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 .
2. Claims 1–20 are presented for examination in a non-provisional application filed on Jul. 27, 2023.
Drawings
3. The drawings were received on 07/27/2023 (in the application filings). These drawings are acceptable.
Examiner’s Remarks
4. Examiner refers to and explicitly cites particular pages, sections, figures, paragraphs or columns and lines in the references as applied to Applicant’s claims to the extent practicable to streamline prosecution.
Although the cited portions of the references are representative of the best teachings in the art and are applied to meet the specific limitations of the claims, other uncited but related teachings of the references may be equally applicable as well. It is respectfully requested that, in preparing responses to the rejections, the Applicant fully considers not only the cited portions of the references, but also the references in their entirety, as potentially teaching, suggesting or rendering obvious all or one or more aspects of the claimed invention.
Abbreviations
5. Where appropriate, the following abbreviations will be used when referencing Applicant’s submissions and specific teachings of the reference(s):
i. figure / figures: Fig. / Figs.
ii. column / columns: Col. / Cols.
iii. page / pages: p. / pp.
References Cited
6. (A) YORK et al., US 2020/0357406 A1 (“York”).
Notice re prior art available under both pre-AIA and AIA
7. 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 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.
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 of this title, 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.
A.
8. Claims 1, 4–8, 11–15, and 18–20 are rejected under 35 U.S.C. 103 as being unpatentable over (A) York (US 2020/0357406 A1).
See “References Cited” section, above, for full citations of references.
9. Regarding claim 1, (A) York teaches/suggests the invention substantially as claimed, including:
“A computer-implemented method comprising:
determining, by one or more computer processors, an activity of a user”
(¶ 307: determines a timeliness score of a notification that represents the notification's timeliness. In some examples, notifications model 854 determines a timeliness score of a notification based on context information associated with the a user (user context). Exemplary user context includes a location of a user, a user notification setting, a device setting ( e.g. low power mode, do not disturb mode), a rate of travel of a user, a current activity the user is engaged in ( e.g., driving, turning while driving, in a meeting, in a workout session, listening to music, watching a movie), a state of the user (e.g., sleeping, awake));
“calculating, by one or more computer processors, a [[focus]] (engagement) score associated with the activity”
(¶ 308: if notifications model 854 determines that device 800 is in a do not disturb mode, a TIMELINESS score of a notification is decreased ( e.g., below a threshold). As another example, if notifications model 854 determines that a user is currently engaged in a first set of predetermined activities ( e.g., in a meeting as determined from calendar data, in a workout session as determined from a workout application being initiated), a timeliness score of a notification is decreased;
“receiving, by one or more computer processors, an incoming notification”
(¶ 258: The notification is a text message from the user's mom asking "where are you?" ….;
¶ 265: when device 800 (here the external device) receives the notification, device 800 sends an indication of the notification to device 810 and device 810 receives the indication from device 800;
¶ 347: receiving the indication of the notification includes receiving the notification at an electronic device)
“determining, by one or more computer processors, the focus score exceeds a pre-defined focus threshold”
(¶ 310: notifications model 854 determines whether a timeliness score of a notification exceeds (or does not exceed) one or more thresholds. For example, a timeliness score below a lower threshold (low timeliness score) indicates that the corresponding notification is not timely and a timeliness score above an upper threshold (high timeliness score) indicates that the corresponding notification is timely);
“calculating, by one or more computer processors, a relevance score of the incoming notification”
(¶ 303: notifications model 854 determines an IMPORTANCE score of a notification that represents the notification's importance. In some examples, notifications model 854 determines an importance score of a notification based on context information associated with the notification (notification context). Exemplary notification context includes the sender of the notification, whether the user has previously received notifications from the sender, previous user responses to notifications from the sender, the time of the notification, the content of the notification, the relevance of the notification to a previous notification, the length of the notification, the type of the notification ( e.g., text message, email, application notification), the relevance of the notification to a user's current context, user notification settings, and the like. In some examples, notifications model 854 determines such context information and uses such context information ( or a combination of such context information) to determine and/or adjust an importance score of a notification;
¶ 305: notifications model 854 performs content analysis on a notification to determine whether the notification is relevant to a user's current context ( e.g., current location, current activity being performed, and the like).
For example, if a user’s current context indicates that he or she is waiting for a flight (e.g., as determined by user location and/or calendar data) and a notification is determined to be relevant to the flight (e.g., includes a flight gate change information) an importance score of the notification is increased)
“determining, by one or more computer processors, the relevance score exceeds a pre-defined relevance threshold”
(¶ 306: notifications model 854 determines whether an importance score for a notification exceeds (or does not exceed) one or more thresholds. For example, an importance score below a lower threshold (low importance score) indicates that the corresponding notification is not important and an importance score above an upper threshold (high importance score) indicates that the corresponding notification is important);
“based on the focus score exceeding the pre-defined focus threshold and the relevance score exceeding the pre-defined relevance threshold, delivering, by one or more computer processors, the incoming notification at an opportune time”
(¶ 301: For example, determining whether to provide a notification output may be alternatively or additionally based on a determined importance of the notification ( e.g., its urgency) and/or a determined timeliness of the notification ( e.g., whether it is currently a good time to provide the notification output);
¶ 311: In some examples, notifications model 854 determines a relevance score of a notification based on a timeliness score of the notification and/or an importance score of the notification … example, a relevance score above a threshold (high relevance score) indicates that a corresponding notification output should be provided, while a relevance score below a threshold (low relevance score) indicates that a corresponding notification output should not be provided;
¶ 320: a score of a notification affects when a notification output is provided. For example, if an importance score of a notification is high, but a current timeliness score of the notification is low, notifications module 830 waits until the timeliness score is high to provide the notification output. In this manner, notifications module 830 can wait for appropriate times to provide important notification outputs. For example, if a user is currently in a meeting and receives an important notification, notifications model 854 determines that a timeless score of the notification is low. However, after the user is done with the meeting, notifications model 854 determines that the timeliness score is now high. Notifications module 830 thus causes the notification output to be provided after the meeting).
The Examiner notes that York do not expressly use the term “focus score.”
However, York explicitly describes its timeliness score as a measure (reflection) of how engaged in or “focused” a user is on a particular activity (see ¶¶ 307–308).
Accordingly, York’s “timeliness” score or metric may be reasonably understood and construed as a “focus” score associated with an activity (such as driving, working out, attending a meeting).
10. Regarding claim 4, York teaches or suggests:
“determining, by one or more computer processors, the relevance score does not exceed the pre-defined relevance threshold”
(¶ 301: For example, determining whether to provide a notification output may be alternatively or additionally based on a determined importance of the notification ( e.g., its urgency) and/or a determined timeliness of the notification ( e.g., whether it is currently a good time to provide the notification output;
¶ 306: notifications model 854 determines whether an importance score for a notification exceeds (or does not exceed) one or more thresholds …. an importance score below a lower threshold (low importance score) indicates that the corresponding notification is not important and an importance score above an upper threshold (high importance score) indicates that the corresponding notification is important. In some examples, notifications model 854 causes notifications module 830 to provide an output associated with a notification in accordance with determining that an importance score of the notification exceeds a threshold);
“based on the focus score exceeding the pre-defined focus threshold and the relevance score not exceeding the pre-defined relevance threshold, delaying, by one or more computer processors, delivery of the incoming notification to a later time”
(¶ 310: notifications model 854 determines whether a timeliness score of a notification exceeds (or does not exceed) one or more thresholds. For example, a timeliness score below a lower threshold (low timeliness score) indicates that the corresponding notification is not timely and a timeliness score above an upper threshold (high timeliness score) indicates that the corresponding notification is timely);
¶¶ 301 and 306, as applied above, teaching determining whether to provide a notification output based on a determined importance of the notification;
¶ 316: indicate that notifications model 854 should have not determined to provide the notification output based on the context information (e.g., should have determined a low relevance score). Thus, based on such user engagement data, notifications model 854 is trained to determine low relevance scores of subsequent notifications associated with contexts matching ( or similar to) the context. In this manner, device 810 may not provide notification outputs for undesirable subsequent notifications).
11. Regarding claim 5, York teaches or suggests:
“wherein delaying the delivery of the incoming notification to the later time further comprises: determining, by one or more computer processors, a time when the focus score does not exceed the pre-defined focus threshold”
(¶ 301: For example, determining whether to provide a notification output may be alternatively or additionally based on a determined importance of the notification ( e.g., its urgency) and/or a determined timeliness of the notification ( e.g., whether it is currently a good time to provide the notification output;
¶ 320: a score of a notification affects when a notification output is provided. For example, if an importance score of a notification is high, but a current timeliness score of the notification is low, notifications module 830 waits until the timeliness score is high to provide the notification output. In this manner, notifications module 830 can wait for appropriate times to provide important notification outputs. For example, if a user is currently in a meeting and receives an important notification, notifications model 854 determines that a timeless score of the notification is low. However, after the user is done with the meeting, notifications model 854 determines that the timeliness score is now high. Notifications module 830 thus causes the notification output to be provided after the meeting).
12. Regarding claim 6, York teaches or suggests:
“receiving, by one or more computer processors, feedback associated with the delivered incoming notification from the user”
(¶ 313: In some examples, training module 856 trains notification model 854 using data obtained for a particular user (e.g., the user of device's 800 and 810). In some examples, such data indicates appropriate (and/or inappropriate) user contexts to provide notification outputs for a particular user;
¶ 314: training module 856 collects user engagement and data trains notification model 854 using the data. User engagement data includes data relating to user interaction with a notification (and/or notification output) at devices 800 and/or 810. For example, user engagement data indicates whether a user has interacted with a notification ( e.g., replied to a notification, deleted a notification, dismissed a notification) and/or whether a user has terminated a notification output);
“training, by one or more computer processors, a machine learning algorithm with the received feedback”
(¶ 313: In some examples, training module 856 trains notification model 854 using data obtained for a particular user (e.g., the user of device's 800 and 810). In some examples, such data indicates appropriate (and/or inappropriate) user contexts to provide notification outputs for a particular user;
¶ 302: notifications model 854 includes one or more neural networks (e.g., recurrent neural networks (RNNs), convolutional neural networks (CNNS), and the like) and/or other machine learned models trained to determine the importance and/or timeliness of notifications).
13. Regarding claim 7, York teaches or suggests:
“wherein calculating the focus score associated with the activity includes analyzing at least one of: a typing pattern of the user, data from one or more wearable devices associated with the user, a webcam feed, and an eye gaze of the user”
(¶ 259: device may be any type of device, such as a phone, laptop computer, desktop computer, tablet, wearable device (e.g., smart watch), television, speaker, vehicle console, or any combination thereof;
¶ 162: detected eye movements; biometric inputs; and/or any combination thereof are optionally utilized as inputs corresponding to sub-events
¶ 307: Exemplary user context includes a location of a user, a user notification setting, a device setting ( e.g. low power mode, do not disturb mode), a rate of travel of a user, a current activity the user is engaged in ( e.g., driving, turning while driving, in a meeting, in a workout session, listening to music, watching a movie), a state of the user (e.g., sleeping, awake)).
14. Regarding claims 8, 11–14, they are the corresponding computer program product claim reciting similar limitations of commensurate scope as the method of claims 1 and 4–7, respectively. Therefore, they are rejected on the same basis as claims 1 and 4–7 above.
15. Regarding claim 15 and 18–20, they are the corresponding system claim reciting similar limitations of commensurate scope as the method of claims 1 and 4–6, respectively. Therefore, they are rejected on the same basis as claims 1 and 4–6 above, further including the following rationale:
York teaches or suggests: “computer system comprising: one or more computer processors;
one or more computer readable memories; and one or more computer readable storage media;
program instructions, stored on at least one of the one or more computer readable storage media for execution by at least one of the one or more computer processors via at least one of the one or more memories to … (perform the claimed steps)”
(¶ 15: example electronic device comprises one or more processors; a memory; and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions;
Fig. 2A and ¶ 60: Memory 202 includes one or more computer-readable storage mediums. The computer-readable storage mediums are, for example, tangible and non-transitory. Memory 202 includes high-speed random access memory and also includes non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other nonvolatile solid-state memory devices;
Claim 37).
Allowable Subject Matter
16. Claims 2–3, 9–10, and 16–17 are objected to as being dependent upon a rejected base claim, but would be allowable if 1) rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is the Examiner’s statement of reasons for allowance:
The prior art of record, when viewed individually or in combination, does not expressly teach nor render obvious the features of dependent claims 2, 9, and 16 when viewed as a whole, specific to the limitation(s) of:
“extracting, by one or more computer processors, project information from the retrieved data using one or more natural language processing techniques;
determining, by one or more computer processors, one or more important projects and deadlines from the extracted data; and
generating, by one or more computer processors, a semantic graph for each of the one or more projects using the extracted project information.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
(a) Taboriskiy, US 2018/0107743 A1, teaching notifying users of relevant
content.
(b) GUERRA et al., US 2024/0004727 A1, teaching notification delay and auto-dismiss functionality.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BENJAMIN C WU whose telephone number is (571)270-5906. The examiner can normally be reached Monday through Friday, 8:30 A.M. to 5:00 P.M..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aimee J. Li can be reached on (571)272-4169. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BENJAMIN C WU/Primary Examiner, Art Unit 2195
September 16, 2026
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