DETAILED ACTION
1. Claims 1-15 and 17-20 are pending.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
3. Claim 18 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 18 recites the limitation "the plurality of application window layouts". There is insufficient antecedent basis for this limitation in the claim.
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.
4. Claim(s) 1, 3-10, 17, 19, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jeon et al. (WO 2025/154986 A1) and further in view of Ahn et al. (KR 102593826 B1).
NOTE: In the below rejections, the cited portions of Jeon et al. (WO 2025/154986 A1) are with respect to the provided machine translation appended to the end of the provided copy of Jeon et al. (WO 2025/154986 A1).
NOTE: In the below rejections, all relied on portions of Jeon et al. (WO 2025/154986 A1) are described in the priority document 10-2024-0032125, dated 3/6/2024, which is published as Jeon et al. (KR 20250112111 A).
NOTE: In the below rejections, the cited portions of Ahn et al. (KR 102593826 B1) are with respect to the provided machine translation included with this office action (see PTO-892).
In regard to claim 1, Jeon discloses a system, comprising: a processing system; and memory coupled to the processing system, the memory comprising computer executable instructions that, when executed by the processing system, causes the system to perform operations comprising (Fig. 1):
in response to a trigger event (Pg 17: “According to one embodiment, the processor (710) may detect an event that triggers the configuration of a multi-window layout while the first application is running. For example, the event that triggers the configuration of the multi-window layout is an event that triggers the second application, and may include events such as, but not limited to, occurrence of an input for selecting an application to run”), collecting or identifying first context signals, the first context signals including at least one of content, topic, subject, or domain of an open application window among a plurality of application windows that is displayed within at least one display screen of corresponding at least one display device (Pg. 17: “ According to one embodiment, the processor (710) may analyze at least some of the information (e.g. application information, device status information, user status/tendency information, or content data)stored in the memory (720) to analyze a user's usage pattern for a plurality of applications to be displayed in a multi-window layout” and Pg. 20: “According to one embodiment, the application information (812) may include information related to various applications installed and/or running on the electronic device. For example, the application information (812) may include at least some of the following: application information such as the type of each application (e.g., media player, messenger, document, calendar, calculator, or game), resolution, execution history, usage frequency, user preference, association with other applications, simultaneous execution frequency, execution screen size, ratio, and resolution; application information related to the multi-window, such as whether multi-window is supported, display position, size, and resolution when running multi-window, and other applications that are frequently run together with multi-window; and/or content information of the application, such as content (e.g., video, audio), messages, or notifications provided by the running application. The application information (812) described in this document is not limited to the examples described above…the execution history of applications, usage frequency, preferences, application search history, Internet search history, frequently executed applications (or relevance of applications) at the same time, or user tendency information such as a preferred form of multi-window layout, and a behavior pattern when a notification (e.g., receiving a message) occurs”);
providing the first context signals as input to a machine learning ("ML") model that has been trained to provide window layout suggestions based on a plurality of combinations of context signals (Pg. 15: “According to one embodiment, the electronic device (610, 620) may transmit a task request to the AI model (650) to cause the AI model (650) to perform an intended task based on a user input. For example, when a user of the electronic device (610, 620) inputs a task to be requested to the AI model (650) through a voice input via a microphone or a text input via a keyboard/keypad, the electronic device (610, 620) may generate a prompt including the task request and transmit it to the AI model(650)” and Pg. 17: “According to one embodiment, the processor (710) may generate a prompt including a task request for requesting an AI model (e.g., a generative AI model) to configure a multi-window layout”, Pg. 18: “Examples of prompts generated based on the analysis results of the current operating status information of the electronic device (700) and/or the user's usage pattern are as shown”, Pg. 21: “the application analysis module (822) can analyze execution history, usage frequency, or user preference to determine whether the content provided through each window is important content to the user. The application analysis module (822) can, during the analysis, be based on at least some of the device status information (814), the user status/tendency information (816), and/or the content data (818) in addition to the application information (812)”, and Pg. 22: “According to one embodiment, the electronic device may generate a prompt (830) based on the analysis result of the analysis module (820). For example, the electronic device may generate the prompt (830) including a task request for configuring a multi-window layout, information on the current operating status of the electronic device generated based on the analysis result of the analysis module, and/or information necessary for configuring the multi-window layout, such as usage pattern and preference information”);
receiving, as output from the ML model, windowing suggestions for at least one window layout for a plurality of application windows based on the first context signals (Pg. 15: “the AI model (650) can interpret a prompt received from an electronic device (610, 620), execute a task requested by a user, and generate the result of the executed task as text and/or image information and transmit it to the electronic device (610, 620) as a task response” and Pg. 17: “ Accordingly, the AI model may configure a multi-window layout according to the task request included in the prompt of the electronic device (700)and transmit a task response including information related thereto to the electronic device (700)”).
While Jeon teaches receiving, as output from the ML model, windowing suggestions for at least one window layout for a plurality of application windows based on the first context signals, they fail to show the displaying the windowing suggestions for the at least one window layout for the plurality of application windows, as recited in the claims. Ahn teaches a ML model and windowing suggestions similar to that of Jeon. In addition, Ahn further teaches
displaying the windowing suggestions for at least one window layout for a plurality of application windows (Pg. 8 “…Meanwhile, this implementation device 100 may use machine learning to arrange windows in multiwindow implementation according to user preference… the output data of the machine learning model consists of a predicted order or window arrangement according to user preference. This can take the form of… a set of recommended window arrangements from which the user can select…”: the machine learning model outputs a set of recommended window arrangements from which the user can select).
It would have been obvious to one of ordinary skill in the art, having the teachings of Jeon and Ahn before him before the effective filing date of the claimed invention, to modify the receiving, as output from the ML model, windowing suggestions for at least one window layout for a plurality of application windows based on the first context signals taught by Jeon to include displaying the windowing suggestions for at least one window layout for a plurality of application windows of Ahn, in order to obtain displaying the windowing suggestions for the at least one window layout for the plurality of application windows. It would have been advantageous for one to utilize such a combination as arranging windows according to user preference thereby providing a more personalized and efficient user experience, as suggested by Ahn (Pg. 8 “…By arranging windows in a multi-window implementation according to the user's preference using machine learning, the implementation device 100 provides a more personalized and efficient user experience (UX), allowing the user to run multiple applications or processes at once. This can provide the effect of working more efficiently and productively…”).
In regard to claim 3, Jeon discloses wherein the operations further comprise at least one of: launching, duplicating, or maximizing one or more application windows among the plurality of application windows, based on a first window layout of the windowing suggestions (Pg. 2: “a multi-window layout to be configured in response to the first event, and to configure a multi-window layout including an execution screen of the first application and an execution screen of the second application”, Fig. 13(a)-13(b), and Pg. 28 “Referring to (a) of FIG. 13, the electronic device can execute a lecture application (1310) and provide the contents of the lecture application (1310) in a single window layout.. can execute a note application (1320) as in (b) of Fig. 13, and display the lecture application (1310) and the note application (1320) in a multi-window layout”); layering, cascading, stacking, or overlaying two or more application windows among the plurality of application windows over one or more other application windows among the plurality of application windows, based on the first window layout; tiling, snapping, or grouping two or more other application windows among the plurality of application windows within the at least one display screen of corresponding at least one display device, based on the first window layout; or closing or minimizing one or more other currently displayed application windows that are not among the plurality of application windows, based on the first window layout.
In regard to claim 4, Jeon discloses identifying two or more application windows among the plurality of application windows having at least one of common or related content, common or related topic, common or related subject, or common or related domain (Pg. 23: “According to one embodiment, the electronic device may determine the correlation between each application based on the similarity of keywords that can be extracted from each application execution screen of the multi-window. …According to one embodiment, the electronic device may determine the relevance between applications based on the positions of application windows arranged in a multi-window layout. For example, if a user directly configures a multi-window layout and frequently arranges a messenger application and a shopping mall application, or a gallery application and a file application, adjacent to each other, the relevance may be determined to be high”);
and grouping the two or more application windows within the at least on display screen, based on a first window layout of the windowing suggestions (Pgs. 25-26: “In one embodiment, if the user is currently driving, the electronic device may determine, based on the analysis results, that the user's driving usage pattern/taste is to listen to music while looking at navigation… generate a task response including information related to a layout in the form of a multi-window layout in which a navigation application is disposed in a left window close to the user, a music application is disposed in a right window, and a size ratio of 8 to 2, and provide the task response to the electronic device”).
In regard to claim 5, Jeon discloses wherein the trigger event includes one of: a user-system interaction-based trigger event including one of: detecting a user logging into a user account; detecting a user unlocking a locked display screen; detecting a user launching, closing, duplicating, maximizing, minimizing, or resizing an application window for display (Pg 17: “According to one embodiment, the processor (710) may detect an event that triggers the configuration of a multi-window layout while the first application is running. For example, the event that triggers the configuration of the multi-window layout is an event that triggers the second application, and may include events such as, but not limited to, occurrence of an input for selecting an application to run”), or that is being displayed, within the at least one display screen of the corresponding at least one display device; detecting a user changing from a first user task to a second user task, each involving one or more application windows for display, or that are being displayed, within the at least one display screen of the corresponding at least one display device; or receiving a user input, the user input including one of: a user input to select from a suggested list of smart window layouts; a user input to select from one of a saved set of smart window layouts or a frequently used set of smart window layouts; a user input to trigger smart window layout functionality; or a user input to organize a cluttered desktop environment; or a system change-based trigger event including one of: detecting the system being booted up; detecting docking or undocking of a laptop computer; detecting a change from a first monitor setup to a second monitor setup, the second monitor setup having at least one of a second number, a second type, or a second size of monitor that is different from the first monitor setup having a corresponding at least one of a first number, a first type, or a first size of monitor; detecting tripping of a time-of-day-based trigger; detecting a cluttered condition of application windows displayed within the at least one display screen of the corresponding at least one display device; or detecting a number of displayed application windows exceeding a threshold number of application windows.
In regard to claim 6, Jeon discloses wherein the ML model is a neural network model including one of a convolutional neural network ("CNN") model, a recurrent neural network ("RNN"), or a deep neural network ("DNN") (Pg. 4: “the artificial intelligence model may include a plurality of artificial neural network layers. The artificial neural network may be one of a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), deep Q-networks, or a combination of two or more of the above, but is not limited to the examples described above”).
In regard to claim 7, Jeon discloses wherein the ML model is a local ML model (Pg. 19: “the on-device AI model”) that is trained and optimized local to the system, using the collected or identified context signals (Pg. 4: “Such learning may be performed, for example, in the electronic device (101) itself on which the artificial intelligence model is executed” and Pg. 17: “the AI model may be learned based on operation state information (e.g., application information, device state information, user state/tendency information, content data, usage pattern and/or preference information) of the electronic device (700) and the form of the multi-window layout”).
In regard to claim 8, Jeon discloses wherein the context signals further include at least one of window positioning, window sizing, window layering, window layout, window tiling, titles of application windows, types of applications displayed in the application windows, content of applications, content of application windows, or a number of monitors used, correlated with at least one of user, type of user, task, time-of-day, monitor setup, computing system setup, number of task switches, number of window layout changes, or user location (Pg. 20: “According to one embodiment, the application information (812) may include information related to various applications installed and/or running on the electronic device. For example, the application information (812) may include at least some of the following: application information such as the type of each application (e.g., media player, messenger, document, calendar, calculator, or game), resolution, execution history, usage frequency, user preference, association with other applications, simultaneous execution frequency, execution screen size, ratio, and resolution; application information related to the multi-window, such as whether multi-window is supported, display position, size, and resolution when running multi-window, and other applications that are frequently run together with multi-window; and/or content information of the application, such as content (e.g., video, audio), messages, or notifications provided by the running application. The application information (812) described in this document is not limited to the examples described above”).
In regard to claim 9, Jeon discloses wherein the context signals further include at least one of dwell time of layout of application windows, metadata of application windows (Pg. 20: “According to one embodiment, the application information (812) may include information related to various applications installed and/or running on the electronic device. For example, the application information (812) may include at least some of the following: application information such as the type of each application (e.g., media player, messenger, document, calendar, calculator, or game), resolution, execution history, usage frequency, user preference, association with other applications… execution screen size, ratio, and resolution; application information related to the multi-window, such as whether multi-window is supported”), or a list of top x-number of open application windows by z-order of the open application windows.
In regard to claim 10, Jeon discloses wherein collecting or identifying the first context signals further comprises at least one of: inferring the content of the open application window from one or more of a document title of the open application window (Pg. 28: “According to one embodiment, the electronic device may analyze the content provided through the running application and data stored in the electronic device…For example, the electronic device may analyze the title provided through the video application…to determine that the soccer broadcast currently provided through the video application”), a uniform resource identifier ("URI") of a resource that is displayed in the open application window, or a uniform resource locator ("URL") of the resource that is displayed in the open application window; based on a determination that the system has access to full content contained in an application that is displayed in the open application window, extracting the full content from the application; performing optical character recognition ("OCR") of one or more of title, content, or URI that is displayed in the open application window; extracting the at least one of content, topic, subject, or domain from the open application window, converting the extracted at least one of content, topic, subject, or domain into feature sets, wherein providing the first context signals as input to the ML model includes providing the feature sets as input to the ML model; or extracting at least one of elements, attributes, or content from a document object model ("DOM") tree of a document that is displayed in the open application window.
In regard to claim 17, Jeon discloses a system for implementing smart window layout functionalities, the system comprising: a processing system; and memory coupled to the processing system, the memory comprising computer executable instructions that, when executed by the processing system, causes the system to perform operations comprising (Fig. 1):
receiving a user prompt requesting to identify or arrange a window layout of application windows based on a user task to be performed involving the application windows (Pg. 15: “According to one embodiment, the electronic device (610, 620) may transmit a task request to the AI model (650) to cause the AI model (650) to perform an intended task based on a user input. For example, when a user of the electronic device (610, 620) inputs a task to be requested to the AI model (650) through a voice input via a microphone or a text input via a keyboard/keypad, the electronic device (610, 620) may generate a prompt including the task request and transmit it to the AI model(650)” and Pg. 25: “According to one embodiment, the electronic device may generate and transmit the prompt to the AI model when a touch input or voice input for the user's multi-window execution occurs”);
generating, for input into a first language model ("LM"), an LM prompt based on the user prompt (Pg. 15: “According to one embodiment, the electronic device (610, 620) may transmit a task request to the AI model (650) to cause the AI model (650) to perform an intended task based on a user input. For example, when a user of the electronic device (610, 620) inputs a task to be requested to the AI model (650) through a voice input via a microphone or a text input via a keyboard/keypad, the electronic device (610, 620) may generate a prompt including the task request and transmit it to the AI model(650)” and Pg. 17: “According to one embodiment, the processor (710) may generate a prompt including a task request for requesting an AI model (e.g., a generative AI model) to configure a multi-window layout”);
receiving, as output from the first LM, windowing suggestions for at least one window layout for a plurality of application windows for facilitating performance of the user task (Pg. 15: “the AI model (650) can interpret a prompt received from an electronic device (610, 620), execute a task requested by a user, and generate the result of the executed task as text and/or image information and transmit it to the electronic device (610, 620) as a task response” and Pg. 17: “ Accordingly, the AI model may configure a multi-window layout according to the task request included in the prompt of the electronic device (700)and transmit a task response including information related thereto to the electronic device (700)”);
While Jeon teaches receiving, as output from the first LM, windowing suggestions for at least one window layout for a plurality of application windows for facilitating performance of the user task, they fail to show the displaying the windowing suggestions for the at least one window layout for the plurality of application windows, as recited in the claims. Ahn teaches a ML model and windowing suggestions similar to that of Jeon. In addition, Ahn further teaches
displaying the windowing suggestions for at least one window layout for a plurality of application windows (Pg. 8 “…Meanwhile, this implementation device 100 may use machine learning to arrange windows in multiwindow implementation according to user preference… the output data of the machine learning model consists of a predicted order or window arrangement according to user preference. This can take the form of… a set of recommended window arrangements from which the user can select…”: the machine learning model outputs a set of recommended window arrangements from which the user can select).
It would have been obvious to one of ordinary skill in the art, having the teachings of Jeon and Ahn before him before the effective filing date of the claimed invention, to modify the receiving, as output from the first LM, windowing suggestions for at least one window layout for a plurality of application windows for facilitating performance of the user task taught by Jeon to include displaying the windowing suggestions for at least one window layout for a plurality of application windows of Ahn, in order to obtain displaying the windowing suggestions for the at least one window layout for the plurality of application windows. It would have been advantageous for one to utilize such a combination as arranging windows according to user preference thereby providing a more personalized and efficient user experience, as suggested by Ahn (Pg. 8 “…By arranging windows in a multi-window implementation according to the user's preference using machine learning, the implementation device 100 provides a more personalized and efficient user experience (UX), allowing the user to run multiple applications or processes at once. This can provide the effect of working more efficiently and productively…”).
In regard to claim 19, Jeon discloses collecting or identifying context signals associated with one or more application windows that had been displayed within at least one display screen of a corresponding at least one display device prior to receiving the user prompt, the context signals including at least one of window positioning, window sizing, window layering, window layout, window tiling, titles of application windows, types of applications displayed in the application windows, content of applications, content of application windows, or a number of monitors used, correlated with at least one of user, type of user, task, time-of-day, monitor setup, computing system setup, number of task switches, number of window layout changes, or user location (Pg. 17: “ According to one embodiment, the processor (710) may analyze at least some of the information (e.g. application information, device status information, user status/tendency information, or content data)stored in the memory (720) to analyze a user's usage pattern for a plurality of applications to be displayed in a multi-window layout” and Pg. 20: “According to one embodiment, the application information (812) may include information related to various applications installed and/or running on the electronic device. For example, the application information (812) may include at least some of the following: application information such as the type of each application (e.g., media player, messenger, document, calendar, calculator, or game), resolution, execution history, usage frequency, user preference, association with other applications, simultaneous execution frequency, execution screen size, ratio, and resolution; application information related to the multi-window, such as whether multi-window is supported, display position, size, and resolution when running multi-window, and other applications that are frequently run together with multi-window; and/or content information of the application, such as content (e.g., video, audio), messages, or notifications provided by the running application. The application information (812) described in this document is not limited to the examples described above…the execution history of applications, usage frequency, preferences, application search history, Internet search history, frequently executed applications (or relevance of applications) at the same time, or user tendency information such as a preferred form of multi-window layout, and a behavior pattern when a notification (e.g., receiving a message) occurs”);
wherein generating the LM prompt includes adding the context signals (Pg. 18: “Examples of prompts generated based on the analysis results of the current operating status information of the electronic device (700) and/or the user's usage pattern are as shown”, Pg. 21: “the application analysis module (822) can analyze execution history, usage frequency, or user preference to determine whether the content provided through each window is important content to the user. The application analysis module (822) can, during the analysis, be based on at least some of the device status information (814), the user status/tendency information (816), and/or the content data (818) in addition to the application information (812)”, and Pg. 22: “According to one embodiment, the electronic device may generate a prompt (830) based on the analysis result of the analysis module (820). For example, the electronic device may generate the prompt (830) including a task request for configuring a multi-window layout, information on the current operating status of the electronic device generated based on the analysis result of the analysis module, and/or information necessary for configuring the multi-window layout, such as usage pattern and preference information”).
In regard to claim 20, Jeon discloses further comprising the LM, wherein the LM is located in a local architecture of the system, wherein prompts provided as input to the LM include local user data Pg. 19: “the on-device AI model”, Pg. 20: “According to one embodiment, an electronic device (e.g., an electronic device (700) of FIG. 7) may store various data (810) necessary to configure a multi-window layout on a memory (e.g., a memory(720) of FIG. 7”), and Pg. 22: “According to one embodiment, the electronic device may generate a prompt (830) based on the analysis result of the analysis module (820). For example, the electronic device may generate the prompt (830) including a task request for configuring a multi-window layout, information on the current operating status of the electronic device generated based on the analysis result of the analysis module, and/or information necessary for configuring the multi-window layout, such as usage pattern and preference information”).
5. Claim(s) 2 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jeon et al. (WO 2025/154986 A1), Ahn et al. (KR 102593826 B1), and further in view of Lee et al. (US 2022/0291818 A1).
NOTE: In the below rejections, the cited portions of Jeon et al. (WO 2025/154986 A1) are with respect to the provided machine translation appended to the end of the provided copy of Jeon et al. (WO 2025/154986 A1).
NOTE: In the below rejections, all relied on portions of Jeon et al. (WO 2025/154986 A1) are described in the priority document 10-2024-0032125, dated 3/6/2024, which is published as Jeon et al. (KR 20250112111 A).
NOTE: In the below rejections, the cited portions of Ahn et al. (KR 102593826 B1) are with respect to the provided machine translation included with this office action (see PTO-892).
In regard to claim 2, Jeon discloses displaying the plurality of application windows within the at least one display screen of the corresponding at least one display device based on a first window layout, wherein displaying the plurality of application windows based on the first window layout comprises at least one of: changing display of one or more first application windows that are currently being displayed within the at least one display screen of the corresponding at least one display device from a current window layout to the first window layout; replacing the current window layout of one or more second application windows as currently displayed within the at least one display screen of the corresponding at least one display device with the first window layout of the one or more second application windows; mapping each application window being displayed in the current window layout to the corresponding application window according to the first window layout; or for each application window being displayed in the current window layout, changing at least one of a first size, a first position, or a first level of zoom of the application window to a corresponding at least one of a second size, a second position, or a second level of zoom for the application window according to the first window layout (Pg. 2: “a multi-window layout to be configured in response to the first event, and to configure a multi-window layout including an execution screen of the first application and an execution screen of the second application”, Fig. 13(a)-13(b), and Pg. 28 “Referring to (a) of FIG. 13, the electronic device can execute a lecture application (1310) and provide the contents of the lecture application (1310) in a single window layout.. can execute a note application (1320) as in (b) of Fig. 13, and display the lecture application (1310) and the note application (1320) in a multi-window layout”).
While Jeon teaches the above and the combination of Jeon and Ahn teaches displaying the windowing suggestions for at least one window layout for a plurality of application windows, they fail to explicitly show the in response to receiving a selection of a first window layout from the windowing suggestions, as recited in the claims. Lee teaches windowing suggestions similar to that of Jeon and Ahn. In addition, Lee further teaches
displaying recommended layouts, receiving selection of a recommended layout, and displaying windows according to the selected recommended layout (Fig. 3 elements 330 and 340, Paragraph 0080, and Paragraph 0083).
It would have been obvious to one of ordinary skill in the art, having the teachings of Jeon, Ahn, and Lee before him before the effective filing date of the claimed invention, to modify the combination of Jeon and Lee to include the receiving selection of a recommended layout and displaying windows according to the selected recommended layout of Lee, in order to obtain in response to receiving a selection of a first window layout from the windowing suggestions, displaying the plurality of application windows within the at least one display screen of the corresponding at least one display device based on the first window layout, wherein displaying the plurality of application windows based on the first window layout comprises at least one of: changing display of one or more first application windows that are currently being displayed within the at least one display screen of the corresponding at least one display device from a current window layout to the first window layout; replacing the current window layout of one or more second application windows as currently displayed within the at least one display screen of the corresponding at least one display device with the first window layout of the one or more second application windows; mapping each application window being displayed in the current window layout to the corresponding application window according to the first window layout; or for each application window being displayed in the current window layout, changing at least one of a first size, a first position, or a first level of zoom of the application window to a corresponding at least one of a second size, a second position, or a second level of zoom for the application window according to the first window layout. It would have been advantageous for one to utilize such a combination as arranging windows according to user preference (The cited portions of Ahn in the rejection of claim 1 are incorporated herein in their entirety). As disclosed by Ahn, the suggestions are displayed for selection. However, Ahn never explicitly recites receiving a selection. By including the selection taught by Lee, the user can indicate their preference as to applying a recommended layout and therefore arrange the windows according to user preference.
In regard to claim 18, Jeon discloses displaying the plurality of application windows within at least one display screen of a corresponding at least one display device based on a first window layout, wherein displaying the plurality of application windows based on the first window layout comprises at least one of: changing display of one or more first application windows that are currently being displayed within the at least one display screen of the corresponding at least one display device from a current window layout to the first window layout; replacing the current window layout of one or more second application windows as currently displayed within the at least one display screen of the corresponding at least one display device with the first window layout of the one or more second application windows; mapping each application window being displayed in the current window layout to the corresponding application window according to the first window layout; or for each application window being displayed in the current window layout, changing at least one of a first size, a first position, or a first level of zoom of the application window to a corresponding at least one of a second size, a second position, or a second level of zoom for the application window according to the first window layout (Pg. 2: “a multi-window layout to be configured in response to the first event, and to configure a multi-window layout including an execution screen of the first application and an execution screen of the second application”, Fig. 13(a)-13(b), and Pg. 28 “Referring to (a) of FIG. 13, the electronic device can execute a lecture application (1310) and provide the contents of the lecture application (1310) in a single window layout.. can execute a note application (1320) as in (b) of Fig. 13, and display the lecture application (1310) and the note application (1320) in a multi-window layout”).
While Jeon teaches the above and the combination of Jeon and Ahn teaches displaying the windowing suggestions for at least one window layout for a plurality of application windows, they fail to explicitly show the in response to receiving a selection of a first window layout from the windowing suggestions, as recited in the claims. Lee teaches windowing suggestions similar to that of Jeon and Ahn. In addition, Lee further teaches
displaying recommended layouts, receiving selection of a recommended layout, and displaying windows according to the selected recommended layout (Fig. 3 elements 330 and 340, Paragraph 0080, and Paragraph 0083).
It would have been obvious to one of ordinary skill in the art, having the teachings of Jeon, Ahn, and Lee before him before the effective filing date of the claimed invention, to modify the combination of Jeon and Lee to include the receiving selection of a recommended layout and displaying windows according to the selected recommended layout of Lee, in order to obtain in response to receiving a selection of a first window layout from the windowing suggestions, displaying the plurality of application windows within at least one display screen of the corresponding at least one display device based on the first window layout, wherein displaying the plurality of application window layouts based on the first window layout comprises at least one of: changing display of one or more first application windows that are currently being displayed within the at least one display screen of the corresponding at least one display device from a current window layout to the first window layout; replacing the current window layout of one or more second application windows as currently displayed within the at least one display screen of the corresponding at least one display device with the first window layout of the one or more second application windows; mapping each application window being displayed in the current window layout to the corresponding application window according to the first window layout; or for each application window being displayed in the current window layout, changing at least one of a first size, a first position, or a first level of zoom of the application window to a corresponding at least one of a second size, a second position, or a second level of zoom for the application window according to the first window layout. It would have been advantageous for one to utilize such a combination as arranging windows according to user preference (The cited portions of Ahn in the rejection of claim 1 are incorporated herein in their entirety). As disclosed by Ahn, the suggestions are displayed for selection. However, Ahn never explicitly recites receiving a selection. By including the selection taught by Lee, the user can indicate their preference as to applying a recommended layout and therefore arrange the windows according to user preference.
Allowable Subject Matter
6. Claims 11-15 are allowed.
In regard to claims 11-15, the prior art of record, alone or in combination fails to teach or suggest the recited “collecting or identifying, by the computing system, context data regarding the at least one application window, the context data including at least one of dwell time of layout of the at least one application window, window layout changes involving the at least one application window, or use of the at least one application window, wherein the window layout changes include changes in one or more of window positioning, window sizing, level of zoom, position relative to other open application windows, or change in z-order of open application windows; and performing, by the computing system, one of: based on a determination that layout of the at least one application window has not changed within a threshold period, updating either historical use and layout data or at least one Al model to reinforce preference of the first window layout with respect to the at least one application window; or based on a determination that layout of the at least one application window has changed to a second window layout within the threshold period, updating either the historical use and layout data or the at least one Al model to replace the first window layout with respect to the at least one application window to the second window layout with respect to the at least one application window”.
The arguments, see Remarks filed 5/28/2026, with respect to amended claim 11 in view of the previously applied prior art reference are found persuasive. That is, Jeon fails to teach the combination of limitations of claim 11 for the reasons argued. An updated search and consideration of the prior art was performed, but no references were found to teach or suggest the combination of subject matter in independent claim 11. Accordingly, independent claim 11 and claims 12-15 that depend therefrom are allowable over the prior art of record.
Response to Arguments
7. The amendments to claims 2 and 14 have overcome the previously objections to claims 2 and 14. Accordingly, the objections to claims 2 and 14 are withdrawn in view of the amendments.
8. The arguments with respect to the 35 U.S.C. 102 rejections of independent claims 1 and 17 have been fully considered but are moot in view of the claim amendments and new grounds of rejections.
9. The arguments with respect to the 35 U.S.C. 102 rejections of independent claim 11 incorporating the subject matter of dependent claim 16 are found persuasive. Accordingly, the 35 U.S.C. 102 rejections of claims 11-15 are withdrawn in view of the amendments and arguments.
Conclusion
10. 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.
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/Nicholas Ulrich/Primary Examiner, Art Unit 2179
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