even arguably inventive are insufficient to pass the test of an inventive concept in the application of an abstract idea." Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1056 (Fed. Cir. 2017) (citations and quotation marks omitted). 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.
Dependent Claims Step 2A:
The limitations of the dependent claims but for those addressed below merely set forth further refinements of the abstract idea without changing the analysis already presented (i.e., they merely narrow the abstract idea without adding any new additional elements beyond it). Additionally, for the same reasons as above, the limitations fail to integrate the abstract idea into a practical application because they use the same general technological environment and instructions to implement the abstract idea as the independent claims.
Dependent Claims Step 2B:
The dependent claims merely use the same general technological environment and instructions to implement the abstract idea. They do not add any new additional elements to be analyzed here. Accordingly, they are not directed to significantly more than the exception itself, and are not eligible subject matter under § 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 5-6, 8-11, 14-15, and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Reis, et al., U.S. Pat. Pub. No. 2021/0248696 (Reference A of the PTO-892 part of paper no. 20241120) in view of Delahaye, et al., U.S. Pat. Pub. No. 2024/0185144 (Reference A of the PTO-892 part of paper no. 20250714).
As per claim 1, Reis teaches a computer-implemented method for travel planning, comprising:
receiving, via a conversational user interface (UI), a user input associated with a product offered by a booking application (¶ 0024);
retrieving, from a database associated with the booking application, at least one attribute of the product (¶ 0038);
determining, using one or more machine learning (ML) models of a plurality of ML models, a user intent associated with the user input (¶¶ 0024, 48);
generating, based on the at least one attribute and the user intent, a first response to the user input (¶¶ 0046-48), wherein the first response includes a marker associated with a travel planning workflow integrated into the conversational UI (¶¶ 0034-35, 43);
triggering, based on the marker of the first response, the travel planning workflow (¶¶ 0035, 43); and
providing, via the conversational UI, the first response to the user input (¶ 0049).
Reis does not explicitly teach the one or more ML models are dynamically selected from the plurality of ML models based on an availability of resources of the one or more ML models; which is taught by Delahaye (¶¶ 0051, 67-69). It would have been prima facie obvious to incorporate this element for the same reason it is useful in Delahaye—namely, because certain models may be more appropriate under different circumstances (e.g., computational resources or available training data). Moreover, this is merely a combination of old elements in the art of travel planning. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claim 2, Reis in view of Delahaye teaches claim 1 as above. Reis further teaches the product includes at least one of a lodging, a means of transportation, and a destination activity (Figs. 3A-3B); and the booking application includes a travel booking application (¶ 0017).
As per claim 5, Reis in view of Delahaye teaches claim 1 as above. Reis further teaches determining the user intent associated with the user input includes: selecting the one or more ML models of the plurality of ML models based on the at least one attribute of the product (¶ 0048).
As per claim 6, Reis in view of Delahaye teaches claim 1 as above. Reis further teaches generating the first response to the user input includes: generating an instruction for the one or more ML models of the plurality of ML models, the instruction causing the one or more ML models to output the first response to the user input based on a policy governing a structure and a content of the first response, and the instruction causing the one or more ML models to include, in the first response, metadata associated with the user input (¶ 0048; see also ¶ 0024 & Figs. 3A-3B, as well as Specification ¶ 0071 defining metadata as including, e.g., the language of the input/output).
As per claim 8, Reis in view of Delahaye teaches claim 6 as above. Reis further teaches providing the first response to the user input includes: extracting the metadata from the first response (¶¶ 0034, 51); and storing the metadata in the database associated with the booking application (¶ 0051).
As per claim 9, Reis in view of Delahaye teaches claim 1 as above. Reis further teaches determining the first response to the user input includes a marker indicating the user intent (¶¶ 0034-35); determining, based on the marker, a second response to the user input (¶¶ 0046-48, 52); and providing, via the conversational UI, the second response (¶¶ 0049, 52).
As per claim 10, Reis in view of Delahaye teaches claim 1 as above. Reis further teaches initiating, via the conversational UI, a booking of the product, wherein the user intent includes an intent to book the product (¶ 0054).
As per claims 11, 14-15, and 17-19, Reis in view of Delahaye teaches a system, comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors, cause the system to perform operations including: the steps of analogous claims 1, 5-6, and 8-10 (¶ 0057, see also citations above).
Claims 3, 7, 12, 16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Reis, et al., in view of Delahaye, et al. as applied to claims 1, 6, 11, and 15 above, further in view of Jouve, et al., U.S. Pat. Pub. No. 2025/0104169 (Reference B of the PTO-892 part of paper no. 20241120).
As per claim 3, Reis in view of Delahaye teaches claim 1 as above. Reis further teaches the user input includes a text input (¶ 0024). Reis does not explicitly teach one or more ML models includes one or more large language models (LLMs); which is taught by Jouve (¶ 0073). It would have been prima facie obvious to incorporate this element for the same reason it is useful in Jouve—namely, to supplement that model's ability to provide natural language interactions. Moreover, this is merely a combination of old elements in the art of travel planning. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claims 7 and 16, Reis in view of Delahaye teaches claims 6 and 15 as above. Reis does not explicitly teach the one or more ML models include the one or more large language models (LLMs); which is taught by Jouve (¶ 0073) and would have been obvious to incorporate for the same reasons as in claim 3 above.
As per claim 12, Reis in view of Delahaye teaches claim 11 as above. Reis further teaches the user input includes a text input (¶ 0024); the product includes at least one of a lodging, a means of transportation, and a destination activity (Figs. 3A-3B); the booking application includes a travel booking application (¶ 0017). Reis does not explicitly teach the first ML model includes a large language model (LLM); which is taught by Jouve (¶ 0073) and would have been obvious to incorporate for the same reasons as in claim 3 above.
As per claim 20, Reis in view of Delahaye and Jouve teaches a non-transitory computer-readable storage medium storing instructions encoded thereon that, when executed by a processor, cause the processor to perform operations comprising: the steps of analogous claims 1-3 and 5 (Reis ¶ 0055, see also citations and obviousness rationale above).
Claims 4 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Reis, et al., in view of Delahaye, et al. as applied to claims 1 and 11 above, further in view of Fleischman, et al., U.S. Pat. No. 10,956,995 (Reference C of the PTO-892 part of paper no. 20241120).
As per claims 4 and 13, Reis in view of Delahaye teaches claims 1 and 11 as above. Reis does not explicitly teach determining the user input includes personally identifiable information (PII); and redacting the PII from the user input; which is taught by Fleischman (col. 8, lines 56-61). It would have been prima facie obvious to incorporate this element for the same reason it is useful in Fleischman—namely, to enhance user privacy. Moreover, this is merely a combination of old elements in the art of travel planning. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL VETTER whose telephone number is (571)270-1366. The examiner can normally be reached M-F 9:00-6:00.
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/DANIEL VETTER/Primary Examiner, Art Unit 3628