DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice to Applicant
2. The following is a Final Office action. In response to Examiner’s Non-Final Action of 10/02/2025, Applicant, on 01/29/2026, amended Claims 7, 11, 17 and 23; and cancelled Claims 16, 18 and 26. Claims 9, 10, 12-15, 19-22, 24, 25 and 27 are as previously presented.
Claims 8-15, 17, 19-25 and 27 are pending in this application and have been rejected below.
Response to Amendment
3. Applicant’s amendments and arguments are acknowledged.
4. Claim Objection added in light of Applicant's amendments.
5. The prior 35 USC §101 rejection maintained despite Applicant's amendments and arguments.
6. The prior 35 USC §103 rejection withdrawn in light of Applicant's amendments and arguments, and new 35 USC §103 rejection added.
Claim Objections
7. Claim 17 objected to for the following informality: Claim 17 should depend from Claim 8 instead of Claim 16 (which has been cancelled).
Claim Rejections - 35 USC § 101
8. 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.
9. Claims 8-15, 17, 19-25 and 27 rejected under 35 U.S.C. 101 because, although they are drawn to statutory categories of method (process) or system (machine), they are also directed to a judicial exception (an abstract idea) without significantly more.
10. At Step 2A Prong One of the subject matter eligibility analysis, Claim 8 recites A method for generating an .. travel itinerary .., comprising: Generating .. user travel preference data based on user activity data ..; storing .. the user travel preference data; generating .. an initial drivable route based on travel timeframe data, origin location data, and destination location data; retrieving ... the user travel preference data and point of interest data; determining .. at least one recommended stop located along the initial drivable route based on the user travel preference data and the point of interest data, wherein the point of interest data is generated .. apply and update weighting to underlying point of interest data based on an indication of usefulness of the underlying point of interest data; .. receiving .. user feedback input related to the initial drivable route and the at least one recommended stop; generating .. a revision to the at least one recommended stop based on the user feedback input, which, under Broadest Reasonable Interpretation in light of the Specification, is an abstract idea of Certain Methods of Organizing Human Activity, particularly fundamental economic principles or practices (including mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; marketing or sales activities or behaviors; business relations) because generating a travel itinerary and determining a recommended stop located along the route is a business practice involving commercial interactions and marketing or sales activities or behaviors. Furthermore, it is also an abstract idea of Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgment, opinion), because generating a route based on travel timeframe, origin and destination locations is a process that, under Broadest Reasonable Interpretation, can be performed in the mind since it involves evaluation, judgement or observation. Claim 23 recites a similar abstract idea.
At Step 2A Prong Two of the analysis, the judicial exception (abstract idea) is not integrated into a practical application because independent Claims 8 and 23, including additional elements such as interactive, using a travel itinerary platform, using a processor, in a database, from a database at the processor, using a machine learning algorithm, using the processor on a user interface, from the user interface at the processor, a processor in communication with the user interface and the database, on the user interface, individually, and in combination, when viewed as a whole, are not an improvement to a computer or a technology, the claims do not apply the judicial exception with a particular machine, and the claims do not effect a transformation or reduction of a particular article to a different state or thing. Generally linking the use of the judicial exception to a particular technological environment or field of use, as in the instant claims, is not indicative of integration into a practical application - see MPEP 2106.05(h); adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as in the instant claims, is also not indicative of integration into a practical application - see MPEP 2106.05(f). Furthermore, the limitations of displaying, using the processor on a user interface, the initial drivable route and the at least one recommended stop and displaying, using the processor on the user interface, the revision to the at least one recommended stop are insignificant extra-solution activity (see MPEP 2106.05(g)). The Claims are therefore directed to the judicial exception.
At Step 2B of the analysis, independent Claims 8 and 23 do not include any additional elements that are sufficient to amount to significantly more than the judicial exception (abstract idea), because any such additional elements such as those listed above, individually or in combination, do not recite anything that is beyond conventional and routine activity or use of computers (as evidenced by Figures 1, 2 and paragraphs 14-18, 58 of the Specification in the instant Application, and court decisions such as buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) discussed at 2106.05(d) of the MPEP), do not effect a transformation or reduction of a particular article to a different state or thing, nor do they apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular field of use or technological environment. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), or generally linking the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)), as in the instant independent Claims, is not indicative of an inventive concept ("significantly more").
At Step 2A Prong One, dependent Claims 9-15, 17, 19-22, 24, 25 and 27 incorporate (and therefore recite) the abstract idea noted in independent Claims from which they depend, and further recite extensions of that abstract idea.
At Step 2A Prong Two, dependent Claims 9, 10, 12, 13, 15, 17, 19, 20, 22, 24, 25 and 27 do not include any additional elements beyond those included in the list above with respect to the independent Claims from which they depend. These dependent Claims therefore do not integrate the judicial exception (abstract idea) into a practical application for the same reasons as stated above at Step 2A Prong Two for the independent Claims.
At Step 2A Prong Two for dependent Claims 11, 14 and 21 the judicial exception (abstract idea) is not integrated into a practical application because the Claims, including additional elements such as those listed above for the independent Claims and connected device, real time, individually, and in combination, when viewed as a whole, are not an improvement to a computer or a technology, the claims do not apply the judicial exception with a particular machine, and the claims do not effect a transformation or reduction of a particular article to a different state or thing. Generally linking the use of the judicial exception to a particular technological environment or field of use, as in the instant claims, is not indicative of integration into a practical application - see MPEP 2106.05(h); adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as in the instant claims, is also not indicative of integration into a practical application - see MPEP 2106.05(f). These Claims are therefore directed to the judicial exception.
At Step 2B, dependent Claims 9, 10, 12, 13, 15, 17, 19, 20, 22, 24, 25 do not include any additional elements beyond those included in the list above with respect to the independent Claims from which they depend. These dependent Claims therefore do not recite anything that is sufficient to amount to significantly more than the judicial exception for the same reasons as stated above at Step 2B for the independent Claims.
At Step 2B, dependent Claims 11, 14 and 21 do not include any additional elements that are sufficient to amount to significantly more than the judicial exception (abstract idea), because any such additional elements such as those listed above for the independent Claims and connected device, real time, individually or in combination, do not recite anything that is beyond conventional and routine activity or use of computers (as evidenced by Figures 1, 2 and paragraphs 14-18, 58 of the Specification in the instant Application, and court decisions such as buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) discussed at 2106.05(d) of the MPEP), do not effect a transformation or reduction of a particular article to a different state or thing, nor do they apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular field of use or technological environment. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), or generally linking the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)), as in the instant Claims, is not indicative of an inventive concept ("significantly more").
Therefore, Claims 8-15, 17, 19-25 and 27 are rejected under 35 U.S.C. 101 as being directed to non-eligible subject matter. See Alice Corp. v. CLS Bank International, 573__ U.S. 2014.
Claim Rejections - 35 USC § 103
11. The following is a quotation of 35 U.S.C. 103:
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.
35 U.S.C. 103 forms the basis for all obviousness rejections set forth in this Office action.
12. Claims 8-15, 17, 19-25 and 27 rejected under 35 U.S.C. 103 as being unpatentable over Nevrekar et al. (US Patent Publication Number 20160258767 A1 - hereinafter Nevrekar) in view of Valecha et al. (US Patent Publication Number 20190139165 A1 - hereinafter Valecha) in further view of Zhang et al. (US Patent Publication Number 20170046802 A1 - hereinafter Zhang).
13. As per Claim 8, Nevrekar teaches:
A method for generating an interactive travel itinerary using a travel itinerary platform [NEVREKAR reads on: Abstract (searches along a route, change the itinerary on-the-go); Fig. 3 (system 300 is a travel itinerary platform); Fig. 7 (system 700)], comprising: …
generating, using the processor, an initial drivable route based on travel timeframe data, origin location data, and destination location data [NEVREKAR reads on: Figs. 1, 2 (ROUTE GENERATION COMPONENT 102, MAP, ORIGIN, DESTINATION); Fig. 5 (500, 504); Fig. 7 (computing system 700); para 7; para 41; para 78; para 79 (timeframe in which the trip must be completed.)]; …
… determining, using the processor, at least one recommended stop located along the initial drivable route based on the user travel preference data and the point of interest data [NEVREKAR reads on: Fig. 5 (502, 506); Fig. 6 (IDENTIFY ENTITIES-OF-INTEREST ALONG THE ROUTE RELEVANT TO THE USER INTENT 604 is the point of interest data); para 6 (ask users if they want to .. visit some desired location); para 7 (entities identified along the route); para 8 (user intent based on the query is based on the user travel preference data); para 28 (Entities are identified which are conveniently reachable within a certain amount of time along the route is at least one recommended stop located along the initial drivable route based on the user travel preference data)], wherein the point of interest data is generated using a machine learning algorithm [NEVREKAR reads on: para 19 (Cortana can be speech activated, and learns about the user); para 22 (Machine learning algorithms can be utilized to understand the user intent); para 23 (describe an upcoming attraction (entity) using available rich data for local entities)] …
… displaying, using the processor on a user interface, the initial drivable route and the at least one recommended stop [NEVREKAR reads on: Figs. 1, 2 (map user interface 106); Fig. 4 (map interface 400); Fig. 5 (508); Fig. 7 (ONBOARD DISPLAY 740); para 41 (generate a route 104 for presentation on a map user interface 106); para 28, as above];
receiving, from the user interface at the processor, user feedback input related to the initial drivable route and the at least one recommended stop [NEVREKAR reads on: Figs. 1, 2 (QUERY INPUT FIELD); Fig. 6 (user query 600); para 28, as above; para 57 (user selects a point-of-interest along the route 104, sequence of interactions can be useful in defining various types of intent, such as directions intent)];
generating, using the processor, a revision to the at least one recommended stop based on the user feedback input [NEVREKAR reads on: Fig. 6 (UPDATING THE ITINERARY WITH A NEW ENTITY 606)]; and
displaying, using the processor on the user interface, the revision to the at least one recommended stop [NEVREKAR reads on: Fig. 6 (PRESENT THE UPDATED ITINERARY IN A MAP USER INTERFACE 608)].
Although Nevrekar teaches user preferences and history (at paragraphs 29, 30), it does not explicitly teach but Valecha teaches:
… generating, using a processor, user travel preference data based on user activity data associated with prior user engagement with the travel itinerary platform; storing, using the processor in a database, the user travel preference data [Valecha reads on: Fig. 1 (USER DATA 114, PREFERENCE IDENTIFICATION 118, USER PREFERENCE TYPES 120 is user travel preference data based on user activity data associated with prior user engagement with the travel itinerary platform); Fig. 3; para 12 (trip itinerary system is the travel itinerary platform); paras 13, 14 (processing components, storage components), 15 (databases); para 23 (User data 114 may store information on users that interact with trip itinerary system 106; User data 114 may also store the user preferences determined using preference identification 118)]; …
… retrieving, from a database at the processor, the user travel preference data and point of interest data [Valecha reads on: Fig. 1 (trip itinerary system 106, USER DATA 114, PREFERENCE IDENTIFICATION 118, USER PREFERENCE TYPES); Fig. 4 (RETRIEVE A LIST OF TOP ATTRACTIONS/THINGS TO DO FOR LOCATION IN THE QUERY 420 is point of interest data); para 15 (trip itinerary system 106 may be stored in .. relational databases)]; …
At the time of filing, it would have been obvious to a person of ordinary skill in the art to have modified Nevrekar to incorporate the teachings of Valecha in the same field of endeavor of travel itineraries to include generating, using a processor, user travel preference data based on user activity data associated with prior user engagement with the travel itinerary platform; storing, using the processor in a database, the user travel preference data; retrieving, from a database at the processor, the user travel preference data and point of interest data. The motivation for doing this would have been to improve the itinerary generation of Nevrekar by efficiently incorporating user preferences. See Valecha, Abstract, "A method may include analyzing, using at least one processor, a corpus of data to identify a plurality of travel-related user inputs from a user".
Nevrekar in view of Valecha does not explicitly teach but Zhang teaches:
… that is configured to apply and update weighting to underlying point of interest data based on an indication of usefulness of the underlying point of interest data [ZHANG reads on: para 5 (information on points of interest they visited); para 81 (system 160 may use a variety of factors to calculate a coefficient. .. different factors may be weighted differently when calculating the coefficient. The weights for each factor may be static or the weights may change .. system 160 may consider a variety of variables when determining weights for various factors used to calculate a coefficient, such as .. relationship to the object about which information was accessed .. weights may be continuously updated based on continued tracking of the actions upon which the coefficient is based. .. system 160 may determine coefficients using machine-learning algorithms trained on historical actions and past user responses - relationship to the object about which information was accessed is an indication of usefulness of the underlying point of interest data)]; …
At the time of filing, it would have been obvious to a person of ordinary skill in the art to have modified Nevrekar in view of Valecha to incorporate the teachings of Zhang in the same field of endeavor of travel itineraries to include that is configured to apply and update weighting to underlying point of interest data based on an indication of usefulness of the underlying point of interest data. The motivation for doing this would have been to improve the itinerary generation of Nevrekar in view of Valecha by efficiently incorporating user preferences. See Zhang, Figure 12 (Identifying one or more second geographic locations, within a threshold distance from the first geographic location, the one or more second geographic locations being determined based on a travel-recommendation model associated with the first user 1220).
14. As per Claim 9, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 8 [as above]: further comprising
Nevrekar further teaches:
receiving one or more of the travel timeframe data, the origin location data, or the destination location data at the processor from the user interface [NEVREKAR reads on: Figs. 1, 2, ; Fig. 6 (RECEIVE A USER QUERY OF A USER ON A DEVICE FOR DIRECTIONS ALONG A ROUTE DEFINED FROM A GEOGRAPHICAL ORIGIN TO A GEOGRAPHICAL DESTINATION 600)];
wherein generating the initial drivable route [NEVREKAR, as above, Claim 8] comprises generating the initial drivable route based on one or more of the received travel timeframe data, the received origin location data, or the received destination location data [NEVREKAR reads on: Figs. 1, 2, 6, as above].
15. As per Claim 10, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 8 [as above]: further comprising …
… wherein generating the initial drivable route comprises generating the initial drivable route [NEVREKAR, as above, Claim 8] …
Nevrekar does not explicitly teach but Valecha further teaches:
… determining one or more of the travel timeframe data, the origin location data, or the destination location data based on the user travel preference data retrieved from the database [Valecha reads on: Fig. 1, para 15, as above, Claim 8; para 54 (determined location destination in search query 302)]; …
… based on one or more of the determined travel timeframe data, the determined origin location data, or the determined destination location data [Valecha, as above].
At the time of filing, it would have been obvious to a person of ordinary skill in the art to have modified Nevrekar in view of Valecha in view of Zhang to incorporate the further teachings of Valecha in the same field of endeavor of travel itineraries to include determining one or more of the travel timeframe data, the origin location data, or the destination location data based on the user travel preference data retrieved from the database … based on one or more of the determined travel timeframe data, the determined origin location data, or the determined destination location data. The motivation for doing this would have been to improve the itinerary generation of Nevrekar in view of Valecha in view of Zhang by efficiently incorporating user preferences.
16. As per Claim 11, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 8, wherein the user travel preference data [as above] comprises
Nevrekar further teaches:
one or more of direct user input data, user activity data, or connected device data [NEVREKAR reads on: para 81 (itinerary can be input to a typical navigation device)].
17. As per Claim 12, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 11, wherein the direct user input data [as above] comprises
Nevrekar further teaches:
answers received on the user interface in response to travel itinerary questions [NEVREKAR reads on: para 51 (a search for "gas stations" initiated by a query in the query input field, a category entity card 126 is generated and presented that lists some or all gas stations along the route 104)].
18. As per Claim 13, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 11, wherein the user activity data [as above] comprises
Nevrekar further teaches:
one or more of user selection data, user filter data, user saved location data, user visited location data, vehicle data, user rating data, user shared content data, or user generated content sentiment analysis data [NEVREKAR reads on: para 28 (selecting a card identifies the corresponding entity point on the route)].
19. As per Claim 14, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 11, wherein the connected device data [as above] comprises
Nevrekar further teaches:
one or more of real time location data or vehicle status data [NEVREKAR reads on: para 91 (while traveling the route is vehicle status data)].
20. As per Claim 15, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 8, wherein determining the at least one recommended stop [as above] comprises
Nevrekar further teaches:
determining the at least one recommended stop further based on the travel timeframe data, the origin location data, and the destination location data [NEVREKAR reads on: para 28, as above, Claim 8].
21. As per Claim 17, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 16 [as above], further comprising
Nevrekar further teaches:
generating the point of interest data based on one or more of point of interest discoverability data, point of interest fidelity data, point of interest ratings data, point of interest rating count data, or point of interest article data [NEVREKAR reads on: para 25, para 26 (After ranked results are obtained .. building of the itinerary by adding discovered entities ( e.g., businesses, sightseeing, attractions, etc.) to the route)].
22. As per Claim 19, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 8, wherein the at least one recommended stop [as above] comprises
Nevrekar further teaches:
a plurality of recommended stops that are ranked based on the user travel preference data and the initial drivable route [NEVREKAR reads on: para 25 (search along the route. Input parameters include .. user context, .. and/or user query. Algorithms parse a query, derive (understand) user intent .. The search could also include .. parks, and so on is a plurality of recommended stops .. based on the user travel preference data and the initial drivable route); para 26 (After ranked results are obtained .. building of the itinerary by adding discovered entities ( e.g., businesses, sightseeing, attractions, etc.) to the route)].
23. As per Claim 20, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 8, wherein the at least one recommended stop [as above] comprises
Nevrekar further teaches:
one or more of an accommodation stop or a point of interest stop [NEVREKAR reads on: Fig. 5 (IDENTIFY ENTITIES-OF-INTEREST ALONG THE ROUTE RELEVANT TO THE USER INTENT 504)].
24. As per Claim 21, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 8, wherein the user feedback input [as above] comprises
Nevrekar further teaches:
one or more of user input received on the user interface or connected device data [NEVREKAR reads on: Fig. 1, Fig. 2 (QUERY INPUT FIELD, user interface 106); Fig. 5 (RECEIVE A USER QUERY 500)].
25. As per Claim 22, Nevrekar in view of Valecha in view of Zhang teaches:
The method of claim 8 [as above], further comprising:
Nevrekar further teaches:
generating, using the processor, a revision to the initial drivable route based on the user feedback input; and displaying, using the processor on the user interface, the revision to the initial drivable route [NEVREKAR reads on: Fig. 6 (COMPUTE USER INTENT BASED ON THE QUERY AND USER INFORMATION 602, PERFORM A NEW SEARCH FOR NEW ENTITIES DURING TRAVEL ALONG THE ROUTE, AND UPDATING THE ITINERARY WITH A NEW ENTITY 606, PRESENT THE UPDATED ITINERARY IN A MAP USER INTERFACE 608); para 89; para 91 (User reaction to the notification can also be employed to dynamically adjust user intent and ultimately, the itinerary)].
26. As per Claim 23, Nevrekar teaches:
A system for generating an interactive travel itinerary on a travel itinerary platform [NEVREKAR reads on: Abstract, Fig. 3, Fig. 7, as above, Claim 8], comprising:
a user interface [NEVREKAR reads on: Fig. 4, as above, Claim 8];
Although Nevrekar teaches a processor in communication with a user interface (at Figure 7 for example), it does not explicitly teach but Valecha teaches:
a database comprising user travel preference data and point of interest data [Valecha reads on: Fig. 1, para 15, as above, Claim 8; Fig. 4 (RETRIEVE A LIST OF TOP ATTRACTIONS/THINGS TO DO FOR LOCATION IN THE QUERY 420 is point of interest data)];
a processor in communication with the user interface and the database, the processor configured to [Valecha reads on: Fig. 1, para 15, as above, Claim 8; Fig. 6 ; paras 71, 72; para 74 (centralized or distributed database)]:
At the time of filing, it would have been obvious to a person of ordinary skill in the art to have modified Nevrekar to incorporate the teachings of Valecha in the same field of endeavor of travel itineraries to include a database comprising user travel preference data and point of interest data; a processor in communication with the user interface and the database. The motivation for doing this would have been to improve the itinerary generation of Nevrekar by efficiently incorporating user preferences.
The remainder of the Claim rejected under the same rationale as Claim 8 above.
27. As per Claim 24, Nevrekar in view of Valecha in view of Zhang teaches:
The system of claim 23, wherein the processor [as above] is further configured to
The remainder of the Claim rejected under the same rationale as Claim 10 above.
28. As per Claim 25, Nevrekar in view of Valecha in view of Zhang teaches:
The system of claim 23, wherein the processor [as above] is configured to
The remainder of the Claim rejected under the same rationale as Claim 15 above.
29. As per Claim 27, Nevrekar in view of Valecha in view of Zhang teaches:
The system of claim 23, wherein the at least one recommended stop [as above] comprises
The remainder of the Claim rejected under the same rationale as Claim 19 above.
Response to Arguments
30. Applicant's arguments filed 01/29/2026 have been fully considered, but they are found not persuasive with regard to the 35 U.S.C. 101 rejection; with regard to 35 U.S.C. 103, they are moot in view of the new rejections necessitated by the amendments.
31. Applicant argues (at pp. 8-10) that ”the claimed systems and methods have been mischaracterized as "mental processes"” at Step 2A Prong One of the subject matter eligibility analysis, because “the point of interest data is generated using a machine learning algorithm” and the result is displayed on a user interface, which cannot be done in the human mind.
Examiner respectfully disagrees with this analysis. As explained in detail at paragraph 10 above in this office action, the claim language recites an abstract idea (falling under the categories of Mental Processes and Certain Methods of Organizing Human Activity) at Step 2A Prong One of the analysis; at Step 2A Prong Two, the additional elements, including the machine learning algorithm, are merely used as tools to perform the abstract idea (see MPEP 2106.05(f)) or generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)); and displaying the results on a user interface is insignificant extra-solution activity (see MPEP 2106.05(g)). The claims therefore do not integrate the judicial exception into a practical application of the abstract idea, and are thus directed to the judicial exception at Step 2A Prong Two.
32. Applicant further argues (at p. 11) that the amended claim language is not directed to an abstract idea at Step 2A Prong Two of the subject matter eligibility analysis because the claims recite an improved way to generate an interactive travel itinerary and are therefore directed to specific improvements in technology.
Examiner respectfully disagrees. As noted above, the claims recite an abstract idea; the technological aspects are the additional elements, which do not serve to integrate the abstract idea into a practical application at Step 2A Prong Two.
33. With regard to the 35 U.S.C. 103 rejection, Applicant’s arguments are moot in light of the new rejections incorporating the additional reference Zhang.
Conclusion
34. 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 extension fee 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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/SARJIT S BAINS/Examiner, Art Unit 3623 /RUTAO WU/Supervisory Patent Examiner, Art Unit 3623
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