DETAILED ACTION
The following is a FINAL office action upon examination of the application number 18/881123.
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 .
Response to Amendment
Claim 1 has been amended.
Claim 8 is new.
Claims 1-8 are pending in the application and have been examined on the merits discussed below.
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 1-8 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.
(Step 1) Claims 1-8 are directed to a device comprising processing circuitry, and therefore, is directed to a machine which is a statutory category of invention. Claim 8 is directed to a method; thus these claims are directed to a process, which is one of the statutory categories of invention.
(Step 2A – prong 1) The claims recite an abstract idea instructing how to estimate a stay POI, which is described by claim limitations reciting:
periodically acquire, … contact information indicating contact with one or more other… users, and store the acquired information as part of user information of the user;
…estimate a stay POI that is a POI in which a user stays in an unassociated stay that is a stay not associated with the POI, among stays comprised in the user information that is a chronological history of a stay during movement of each user,
a part of which is associated with the POI in which the user stays, and adjacency of each user to other users, on the basis of the user information,
…perform a simulation assuming that the user moves via a POI candidate that is a candidate of the stay POI for each user, and estimate the stay POI from the POI candidate, on the basis of a chronological match between adjacency between users extracted in the simulation and adjacency comprised in the user information, and
chronologically match the … contact information ... and a contact timing in the simulation via the POI candidate.
The identified limitations in the claims describing estimating a stay POI (i.e., the abstract idea) fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, which covers marketing activities. Dependent claims 2, 3, 4, 5, 6, and 7 recite limitations that further narrow the abstract idea; therefore, these claims are also found to recite an abstract idea.
(Step 2A – prong 2) This judicial exception is not integrated into a practical application because additional elements such as the processing circuitry in claim 1 does not add a meaningful limitation to the abstract idea since these elements are only broadly applied to the abstract ideas at a high level of generality; thus, none of recited hardware offers a meaningful limitation beyond generally linking the abstract idea to a particular technological environment, in this case, implementation via a processor/computer.
Additional elements such as acquire, from a mobile terminal of a user, Bluetooth Low Energy (BLE) contact information indicating contact with one or more other mobile terminals of other users… and BLE contact information acquired from the mobile terminal do not yield an improvement in the functioning of the computer itself, nor do they yield improvements to a technical field or technology; further these additional elements only add insignificant extra-solution activity (data gathering). Accordingly, these additional element do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
(Step 2B) The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to integration of the abstract idea into a practical application, the hardware additional elements amount to no more than mere instructions to apply the exception using a generic computer component (see Spec. [0090][0099]). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Additional elements such as acquire, from a mobile terminal of a user, Bluetooth Low Energy (BLE) contact information indicating contact with one or more other mobile terminals of other users… and BLE contact information acquired from the mobile terminal do not yield an improvement in the functioning of the computer itself, nor do they yield improvements to a technical field or technology; further these additional elements only add insignificant extra-solution activity (data gathering). With respect to data gathering limitations, the courts have recognized the use of computers to receive and transmit data as a well-understood, routine, and conventional, TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network). In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology.
Claim Rejections - 35 USC § 103
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) 1-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Exploiting bi-directional global transition patterns and personal preferences for missing POI category identification (Xi); in view of US 2022/0201432 (Kawaguchi); in view of US 2021/0400428 (Loh).
As per claim 1, Xi teaches: …estimate a stay POI that is a POI in which a user stays in an unassociated stay that is a stay not associated with the POI, among stays comprised in user information that is a chronological history of a stay during movement of each user, ([Abstract] … identify the missing POI categories at any time in the real-world check-in data of mobile users. To this end, in this paper, we propose a novel neural network approach to identify the missing POI categories by integrating both bi-directional global non-personal transition patterns and personal preferences of users. Specifically, we delicately design an attention matching cell to model how well the check-in category information matches their non-personal transition patterns and personal preferences. [Page 75] … utilize the check-in information before and after the missing category, which naturally calls for a bidirectional solution. Therefore, a long-standing challenge is how to effectively identify the missing POI categories at any time in the real-world check-in data of mobile users)
a part of which is associated with the POI in which the user stays, and adjacency of each user to other users, on the basis of the user information, ([Page 76] … users’ check-in activities usually have some public transition patterns, which are non-personal preferences. For example, users often go to dinner after work and watch a movie after dinner. The transition patterns work → dinner,dinner → movie are global and non-personal for all users. Our model is designed to capture bi-directional global transition patterns … the bi-directional global transition patterns and users’ personal preferences, the Bi-GTPPP can yield more accurate missing POI category identification. [Page 77] … Bi-GTPPP model is designed to capture the global transition patterns from bi-direction)
perform a simulation assuming that the user moves via a POI candidate that is a candidate of the stay POI for each user, and estimating the stay POI from the POI candidate, on the basis of a chronological match between adjacency between users extracted in the simulation and adjacency comprised in the user information. ([Abstract] … identify the missing POI categories by integrating both bi-directional global non-personal transition patterns and personal preferences of users. [0076] … predict the most likely location of users given their previous activities. [Page 77] model how well the user’s bi-directional check-in information matches the global transition patterns [Page 78] … we perform experiments to evaluate the proposed Bi-GTPPP model against various baseline methods on two real-world LBSNs datasets [0075] … identify the missing POI categories at any time in the real-world check-in data of mobile users).
chronologically match the … contact information acquired from the mobile terminal and a contact timing in the simulation via the POI candidate ([Abstract] model how well the check-in category information matches their non-personal transition patterns and personal preferences [Page 75] … utilize the check-in information before and after the missing category [Page 76] … model is designed to capture bi-directional global transition patterns … the bi-directional global transition patterns and users’ personal preferences, the Bi-GTPPP can yield more accurate missing POI category identification.
Although not explicitly taught by Xi, Kawaguchi teaches: a stay point of interest (POI) estimation device, comprising processing circuitry configured to estimate a stay POI that is a POI in which a user stays in an unassociated stay that is a stay not associated with the POI ([0039] The information processing apparatus 100 may be constituted by, for example, a personal computer (hereinafter, referred to as “PC”). The information processing apparatus 100 includes a control unit 110, a storage unit 130, [0004] In order to actually utilize the location information history, it is necessary to model the location information history in accordance with the purpose. For example, as approaches for modeling a staying location transition of a user, there have been known a “coordinate transition model” that represents staying locations by coordinates (latitude and longitude) and a “label transition model” that represents staying locations by labels (for example, residential districts, restaurants, and the like). By modeling the location information history, the data can be abstracted and the meaning can be easily settled for each user.).
It would have been obvious, before the effective filing date of the claimed invention, for one of ordinary skill in the art to have modified the teachings of Xi with the aforementioned teachings of Kawaguchi with the motivation of labeling stay locations (Kawaguchi [0004]). Further, one of ordinary skill in the art would have recognized that applying the teachings of Kawaguchi to the system of Xi would have yielded predictable results and doing so would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow for the labeling of stay locations.
Although not explicitly taught by Xi, Loh teaches: periodically acquire, from a mobile terminal of a user, Bluetooth Low Energy (BLE) contact information indicating contact with one or more other mobile terminals of other users, and store the acquired information as part of user information of the user; ([0106] In an example implementation, a participating device can periodically wake up (on a predetermined or random schedule) and use a short-range communication method (e.g., radio frequency, ultrasound, etc.) to scan the vicinity for nearby participating devices which are available to communicate. [0107] … a bilateral protocol based on BLUETOOTH Low Energy is as follows. [0108] Device A initiates a vicinity scan to detect a list of devices advertising their presence. BLUETOOTH Low Energy communication returns information such as the received signal [0110] … Device A sends information about the interaction to Device B … Both devices record this information. [0174] The array of electronic communication devices 172 periodically sends observed interaction records (unilateral and bilateral) to the central authority 174 operated, e.g., by one or more server devices. Data can also (or alternatively) be sent to a decentralized infrastructure. The observed interaction records can include information such as positions/locations of the electronic communication devices, distance to another electronic communication device [0175] … one or more networks 176 that represent pairwise interactions between users [0239] … mobile devices can submit contact information and receive, from the server and/or decentralized infrastructure, displayable output which includes information based on the proximity network. Interactions between devices and the server and/or decentralized infrastructure can occur in real-time).
chronologically match the BLE contact information acquired from the mobile terminal and a contact timing … ([0178] … there were at least 2 different times, separated by at least 5 minutes, such that at those times, Users A and B had devices which detected that they were within short-range communication range (e.g., detected each other via the Example Implementation of BLUETOOTH Low Energy Bilateral Protocol). [0240] … contact proximity network represents pairwise interactions between the users of the first and second electronic communication devices. The contact proximity network includes proximity information amongst a plurality of users, where the proximity information may include a geographical distance, a network distance along the contact proximity network, and/or a frequency of contact between users. The proximity information may include: 1) current vicinity information related to a current geographical distance between users, a current network distance between users, and/or a current geographical distance between mobile electronic communication devices associated with users; 2) past vicinity information related to a geographical distance between users, a network distance between users, and/or a geographical distance between mobile electronic communication devices associated with users during a past period of time; 3) time information related to when users and/or associated mobile electronic communication devices were within a defined vicinity relative to one another).
It would have been obvious, before the effective filing date of the claimed invention, for one of ordinary skill in the art to have modified the teachings of Xi with the aforementioned teachings of Loh with the motivation of modeling contact between users/devices. Further, one of ordinary skill in the art would have recognized that applying the teachings of Loh to the system of Xi would have yielded predictable results and doing so would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow for the use of BLE based detection of contact between users.
As per claim 2, Xi teaches: determine the POI candidate of the user, on the basis of at least one of a stay of the user immediately before the unassociated stay and a stay of the user immediately after the unassociated stay ([Page 76] … users’ check-in activities usually have some public transition patterns, which are non-personal preferences. For example, users often go to dinner after work and watch a movie after dinner. The transition patterns work → dinner,dinner → movie are global and non-personal for all users. Our model is designed to capture bi-directional global transition patterns … the bi-directional global transition patterns and users’ personal preferences, the Bi-GTPPP can yield more accurate missing POI category identification).
As per claim 3, Xi teaches: determine POI candidates of each of users in contact with each other in the unassociated stay by narrowing down the POI candidates to POI candidates overlapping each other among the POI candidates determined for each of the users ([Page 78] … The most popular categories in the training set are selected as the prediction for all users).
As per claim 4, although not explicitly taught by Xi, Kawaguchi teaches: wherein the estimation unit groups processing circuitry is further configured to group users in contact with each other in a predetermined period, and performs the simulation in the predetermined period for each group ([0047] … specifying a vector representation VRa representing features of respective temporal usage patterns (how the location is used with respect to time) of L areas (L is an integer greater than or equal to 2). In the present embodiment, a staying pattern of each user in each area is used as a temporal usage pattern of each area. [0051] The area-specific usage pattern data Da is data for specifying the staying pattern by the combination of the staying date attribute (staying day of the week), the staying time point (arrival time), and the staying time length of each user in each area. FIG. 5 is an explanatory diagram illustrating a classification of each item for specifying the staying pattern. [0056] … The vector representation VRa of each area specified in this way represents a feature such as on which kind of date (day of the week), in which time zone, and how long a person tends to stay in the area. [0073] … The vector representation transition model of a user is a model which represents the staying area of each user at each time point by the vector representation VRa of the area. In the example shown in FIG. 11, the user starts from an area having an area ID:7838 (belonging cluster:<b>9</b>), and transits the staying location in the order of an area having an area ID:6938 (belonging cluster:1), an area having an area ID:7838 (belonging cluster:9), an area having an area ID:6096 (belonging cluster:0), and an area having an area ID:7838 (belonging cluster:9) . . . , and the staying transitions are represented by vector representations VRa of respective staying areas. By using the vector representation transition model, for example, comparison of staying location transitions among a plurality of users can be performed on the basis of the distance between the vector representations VRa of each of the areas where each of the users stayed. [0120] … the temporal usage pattern (how the location is used with respect to time) of each area … As shown in FIG. 4, the area-specific usage pattern data Da indicates which of the 144 staying patterns specified by a combination of the staying day of the week, the staying time point, and the staying time length the individual stay of each user in each area is).
It would have been obvious, before the effective filing date of the claimed invention, for one of ordinary skill in the art to have modified the teachings of Xi with the aforementioned teachings of Kawaguchi with the motivation of labeling stay locations (Kawaguchi [0004]). Further, one of ordinary skill in the art would have recognized that applying the teachings of Kawaguchi to the system of Xi would have yielded predictable results and doing so would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow for the labeling of stay locations.
As per claim 5, Xi teaches: on the basis of the number of matches in the simulation, computes compute an estimation accuracy of the stay POI ([Page 79] … To evaluate the performance of our proposed Bi-GTPPP model and the baselines described above, we follow the existing works (Liu et al., 2016) to use several standard metrics: Recall@K, F1 score@K and Mean Average Precision (MAP) [0080] … Table2 Evaluation of missing category identification in terms of Recall@K, F1-score@KandMAP).
As per claim 6, Xi teaches: on the basis of the number of matches in the simulation with respect to one POI candidate, computes compute an estimation accuracy of the one POI candidate ([Page 79] … To evaluate the performance of our proposed Bi-GTPPP model and the baselines described above, we follow the existing works (Liu et al., 2016) to use several standard metrics: Recall@K, F1 score@K and Mean Average Precision (MAP) [0080] … Table2 Evaluation of missing category identification in terms of Recall@K, F1-score@KandMAP).
As per claim 7, Xi teaches: on the basis of the number of matches in the simulation, and the number of matches in the simulation with respect to one POI candidate, computes compute an estimation accuracy of the one POI candidate ([Page 79] … To evaluate the performance of our proposed Bi-GTPPP model and the baselines described above, we follow the existing works (Liu et al., 2016) to use several standard metrics: Recall@K, F1 score@K and Mean Average Precision (MAP) [0080] … Table2 Evaluation of missing category identification in terms of Recall@K, F1-score@KandMAP).
As per claim 8, this claim recites limitations substantially similar to those addressed by the rejection of claim 1, above; therefore, the same rejection applies.
Response to Arguments
Applicant's arguments filed 6/4/2026 have been fully considered but they are not persuasive.
With respect to the rejection under 35 USC 101, Applicant argues that the claims do not recite a certain method of organizing human activity.
Examiner respectfully disagrees. Examiner maintains that limitations in the claims describing estimating a stay POI (i.e., the abstract idea) fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, which covers marketing activities. Examiner acknowledges that the claims recite certain additional elements related to BLE; these additional elements are addressed in Step 2A – prong 2 of the rejection.
With respect to the rejection under 35 USC 101, Applicant argues that the claims directed to an improvement to the technological environment and integrate the abstract idea into a practical application.
Examiner respectfully disagrees. Additional elements such as acquire, from a mobile terminal of a user, Bluetooth Low Energy (BLE) contact information indicating contact with one or more other mobile terminals of other users… and BLE contact information acquired from the mobile terminal do not yield an improvement in the functioning of the computer itself, nor do they yield improvements to a technical field or technology; further these additional elements only add insignificant extra-solution activity (data gathering).
With respect to the rejection under 35 UCS 103, Applicant argues that the art of record does not disclose the claimed limitations.
Examiner respectfully disagrees. The Applicant’s arguments are directed to newly amended features; additional search has been conducted and the rejection has been updated to address said amendments. See updated Claim Rejections - 35 USC § 103 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2010/0062746 (Proctor) – discloses a system that uses BLE to identify contact between users/devices.
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 ALAN TORRICO-LOPEZ whose telephone number is (571)272-3247. The examiner can normally be reached M-F 10AM-5PM.
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/ALAN TORRICO-LOPEZ/Primary Examiner, Art Unit 3625
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