Prosecution Insights
Last updated: April 18, 2026
Application No. 17/801,435

USING HISTORICAL USER ROUTES TO RECOMMEND NAVIGATIONAL ROUTES

Non-Final OA §103
Filed
Aug 13, 2023
Examiner
ESTEVEZ, DAIRON
Art Unit
3656
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Google LLC
OA Round
3 (Non-Final)
67%
Grant Probability
Favorable
3-4
OA Rounds
2y 8m
To Grant
51%
With Interview

Examiner Intelligence

Grants 67% — above average
67%
Career Allow Rate
43 granted / 64 resolved
+15.2% vs TC avg
Minimal -16% lift
Without
With
+-15.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
28 currently pending
Career history
92
Total Applications
across all art units

Statute-Specific Performance

§101
6.0%
-34.0% vs TC avg
§103
54.3%
+14.3% vs TC avg
§102
18.9%
-21.1% vs TC avg
§112
17.9%
-22.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 64 resolved cases

Office Action

§103
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 . DETAILED ACTION Response to Amendment The RCE filed 2/9/26 has been entered. Claims 1-2, 4-8, 12-13 and 15-25 remain pending in the application. This communication is a Non Final Office Action on the on merits. Response to Arguments Applicant argues that Zhang does not disclose or suggest that information about previous vacations and places visited is subject to any type of threshold or specifically on involving a threshold amount of time for communication between users. Similarly, Applicant identifies that Hill and Chen explicitly teach rating and position based thresholds for certain calculations and decision making. In particular, the limitation most in question is one regarding a “threshold amount of time” for which the aforementioned references do not explicitly recite in their respective disclosures. However, Applicant’s arguments are not persuasive in view of the robust planning and social networking system of Zhang. Beginning in P [0079] Zhang describes the use of concepts called “Social Graph Affinity and Coefficient”, wherein communication between users is directly considered. In P [0081] there is explicit consideration of a decay factor for allowing “more recent actions [to be] more relevant when calculating the coefficient”. Although not an explicit recitation of a threshold amount of time, the coefficient of Zhang is directly related to seeking out relevant information to include as part of the recommendation method. 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. Claim(s) 1-2, 4-8, 12-13, and 15-25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al., hereinafter Zhang (Document ID: US 20170046802 A1) in view of Hill (Document ID: US 9710873 B1), and further in view of Chen et al., hereinafter Chen (Document ID: CN111612914A). Regarding claims 1, 12, and 20, Zhang teaches a computer-implemented method for recommending destinations to a user, a computer system, and non-transitory computer-readable media that stores instructions to perform operations, the method, system, and operations comprising: receiving, by a computing system comprising one or more computing devices, data descriptive of a primary user location of a primary user (see at least P [0051]: “the travel-recommendation model may include aggregated user information from the online social network associated with the first user”); Zhang teaches in P [0005]: “the social-networking system may generate travel recommendations for a user that the social-networking system has determined is or will be traveling to a particular geographic location.” In P [0043] the system prompts the user to enter a query or provide other information about their trip destination. But Zhang does not explicitly teach receiving, by the computing system, data descriptive of a primary user input requesting generation of a navigational routing. Instead, Hill, whose invention pertains to providing point of interest item recommendations and/or map information, teaches in Col 5, Line 33: “a map 120 may be provided that displays point of interest item recommendations that are near the user 102 or are at a search location requested by the user 102” It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to have modified the travel recommendation system of Zhang with the user request for travel recommendations of Hill in order to execute a design choice and provide flexibility to a user to receive automatic recommendations or to request recommendations as in Col 3 Line 16 of Hill. In view of the modification, Zhang further teaches receiving, by the computing system, content associated with a plurality of historical user navigational routings previously traversed by one or more secondary users that differ from the primary user, each of the plurality of historical user navigational routings comprising one or more stops in at least P [0005]: “the social-networking system may have access to information relating to each of these users, including, for example… historical information such as previous vacations and places/tourist attractions visited.” Additionally, the info includes “specific locations and/or points of interest in a particular area. Zhang teaches beginning in P [0079] a measure of social affinity between users which represents “the strength of a relationship or level of interest between particular objects associated with the online social network”. P [0080] then makes it clear that “a user's future actions may be predicted based on the user's prior actions”, wherein actions include “sending messages, posting content, or commenting on content”, all of which are types of communication with at least one connected user of a plurality of connected users. Finally, in P [0081] Zhang states “As an example and not by way of limitation, a coefficient may include a decay factor that causes the strength of the signal provided by particular actions to decay with time, such that more recent actions are more relevant when calculating the coefficient”. Hill teaches in Col 3, line 29 the ability to weight ratings based on “ relationships between the users (e.g., based at least in part on social network information)”. But Zhang and Hill do not explicitly teach communication with the primary user within a threshold amount of time. Instead, Zhang’s coefficient that monitors the actions of the first user (primary user) in the context of second users (connected users), includes a direct consideration of recent actions, including communications, in P [0081]. Therefore, it would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to have modified the recent interaction consideration and social network monitoring for recommendations of Zhang and Hill with a threshold of time for communication between users in order to execute a design choice that allows a decay factor to rule out any interactions or actions that are not sufficiently recent. The system of Zhang is intended to be very personalized and based on accumulating the right amount of context data to support a user. Therefore, one of ordinary skill in the art would have found it obvious to limit data to a threshold amount of time to target a specific trip or excursion that a user wishes to plan. In view of the modification, Zhang further teaches determining, by the computing system, a proposed path for the navigational routing based at least in part on a combination of the one or more stops associated with the plurality of historical navigational routings (see at least P [0073]: “the social-networking system 160 may generate a travel itinerary for the first user based on the first geographic location, the one or more second geographic locations (e.g., the points of interest determined based on second user information, as discussed above), and the one or more itinerary constraints associated with the first user.”); and Zhang additionally teaches providing, by the computing system, the proposed path for the navigational routing for display to the primary user in at least P [0074]: “the social-networking system 160 may send, to the client system 130 of the first user, the travel itinerary for display to the first user.” Hill additionally teaches in item 122 of FIG. 1 a route provided to the user, which includes prompts or popup windows overlayed on the environment. But Zhang and Hill do not explicitly teach that the path is provided in an augmented reality interface, wherein the proposed path is overlayed on real-time imagery of surroundings of the primary user. Instead, Chen, whose invention pertains to an augmented reality guided tour system, teaches in at least P [0008] the use of augmented reality technology which “calculates the position and angle of the camera relative to the image in real time, and adds corresponding images, videos and 3D models to simulate and superimpose physical information that is difficult to experience in a certain time and space in the real world, applying virtual information to the real world and making it perceptible to human senses. It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to have modified the user based travel recommendation and planning of Zhang and Hill with the augmented reality for guidance of Chen in order to execute a design choice to combine known mapping and routing technology with augmented reality technology that effectively allows a user interactive access in a large space as in P [0008]-[0010] of Chen. It should be noted that Zhang and Hill are directly related to the destination planning method of the claimed invention, whereas Chen is directed to a specific application for navigation within a museum guided tour system. However, Chen is primarily relied upon to demonstrate the particulars of using augmented reality in a guidance scenario, and it would have been obvious to one of ordinary skill in the art to modify the itinerary planning and display of Zhang and Hill with an augmented reality mode designed by Chen in order to provide convenience and enhance the experience of a user Regarding claim 12 specifically, Zhang additionally teaches one or more processors (see at least P [0096]: “computer system 1400 includes a processor 1402”); and one or more non-transitory, computer-readable media that store instructions that when executed by the one or more processors cause the computing system to perform operations (see at least P [0096]: “memory 1404”) Regarding claims 2 and 13, modified Zhang teaches the computer-implemented method of claim 1 and the computing system of claim 12, and Zhang further teaches receiving, by the computing system, data descriptive of a second primary user input selecting at least one destination (in view of the modification above a “second” input is obtainable from the primary user as seen in P [0043]: “a user may submit a query to the social-networking system 160 by, for example, selecting a query input or inputting text into query field. As shown in FIG. 4, a user interface 400 associated with generating the travel recommendations for the user (e.g., requesting information such as “tell us where you are going”) may include a “destination” search input area 410 (e.g., requesting the user to input “your next destination”) and a “search” button 420.”); determining, by the computing system, one or more additional stops based at least in part on the plurality of historical navigational routings (see at least P [0077] which discloses “updating of the travel itinerary in real time”, including adding or removing stops based at least in part on the historical navigational routings provided by the social network and the user’s travel constraints); and generating, by the computing system, the proposed path based at least in part on a combination of the data descriptive of a user location, the data descriptive of a second primary user input selecting at least one destination, and one or more additional stops (see at least P [0077] wherein a route is generated, and updated in real time, to include point of interest stops, but to also constrain to the user specified destination, i.e “dinner with a friend in Arlington”). Regarding claims 4 and 15, modified Zhang teaches the computer-implemented method of claim 2 and the computing system of claim 13, and Zhang further teaches that generating the proposed path comprises including one or more additional stops based at least in part on a ranking value associated with the plurality of historical navigational routings (see at least P [0060]: “the one or more travel recommendations displayed to the first user may be ranked based on a relationship between the first user and the one or more second users within a social graph 200 of the online social network”). Regarding claims 5 and 16, modified Zhang teaches the computer-implemented method of claim 1 and the computing system of claim 12, and Zhang further teaches that: the plurality of historical user navigational routings are associated with a plurality of connected users, and wherein the plurality of connected users comprises a plurality of connections via a social network or an address book contained in a primary user device associated with the primary user (see at least P [0042] which describes “the social-networking system 160 may gather and analyze location data and social-graph data for users of the social network in order to provide “travel agent” and “travel log”-like functionalities.” See also FIG. 1 which illustrates a network that communicates the client system to the social networking system). Regarding claims 6 and 17, modified Zhang teaches the computer-implemented method of claim 5 and the computing system of claim 16, and Zhang further teaches in P [0071] obtaining, by the computing system, only content associated with the historical user navigational routings associated with at least one connected user selected by the primary user by slicing “only a subset of users” based on travel criteria or friend status. But Zhang, Hill, and Chen do not explicitly teach receiving data, by the computing system, descriptive of a selection by the primary user of at least one connected user out of the plurality of connected users. However, Zhang does teach in P [0028] that the user can set appropriate privacy settings which in P [0092] includes limiting user access and viewership within the social network based on familiarity and personal relationships. Zhang additionally teaches filtering of recommendations based on “only the users who have been to a particular geographic location, or other suitable subset of second users” in P [0056]. Therefore, it would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to have modified the subset of users and selective filtering of user content of Zhang, Hill and Chen with a primary user selection input for how to filter other user data in order to provide only relevant route recommendations based on acquaintances who have been to a particular location, and to use only information that is in accordance with safe privacy practices. Regarding claims 7 and 18, modified Zhang teaches the computer-implemented method of claim 5 and the computing system of claim 16, and Zhang further teaches determining a subset of the plurality of connected users based at least in part on contextual data (see at least P [0056]: “only a subset of users” based on context data such as “ “friend” connections with the first user, only the users who are first or second degree contacts with the first user, only the users who have been to a particular geographic location, or other suitable subset of second users”). Regarding claims 8 and 19, modified Zhang teaches the computer-implemented method of claim 5 and the computing system of claim 16, and Zhang further teaches reviews associated with the plurality of connected users or a number of historical user visits in at least P [0038]: “The social-networking system 160 may also maintain meta information about particular locations, such as… user reviews”. See also P [0042]: “reviews of these points of interest,”. But Zhang, Hill, and Chen do not explicitly teach that one or more stops are associated with a ranking value based at least in part on the reviews. Instead, Zhang teaches in P [0060] that places of interest may be ranked based on the relationship or level of interest between users. Since the secondary users and their info includes the reviews they leave as well, it would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to have modified the review information and ranking of places of interest of Zhang, Hill, and Chen with a ranking based at least in part on the reviews in order to give additional weight to the reviews of closer friends and acquaintances for a stop ranking system. Regarding claims 21, 22, and 25, modified Zhang teaches the one or more non-transitory computer-readable media of claim 20, the computer-implemented method of claim 1, and the computing system of claim 12, but Zhang and Hill do not explicitly teach that the augmented reality interface comprises navigational instructions that are overlayed on the real-time imagery of the surroundings of the primary user. Instead, Chen teaches in at least P [0042] different methods for overlaying augmented reality information on the surroundings, and in P [0048] specifically displaying the navigation route with navigation clues as instructions. It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to have modified the user based travel recommendation and planning of Zhang and Hill with the augmented reality overlay on a user's surroundings of Chen in order to execute a design choice to combine known mapping and routing technology with augmented reality technology that effectively allows a user interactive access in a large space as in P [0008]-[0010] of Chen. Regarding claim 23, modified Zhang teaches the computer-implemented method of claim 22, but Zhang and Hill do not explicitly teach that the navigational instructions comprise an indication of a direction for the user to follow the navigational routing or an overhead map view of the surroundings. Instead, Chen teaches in P [0058]-[0059] the use of numeric directions or other known methods of map navigation logic to receive directions. It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to have modified the user based travel recommendation and planning of Zhang and Hill with the augmented reality navigation guidance of Chen in order to execute a design choice to combine known mapping and routing technology with augmented reality technology that effectively allows a user interactive access in a large space as in P [0008]-[0010] of Chen. Regarding claim 24, modified Zhang teaches the computer-implemented method of claim 22, but Zhang and Hill do not explicitly teach that the navigational instructions comprise instructions to engage with sights that were seen along the proposed path by the one or more secondary users. Instead, Chen teaches in P [0042] numerous types of interactive content, and in P [0043] conditions for proximity that allow a user to receive prompts to interact with and engage in specific sights. They can also see other users interacting in P [0044]. It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to have modified the user based travel recommendation and planning of Zhang and Hill with the augmented reality prompts and interactive features of Chen in order to execute a design choice to combine known mapping and routing technology with augmented reality technology that effectively allows a user interactive access in a large space as in P [0008]-[0010] of Chen Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Document ID: US 20120254186 A1 Invention pertains to rendering categorized location results for user convenience. Document ID: US 9877148 B1 Invention pertains to providing recommendations to users for places they have not visited before. Document ID: US 10115179 B2 Invention pertains to aggregated content for presenting a map interface to users. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Dairon Estevez whose telephone number is (703)756-4552. The examiner can normally be reached M-F 8:00AM - 4:00PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Khoi Tran can be reached at (571) 272-6919. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /D.E./Examiner, Art Unit 3656 /KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656
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Prosecution Timeline

Aug 13, 2023
Application Filed
Jun 06, 2025
Non-Final Rejection — §103
Sep 09, 2025
Applicant Interview (Telephonic)
Sep 09, 2025
Examiner Interview Summary
Sep 10, 2025
Response Filed
Nov 05, 2025
Final Rejection — §103
Feb 09, 2026
Request for Continued Examination
Feb 23, 2026
Response after Non-Final Action
Apr 02, 2026
Non-Final Rejection — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
67%
Grant Probability
51%
With Interview (-15.9%)
2y 8m
Median Time to Grant
High
PTA Risk
Based on 64 resolved cases by this examiner. Grant probability derived from career allow rate.

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