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
Status of the Application
The following is a Final Office Action in response to communication received on 7/20/2026. Claims 1-20 have been examined in this application.
Response to Amendment
Applicant’s amendments to claims 1, 3, 5, 15-16 and 20 are acknowledged.
Response to Arguments
On Remarks page 11, Applicant argues that the claims are not directed towards an abstract idea. The Examiner respectfully disagrees.
It is a mental process and or certain method of organizing human activities step to collect actionable items (e.g. access actionable item data) from a plurality (first and second) of sources (tools) and the information to be in disparate (unlike) formats, as broadly recited in the claims see argued access step of claim 1. The additional argued element as broadly recited in the claims that the specific tool is “software development” merely results in apply it or generally linking it to the field of computers as discussed in the 101 rejection below.
On Remarks page 11, Applicant argues that the machine learning model is not generically recited. The Examiner respectfully disagrees. The claims recite determine, via a model, by analyzing the action item disparate (unlike) data to create a prioritized action item suggestion set (list). This is a mental process step or certain method of organizing human activity step of using a model (set of rules) to determine a prioritized list (set) based on analyzing actions in different formats (disparate), see determine step of claim 1.
The additional element that the model is machine learning as broadly recited in the claims merely results in apply it. Beyond the abstract idea, the additional element in the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here as the claims recite a result-oriented solution and lack details as to how the computer performs the modifications, which was equivalent to the words "apply it".
Further with respect to the additional element of machine learning, there are not details about how the machine learning model operates to derive that information other than it being used. The machine learning model is used to generally apply the abstract idea without placing any limitation on how the machine learning operates to derive the information. The claim omits any details as to how the machine learning model solves a technical problem and instead only recites the idea of a solution or outcome. The claim invokes a generic machine learning model rather than purporting to improve the technology or computers. Further the limitations of machine learning could be considered nothing more than generally linking it to the field of computers. Additionally see for reference USPTO Example 48. Therefore the Examiner respectfully disagrees.
As to Applicant’s arguments on page 11 with respect to paragraph 0114 and in particular Applicant’s citation of “nor are the key indicators necessarily selectable by a human” the Examiner has carefully considered this part of Applicant’s specification however the Examiner disagrees with Applicant’s arguments. Here it appears applicant’s specification is merely stating that a human does not have to select the key indicators, rather this being done by machine learning. This merely results in apply it level claiming as discussed above (see section 3). Specifically it is a mental process or certain method of organizing human activity step of user selecting a key indicator (like an actionable item), therefore part of the abstract idea. The additional element of this instead being done by a machine learning model in the broad recitation of paragraph 0114 merely results in apply it or generally linking it to the field of computers as discussed above and in the 101 rejection below. Here this argued section does not disclose an improvement in machine learning (see MPEP 2106.05(a)), rather the specification merely discusses using machine learning (artificial intelligence) to generally aggregate data at a broad result based determination which results in apply it level claiming (as discussed above in section 3).
As to Applicant’s arguments on page 12, with respect to a practical application based on refining the model based on feedback. The Examiner respectfully disagrees. As recited in the claims it is a mental process and or certain method of organizing human activity to update a model (set of rules) over time based on feedback, to make a better determination over time, therefore part of the abstract idea. The additional element that the model is a “machine learning” model as recited in the claims recites no more than apply it or generally linking it to the field of computers as discussed in section 3 above.
As to Applicant’s argument on page 12 with respect to paragraph 0029 of the specification as filed, the Examiner has carefully considered Applicant’s arguments however the Examiner respectfully disagrees. Here Applicant’s specification really discusses the abstract idea (mental process or certain method of organizing human activities) of aggregating action items data across sources (tools) to determine a prioritized list. This is a mental process step and or certain method of organizing human activity, as broadly recited herein in the claims. Therefore this is a part of the abstract idea and therefore does not result in a practical application and or significantly more.
MPEP 2106.05(a) clearly states improvements to the abstract idea are not improvements to computer and or technology, cited herein:
Consideration of improvements is relevant to the eligibility analysis regardless of the technology of the claimed invention. That is, the consideration applies equally whether it is a computer-implemented invention, an invention in the life sciences, or any other technology. See, e.g., Rapid Litigation Management v. CellzDirect, Inc., 827 F.3d 1042, 119 USPQ2d 1370 (Fed. Cir. 2016), in which the court noted that a claimed process for preserving hepatocytes could be eligible as an improvement to technology because the claim achieved a new and improved way for preserving hepatocyte cells for later use, even though the claim is based on the discovery of something natural. Notably, the court did not distinguish between the types of technology when determining the invention improved technology. However, it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. For example, in Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.
On Remarks page 14, Applicant argues the prior art with respect to Applicant’s amendments. Specifically, Applicant argues the amendment of “access actionable item data from a plurality of software development tools, comprising at least a first software development tool and a second software development tool, wherein the actionable item data comprises candidate actionable items originating from at least the first software development tool and the second software development tool.” The Examiner has updated the prior art rejection below to reflect Applicant’s amendments.
Specifically Chung teaches this broad limitation as Chung clearly teaches through software aggregating information to provide suggested alerts on a user display of work to be completed for example like immediate attention required (see paragraphs 0148-0150 and Figure 3A), where the alert or notification may be reporting a new bug in a software application to a manager of a team responsible for information security (See paragraph 0066). It is further noted in paragraph 0120 the predictive system uses input from various sources including user inputs with a particular content like a software development company, user inputs associated with a particular group for example a particular software development group, or user inputs associated with a particular product like a software project or software product, all of which can be considered the first or second software development tool from which inputs are used in the predictive system.
Therefore the Examiner respectfully disagrees and maintains the rejection with respect to Chung.
On remarks pages 14-15, Applicant argues the dependent claims in view of the independent claims. However the Examiner finds that Chung teaches the amended claims as detailed above in section 6, therefore the Examiner finds the argument not persuasive.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-14 recite a machine as the claims recite an apparatus with a processor, memory, and computer code performing functions. Claims 15-19 recite a process as the claims recite a method. Claim 20 recite an article of manufacture as the claims recite a non-transitory computer readable medium.
The claim(s) 1-20 recite(s) collecting data related to project management, analyzing it, displaying prioritized actions or results based of the collection and analysis and additional user actions, and updating that information over time based on feedback.
Collecting data related to project management, analyzing it, displaying prioritized actions or results based of the collection and analysis and additional user actions, and updating that information over time based on feedback include observations, evaluations, judgments and opinions that can be performed in the human mind or with pen and paper and accordingly the claims recite a mental process.
Further collecting data related to project management, analyzing it, displaying prioritized actions or results based of the collection and analysis and additional user actions, and updating that information over time based on feedback include subject matter relating to managing personal behavior or relationships or interactions between people including social activities, teachings, and following rules or instructions accordingly the claims recite certain methods of organizing human activities.
Mental processes and certain methods of organizing human activities are in the groupings of enumerated abstracts ideas, and hence the claims recite an abstract idea.
This judicial exception is not integrated into a practical application because the claims merely recite limitations that are not indicative of integration into a practical application in that the claims merely recite:
(1) Adding the words “apply it” ( or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), (2) Generally linking the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)), and (3) Adding insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
Specifically as recited in the claims:
As per claim 1, the claims recite mental process and certain methods of organizing human activity steps, specifically a human could receive a request, access history data including items to be completed, determine a suggestion based on the accessed data from disparate formats, generate a prioritized list, output the list or suggestions in response to the request, and update future selections from a set of rules (model) based on feedback as broadly recited in the claims. This is part of the abstract idea.
The additional elements that these limitations mental process or certain method of organizing human activities are instead being performed by stored software running a processor “ at least one processor, and at least one memory including program code, the at least one memory and the program code configured to, with the at least one processor, cause the apparatus to at least”, interfaces, and by a “computing device” merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here as the claims recite a result-oriented solution and lacked details as to how the computer performs the modifications, which was equivalent to the words "apply it".
Further mental process or certain method of organizing human activity limitations that instead recite the limitations being performed by stored software running a processor “ at least one processor, and at least one memory including program code, the at least one memory and the program code configured to, with the at least one processor, cause the apparatus to at least”, interfaces, and by a “computing device” merely results in generally linking the use of the judicial exception to the field of computers.
Further, the additional elements that the determinations are done via a machine learning model and that the tools or environment that provide the information are “software development” merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here the claims recite a result-oriented solution and lack details as to how the computer performs the modifications, which was equivalent to the words "apply it".
Further with respect to the additional elements of machine learning or software development, there are not details about how the machine learning model or software development operates to derive that information other than it being used. The machine learning and software development are used to generally apply the abstract idea without placing any limitation on how the machine or software development learning operates to derive the information. The claim omits any details as to how the machine learning or software development solves a technical problem and instead only recites the idea of a solution or outcome. The claim invokes a generic machine learning model or software development rather than purporting to improve the technology or computers. Further the limitations of software development and machine learning could be considered nothing more than generally linking it to the field of computers. Additionally see for reference USPTO Example 48.
As per claim 2, the claims recite mental process and certain methods of organizing human activity steps, specifically prioritizing suggestions based on a project identifier and a team member identifier. This is part of the abstract idea. There are no additional elements beyond those previously discussed above including interface from which the claim depends.
As per claim 3, the claims recite mental process and certain methods of organizing human activity steps of specifically querying a repository based on a team member and project identifier. For example looking at records or files, and then retrieving suggestions based on the query. This is part of the abstract idea. There are no additional elements beyond those previously discussed above including interface and software development from which the claim depends.
As per claim 4, the claims recite mental process and certain methods of organizing human activity steps specifically determining suggestions based on results of the query and ranking when there are more than two suggestions and returning the information for display. This is part of the abstract idea.
The additional elements that this is done programmatically merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here the claims recite a result-oriented solution and lacked details as to how the computer performs the modifications, which was equivalent to the words "apply it".
Further limitations that could be performed by a human or humans that instead recite the limitations being performed programmatically merely results in generally linking the use of the judicial exception to the field of computers.
As per claim 5, it is a certain method of organizing human activity or mental process step to make a model (rules) based on learned or collected information (e.g. trained), as broadly recited in the claims (e.g. the level of abstraction recited). For example when X happens perform Y based on previous data. Or for example when A happens G is the result, based on previous learned data, as broadly recited in the claims. It is a human activity or mental process step to perform this with like or unlike (disparate) data. This is part of the abstract idea.
As amended, given the broad recitation in the claims it is further a mental process or certain method of organizing human activity step to correlate disparate data formats (unlike) comprising two or more of build or deployment data, code review data, security vulnerability data, or issue tracking data, as broadly recited in the claims. There is no detail as to how this data is presented or correlated, this could therefore be mere correlation of lists, results, or rules, which is a mental process or certain method of organizing human activity given the broad result based recitation in the claims. Therefore this is part of the abstract idea.
The additional element that the tools or environment that provide the information are “software development” or the rule or model is “machine learning” merely results in apply it or generally linking it to the field of computer as discussed above in claim 1.
As per claim 6, the claims recite mental process and certain methods of organizing human activity limitations of creating or establishing a model based on previous data. This is part of the abstract idea.
The additional elements that this model is machine learning and the create or establish is done by generic training merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here the claims recite a result-oriented solution and lacked details as to how the computer performs the modifications, which was equivalent to the words "apply it".
Specifically here there are not details about the specific training or the machine learning or how it operates to derive that information other than it being used. The machine learning and training are used to generally apply the abstract idea without placing any limitation on how the programming or the machine learning operates to derive the information. The claim omits any details as to how the machine learning or training solves a technical problem and instead only recites the idea of a solution or outcome. The claim invokes a generic machine leaning or training rather than purporting to improve the technology or computers (additionally see for reference USPTO Example 48).
Further limitations that recite mental process and or certain methods of organizing human activity that instead recite the limitations of the model is machine learning and the create or establish is done by generic training merely results in generally linking the use of the judicial exception to the field of computers.
As per claim 7, the claims recite certain methods of organizing human activity and mental processes specifically selecting an action and be provided additional information from another or the same user by for example looking it up in another part of the same or different document (for example like a user looking a table of contents for a specific selection and then flipping to the corresponding desired section). This is part of the abstract idea.
The additional elements that this is performed by software running on a computer and that the display is an interface is addressed above in claim 1.
The additional elements that the selection is a “hover” feature and providing information in real time merely results in apply it. Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here the claims recite a result-oriented solution and lacked details as to how the computer performs the modifications, which is equivalent to the words "apply it".
Further mental process and certain methods of organizing human activities that instead recite the selection is performed by a hover feature and providing information in real time merely results in generally linking the use of the judicial exception to the field of computers.
Further this hover feature can be considered additionally or alternatively to be mere data gathering in conjunction with the abstract idea (Adding insignificant extra-solution activity to the judicial exception).
As per claim 8, the claims recite mental process and certain methods of organizing human activities of specifically detecting a request in response to a user interaction or request. Specifically one user requesting information from another user. This is part of the abstract idea. The additional elements that this is instead done on an “interface” merely results in apply it or generally linking it to the field of computers as discussed above in claim 1.
As per claim 9, the claims recite mental process and certain methods of organizing human activities of specifically displaying a selectable selection or recommendation on a display. A user can select by for example circling it to request more information from another user like a secretary or employee. This is part of the abstract idea. The additional elements that these limitations are being performed by software running on a computer and the display is an interface merely results in apply it or generally linking it to the field of computers as discussed above in claim 1.
As per claim 10, the claims recite mental process and certain methods of organizing human activities of specifically a human could cross out content that they no longer want displayed to them and in the future information brought to them by for example employees or secretaries would no longer include that information. This is part of the abstract idea.
The additional elements that these limitations are being performed by software running on a computer and the display is an interface merely results in apply it or generally linking it to the field of computers as discussed above in claim 1.
As per claim 11, the claims recite mental process and certain methods of organizing human activities steps, specifically requesting additional information, and then based on that additional information decide it’s no longer relevant and ask employees or secretaries for example to no longer bring them information on that topic. This is part of the abstract idea. The additional elements that these limitations are being performed by software running on a computer and the display is an interface merely results in apply it or generally linking it to the field of computers as discussed above in claim 1.
As per claim 12, the claims recite mental process and certain methods of organizing human activities steps specifically selecting information to be provided additional information related to why that information was provided to them or to be provided information on how to fix the action. This is part of the abstract idea.
The additional elements that these limitations are being performed by software running on a computer and the display is an interface merely results in apply it or generally linking it to the field of computers as discussed above in claim 1.
Further the additional elements that the selection is a “embedded tool link” and that the information provided to a user is an access module providing access to a software development tool merely results in apply it. Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g. to receive, store or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here the claims recite a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words "apply it".
Further that these mental process and certain methods of organizing human activities steps instead recite the limitations of the selection is a “embedded tool link” and that the information provided to a user is an access module providing access to a software development tool merely results in generally linking the use of the judicial exception to the field of computers.
As per claim 13, the claims recite mental process and certain methods of organizing human activity steps specifically a human could mark a task complete or finished and update a checklist or have a secretary or employee do such. This is part of the abstract idea.
The additional elements that these limitations are being performed by software running on a computer and the display is an interface merely results in apply it or generally linking it to the field of computers as discussed above in claim 1.
As per claim 14, the claims recite mental process and certain methods of organizing human activity steps specifically a human could request to see additional information collected by another user like an employee or secretary. This is part of the abstract idea.
The additional elements that these limitations are being performed by software running on a computer and the display is an interface merely results in apply it or generally linking it to the field of computers as discussed above in claim 1.
As per claim 15, the claims recite mental process and certain methods of organizing human activity steps specifically receive a request, access history data including actions in disparate (unlike) formats, determine a suggestion based on the accessed data where this includes work to be complete, generate a prioritized list, output the list or suggestions in response to the request, and update the set of rules (model) to complete the suggestions based on feedback received, as broadly recited in the claims. This is part of the abstract idea.
The additional elements that these mental process and certain methods of organizing human activity limitations instead include the displays being interfaces and being displayed/performed by “a computing device” merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here the claims recite a result-oriented solution and lacked details as to how the computer performed the modifications, which is equivalent to the words "apply it".
Further mental process and certain method of organizing human activity limitations that instead recite the additional elements that the displays are interfaces and being displayed/performed by “a computing device” merely results in generally linking the use of the judicial exception to the field of computers.
The additional elements that the determinations are done via a machine learning model and that the tools or environment that provide the information are “software development” merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here as the claims recite a result-oriented solution and lack details as to how the computer performs the modifications, which is equivalent to the words "apply it".
Further with respect to machine learning or software development, there are not details about how the machine learning or software development operates to derive that information other than it being used. The machine learning and software development are used to generally apply the abstract idea without placing any limitation on how the machine or software development learning operates to derive the information. The claim omits any details as to how the machine learning or software development solves a technical problem and instead only recites the idea of a solution or outcome. The claim invokes a generic machine learning model or software development rather than purporting to improve the technology or computers. Further the limitations of software development and machine learning could be considered nothing more than generally linking it to the field of computers. Additionally see for reference USPTO Example 48.
As per claim 16, the claims recite mental process and certain methods of organizing human activity limitations specifically querying a repository based on a team member and project identifier. For example looking at records or files, and then retrieving suggestions based on the query. This is part of the abstract idea. The additional element of the display being an interface and that information or tools information is from is software development is addressed above in claim 15.
As per claim 17, the claims recite mental process and certain methods of organizing human activity limitations specifically determining suggestions based on results of the query and ranking when there are more than two suggestions and returning the information for display. This is part of the abstract idea.
The additional elements that this is done programmatically merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here as the claims recite a result-oriented solution and lacked details as to how the computer performs the modifications, which was equivalent to the words "apply it".
Further limitations that recite mental process and certain methods of organizing human activity that instead recite the limitations being performed programmatically merely results in generally linking the use of the judicial exception to the field of computers.
As per claim 18, the claims recite mental process and certain methods of organizing human activity limitations specifically selecting an action and being provided additional information from another user or the same user by for example looking it up in another part of the same or different document (for example like a user looking a table of contents for a specific selection and then flipping to the corresponding desired section). This is part of the abstract idea.
The additional elements that this is performed by software running on a computer and that the display is an interface and being performed in real time is addressed above in claim 16.
The additional elements that the selection is a “hover” feature and providing information in real time merely results in apply it. Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here the claims recite a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words "apply it".
Further mental process and certain methods of organizing human activities that instead recite selection is performed by a hover feature and providing information in real time merely results in generally linking the use of the judicial exception to the field of computers.
Further this hover feature can be considered additionally or alternatively to be mere data gathering in conjunction with the abstract idea (Adding insignificant extra-solution activity to the judicial exception).
As per claim 19, the claims recite mental process and certain methods of organizing human activity limitations specifically selecting information to be provided additional information related to why that information was provided to them or to be provided information on how to fix the action. Further it is a mental process and certain method of organizing human activity to mark a task complete or finished and update a checklist or have a secretary or employee do such. This is part of the abstract idea.
The additional elements that in these limitations the display is an interface and the tools the information is from is software development merely results in apply it or generally linking it to the field of computers as discussed above in claim 15.
Further the additional elements that the selection is a “embedded tool link” and that the information provided to a user is an access module providing access to a software development tool merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here the claims recite a result-oriented solution and lacked details as to how the computer performs the modifications, which is equivalent to the words "apply it".
Further limitations that recite mental process and certain method of organizing human activity that instead recite the limitations of the selection is a “embedded tool link” and that the information provided to a user is an access module providing access to a software development tool merely results in generally linking the use of the judicial exception to the field of computers.
As per claim 20, the claims recite mental process and certain methods of organizing human activity specifically receiving a request, access history data including actions in disparate formats (unlike), determine a suggestion based on the accessed data which is related to work to be completed, generate a prioritized list, output the list or suggestions in response to the request, and update the set of rules (model) used to make the suggestions based on feedback, as broadly recited in the claim. This is part of the abstract idea.
The additional elements that these limitations that could be performed by a human or humans are instead being performed by stored software running a processor “a computer program product for outputting a prioritized actionable item insight interface component to a project management user interface, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer readable program code portions comprising an executable portion configured to”, the displays being interfaces, and being displayed/performed on “a computing device” merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here as the claims recite a result-oriented solution and lacked details as to how the computer performed the modifications, which is equivalent to the words "apply it".
Further mental process and certain method of organizing human activities limitations that instead recite the limitations being performed by a stored software running a processor “ a computer program product for outputting a prioritized actionable item insight interface component to a project management user interface, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer readable program code portions comprising an executable portion configured to”, the displays being interfaces, and being displayed on “a computing device” merely results in generally linking the use of the judicial exception to the field of computers.
The additional elements that the determinations are done via a machine learning model and that the tools or environment that provide the information are “software development” merely results in apply it.
Specifically here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further the claim recites only the idea of a solution or outcome in that the claim fails to recite details of how a solution to a problem is accomplished. Here the claim limitations attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, therefore does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words apply it. This is the case here the claims recite a result-oriented solution and lack details as to how the computer performs the modifications, which is equivalent to the words "apply it".
Further with respect to additional elements of machine learning or software development, there are not details about how the machine learning or software development operates to derive that information other than it being used. The machine learning and software development are used to generally apply the abstract idea without placing any limitation on how the machine or software development learning operates to derive the information. The claim omits any details as to how the machine learning or software development solves a technical problem and instead only recites the idea of a solution or outcome. The claim invokes a generic machine learning model or software development rather than purporting to improve the technology or computers. Further the limitations of software development and machine learning could be considered nothing more than generally linking it to the field of computers. Additionally see for reference USPTO Example 48.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims merely recite limitations that are not indicative of an inventive concept (“significantly more”) in that the claims merely recite: (1) Adding the words “apply it” ( or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), (2) Generally linking the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)), and (3) Adding insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)), as detailed above with respect to the practical application step.
Further with respect to the Adding insignificant extra-solution activity to the judicial exception or mere data gathering, when reconsidered this is merely
(1) Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (see MPEP 2106.05(d) and Berkheimer Memo). Specifically:
(a) hovering on an interface for selection (See claims 7 and 18)
- Farnsworth et al. (United States Patent Application Publication Number: US 2009/0287470) paragraph 0042 “accordingly, as is known in the art, the user interface routine 50 may present the original the subject line 92 in a tipstrip, or pop-up, when a user hovers a cursor, or other selection device, over the abbreviated text string 63”
- Baldwin et al. (United States Patent Application Publication Number: US 2012/0166220) paragraph 0068 “ For example, a clinician 216 may hover a pointer, cursor, or other selection device as is known in the art, over a listed quality measure 420, 426, 428 to reveal a popup window 438”
- Skomra et al. (United States Patent Application Publication Number: US 2014/0357295) paragraph 0249 “By selecting any individual asset icon displayed on the map, for example, by using a user input selection device such as a mouse ( “clicking”, “hovering”, “double clicking”, etc., as known in the art), a label for the selected asset is shown, which label may be subsequently dismissed by selection of the “X” symbol within the label”
-Parker et al. (United States Patent Application Publication Number: US 2015/0019569) paragraph 0148 “The user may indicate selection of segment 1807 by any means known to a person of ordinary skill in the art including clicking on segment 1807 using any kind of mouse, hovering over segment 1807 for a predetermined amount of time using any kind of cursor, touching segment 1807 as displayed using any kind of touch screen, gesturing over segment 1807, and the like. In response to receiving the indication that the user has selected segment 1807, visualization system 115 may visually highlight a prediction path from center segment 1801 to selected segment 1807.”
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-6, 8-9, 12, 15-17, and 20 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable over Chung (United States Patent Application Publication Number: US 2021/0081459)
As per claim 1, Chung teaches An apparatus for outputting a prioritized actionable item insight interface component (see abstract and Figures 3a-3b, Examiner’s note: collaboration tool for which should be acted on first).
to a project management user interface, (see paragraphs 0038-0039, Examiner’s note: project management).
In a multi-resource software development environment (see paragraphs 0078, 0093, 0107, and 0120, Examiner’s note: teaches using many different types of software environment interactions to determine information including click through, hovers, syntactically similar, metadata, dwell time, average scroll speed, time to interaction, number of interactions events with respect to specific content, specific types of companies like software companies, etc.).
the apparatus comprising at least one processor, and at least one memory including program code, the at least one memory and the program code configured to, with the at least one processor, cause the apparatus to at least: (see paragraph 0017-0018, Examiner’s note: software stored in a medium running on a computer).
detect a prioritized actionable item insight interface component request; (see paragraphs 0110-0111, Examiner’s note: providing prioritized actions to users when the user requests it or accordingly to a determined change).
access actionable item data from a plurality of software development tools, comprising at least a first software development tool and a second software development tool, wherein the actionable item data comprises candidate actionable items originating from at least the first software development tool and the second software development tool, (see paragraphs 0066, 0120, 0148-0150 and Figure 3A, Examiner’s note: Chung teaches this broad limitation as Chung clearly teaches through software aggregating information to provide suggested alerts on a user display of work to be completed for example like immediate attention required (see paragraphs 0148-0150 and Figure 3A), where paragraph 0066 teaches the alert or notification may be reporting a new bug in a software application to a manager of a team responsible for information security. It is further noted in paragraph 0120 the predictive system uses input from various sources including user inputs with a particular content like a software development company, user inputs associated with a particular group for example a particular software development group, or user inputs associated with a particular product like a software project or software product, all of which can be considered the first or second software development tool from which inputs are used in the predictive system).
The candidate actionable items comprising disparate data formats (see paragraphs 0078, 0093, 0107, and 0120, Examiner’s note: teaches using many different types of software environment interactions to determine information including click through, hovers, syntactically similar, metadata, dwell time, average scroll speed, time to interaction, number of interactions events with respect to specific content, specific types of companies like software companies, etc. These are all different disparate data, as they are not alike. This is consistent with Applicant’s specification at paragraphs 0113-0114)).
and including at least one software development item to be completed; (see paragraphs 0148-0150 and Figure 3A, Examiner’s note: further software aggregating information to provide suggested alerts on a user display of work to be completed for example like immediate attention required which reads on the broad “software development work to be completed” (see paragraphs 0148-0150 and Figure 3A)).
determine, via a machine learning model configured to analyze the disparate data formats of the candidate actionable items, a prioritized actionable item suggestion set based at least in part on the actionable item data, the prioritized actionable item suggestion set comprising at least one prioritized actionable item; (see paragraphs 0093, 0112-0114, and 0136, Examiner’s note: predictive model that is trained based on previously received user inputs to provide outputs to users).
generate a prioritized actionable item insight interface component comprising the prioritized actionable item suggestion set; (see paragraphs 0057, 0062, 0149-0150, and 0157, Examiner’s note: teaches ranking actions and providing content based on ranks)
output the prioritized actionable item insight interface component for rendering to a project management user interface of a computing device associated with the prioritized actionable item insight interface component request. (see Figure 3a and paragraphs 0083 and 0150, examiner’s note: can sort by score. Further teaches a client uses a device).
And refine the machine leaning model based on one or more user feedback data objects received from the computing device, the user feedback data objects generated based on user interaction with the prioritized actionable item insight interface component (see paragraph 0113-0117, Examiner’s note: predictive model that is updated or trained based on previous interactions).
As per claim 2, Chung teaches
wherein the prioritized actionable item insight interface component request is associated with a project identifier and a team member identifier (see paragraphs 0066-0067, 0070, 0077-0078, 0092-0093, and 0101, Examiner’s note: teaches providing different information for different users where they can be based on their role in an organization and the projects).
As per claim 3, Chung teaches
wherein accessing the actionable item data from the plurality of software development tools comprises: querying an insight component management repository based on at least the project identifier and the team member identifier, wherein the insight component management repository aggregates data from the plurality of software development tool; and retrieving one or more the candidate actionable items associated with the project identifier and the team member identifier (see paragraphs 0069-0070, 0092-0093, 0107, and 0113-0114, Examiner’s note: teaches querying a database to determine information).
As per claim 4, Chung teaches
wherein determining the prioritized actionable item suggestion set comprises :programmatically determining the at least one prioritized actionable item based on an analysis of the one or more candidate actionable items returned by the query;
in an instance wherein the query returns two or more prioritized actionable items, ranking the two or more prioritized actionable items; (see paragraphs 0057, 0062, 0149-0150, and 0157, Examiner’s note: teaches ranking actions and providing content based on ranks)
and generating the prioritized actionable item suggestion set based on the ranked prioritized actionable items. (see Figure 3a and paragraphs 0083 and 0150, examiner’s note: can sort by score. Further teaches a client uses a device).
As per claim 5, Chung teaches
Wherein the first software development tool is associated with a first software development operation and the second software development tool is associated with a second software development operation different from the first software development operation, and wherein the machine learning model is trained to identify correlations among the disparate data formats, the disparate data formats comprising two or more of built or deployment data ,code review, security vulnerability data, or issue tracking data (see paragraphs 0120 and 0066, Examiner’s note: in paragraph 0120 the predictive system uses input from various sources including user inputs with a particular content like a software development company, user inputs associated with a particular group for example a particular software development group, or user inputs associated with a particular product like a software project or software product, all of which can be considered the first or second software development tool from which inputs are used in the predictive system. Further paragraph 0066 teaches reporting a bug in a software application that relates to user privacy. The above data of software development and a bug in software being reported to a team manager responsible for information security in paragraphs 0120 and 0066 relate to issue tracking and building or deployment data, code review data, security vulnerability thereby meeting the claim as required by the limitation of “two or more of”).
As per claim 6, Chung teaches
wherein the machine learning model is trained using actionable item data. (see paragraphs 0093, 0112-0114, and 0136, Examiner’s note: predictive model that is trained based on previously received user inputs to provide outputs to users).
As per claim 8, Chung teaches
wherein detecting the prioritized actionable item insight interface component request is in response to user interaction with the project management user interface (see paragraphs 0110-0111, Examiner’s note: providing action items based on changes in content or user requests).
As per claim 9, Chung teaches
wherein the program code is further configured to, with the at least one processor, cause the apparatus to: (see paragraph 0017-0018, Examiner’s note: software stored in a medium running on a computer).
cause rendering of a selectable insight interface control elements to the project management user interface, wherein the selectable insight interface control elements is configured for enabling user control of the prioritized actionable item insight interface component (see paragraphs 0049 and 0148, Examiner’s note: hovering and buttons that if pressed by the users will be provide additional content or context to the user).
As per claim 12, Chung teaches
wherein the program code is further configured to, with the at least one processor, cause the apparatus to: (see paragraph 0017-0018, Examiner’s note: software stored in a medium running on a computer).
detect user interaction with an embedded tool link associated with a selected prioritized actionable item; and generate and transmit an access module to the project management user interface, the access module providing access to a software development tool associated with the selected prioritized actionable item (see paragraph 0136, 0148, and 0157, Examiner’s note: user selects a button like 308b and is provided additional content as to why the selected is of high urgency, this is access to a “software development tool” as broadly recited in the claims as this the results of the machine learning, paragraphs 0136 and 0157).
As per claim 15, Chung teaches A method for outputting a prioritized actionable item insight interface component (see abstract and Figures 3a-3b, Examiner’s note: collaboration tool for which should be acted on first).
to a project management user interface (see paragraphs 0038-0039, Examiner’s note: project management).
In a multi-resource software development environment, the method comprising: (see paragraphs 0078, 0093, 0107, and 0120, Examiner’s note: teaches using many different types of software environment interactions to determine information including click through, hovers, syntactically similar, metadata, dwell time, average scroll speed, time to interaction, number of interactions events with respect to specific content, specific types of companies like software companies, etc.).
detecting a prioritized actionable item insight interface component request; (see paragraphs 0110-0111, Examiner’s note: providing prioritized actions to users when the user requests it or accordingly to a determined change).
accessing actionable item data from a plurality of software development tools, comprising at least a first software development tool and a second software development tool, wherein the actionable item data comprises candidate actionable items originating from at least the first software development tool and the second software development tool, (see paragraphs 0066, 0120, 0148-0150 and Figure 3A, Examiner’s note: Chung teaches this broad limitation as Chung clearly teaches through software aggregating information to provide suggested alerts on a user display of work to be completed for example like immediate attention required (see paragraphs 0148-0150 and Figure 3A), and paragraph 0066 teaches the alert or notification may be reporting a new bug in a software application to a manager of a team responsible for information security. It is further noted in paragraph 0120 the predictive system uses input from various sources including user inputs with a particular content like a software development company, user inputs associated with a particular group for example a particular software development group, or user inputs associated with a particular product like a software project or software product, all of which can be considered the first or second software development tool from which inputs are used in the predictive system).
The candidate actionable items comprising disparate data formats; (see paragraphs 0078, 0093, 0107, and 0120, Examiner’s note: teaches using many different types of software environment interactions to determine information including click through, hovers, syntactically similar, metadata, dwell time, average scroll speed, time to interaction, number of interactions events with respect to specific content, specific types of companies like software companies, etc. These are all different disparate data, as they are not alike. This is consistent with Applicant’s specification at paragraphs 0113-0114).
and including at least one software development item to be completed (see paragraphs 0148-0150 and Figure 3A, Examiner’s note: further software aggregating information to provide suggested alerts on a user display of work to be completed for example like immediate attention required which reads on the broad “software development work to be completed” (see paragraphs 0148-0150 and Figure 3A).
Determining, via a machine learning model configure to analyze the disparate formats of the candidate actionable items, (see paragraphs 0078, 0093, 0107, 0120, and 0136, Examiner’s note: teaches using many different types of software environment interactions to determine information including click through, hovers, syntactically similar, metadata, dwell time, average scroll speed, time to interaction, number of interactions events with respect to specific content, specific types of companies like software companies, etc. (see paragraphs 0078, 0093, 0107, and 0120). Further paragraph 0136 teaches machine learning model running on a computer (See paragraph 0136)).
a prioritized actionable item suggestion set based at least in part on the actionable item data, the prioritized actionable item suggestion set comprising at least one prioritized actionable item; (see paragraphs 0110-0111, Examiner’s note: providing prioritized actions to users when the user requests it or accordingly to a determined change).
generating a prioritized actionable item insight interface component comprising the prioritized actionable item suggestion set; (see paragraphs 0057, 0062, 0149-0150, and 0157, Examiner’s note: teaches ranking actions and providing content based on ranks)
outputting the prioritized actionable item insight interface component for rendering to a project management user interface of a computing device associated with the prioritized actionable item insight interface component request. (see Figure 3a and paragraphs 0083 and 0150, examiner’s note: can sort by score. Further teaches a client uses a device).
And refining the machine leaning model based on one or more user feedback data objects received from the computing device, the user feedback data objects generated based on user interaction with the prioritized actionable item insight interface component (see paragraph 0113-0117, Examiner’s note: predictive model that is updated or trained based on previous interactions).
As per claim 16, Chung teaches
wherein the prioritized actionable item insight interface component request is associated with a project identifier and a team member identifier, (see paragraphs 0066-0067, 0070, 0077-0078, 0092-0093, 0101, Examiner’s note: teaches providing different information for different users where they can be based on their role in an organization and the projects).
and wherein determining a prioritized actionable item suggestion set comprises: querying an insight component management repository based on at least the project identifier and the team member identifier, wherein the insight component management repository aggregates data from the plurality of software development tools; (see paragraphs 0057, 0062, 0149-0150, and 0157, Examiner’s note: teaches ranking actions and providing content based on ranks)
and retrieving one or more of the candidate actionable items associated with the project identifier and the team member identifier. (see Figure 3a and paragraphs 0083 and 0150, examiner’s note: can sort by score. Further teaches a client uses a device).
As per claim 17, Chung teaches
wherein determining the prioritized actionable item suggestion set comprises: programmatically determining at least one prioritized actionable item based on an analysis of the one or more candidate actionable items returned by the query; in an instance wherein the query returns two or more prioritized actionable items, ranking the two or more prioritized actionable items; (see paragraphs 0057, 0062, 0149-0150, and 0157, Examiner’s note: teaches ranking actions and providing content based on ranks)
and generating the prioritized actionable item suggestion set based on the ranked prioritized actionable items. (see Figure 3a and paragraphs 0083 and 0150, examiner’s note: can sort by score. Further teaches a client uses a device).
As per claim 20, Chung teaches A computer program product for outputting a prioritized actionable item insight interface component (see abstract and Figures 3a-3b, Examiner’s note: collaboration tool for which should be acted on first).
to a project management user interface, (see paragraphs 0038-0039, Examiner’s note: project management).
In a multi-resource software development environment (see paragraphs 0078, 0093, 0107, and 0120, Examiner’s note: teaches using many different types of software environment interactions to determine information including click through, hovers, syntactically similar, metadata, dwell time, average scroll speed, time to interaction, number of interactions events with respect to specific content, specific types of companies like software companies, etc.).
the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising an executable portion configured to: (see paragraph 0017-0018, Examiner’s note: software stored in a medium running on a computer).
access actionable item data from a plurality of software development tools, comprising at least a first software development tool and a second software development tool, wherein the actionable item data comprises candidate actionable items originating from at least the first software development tool and the second software development tool, (see paragraphs 0066, 0120, 0148-0150 and Figure 3A, Examiner’s note: Chung teaches this broad limitation as Chung clearly teaches through software aggregating information to provide suggested alerts on a user display of work to be completed for example like immediate attention required (see paragraphs 0148-0150 and Figure 3A), and further paragraph 0066 teaches the alert or notification may be reporting a new bug in a software application to a manager of a team responsible for information security. It is further noted in paragraph 0120 the predictive system uses input from various sources including user inputs with a particular content like a software development company, user inputs associated with a particular group for example a particular software development group, or user inputs associated with a particular product like a software project or software product, all of which can be considered the first or second software development tool from which inputs are used in the predictive system).
The candidate actionable items comprising disparate data formats (see paragraphs 0078, 0093, 0107, and 0120, Examiner’s note: teaches using many different types of software environment interactions to determine information including click through, hovers, syntactically similar, metadata, dwell time, average scroll speed, time to interaction, number of interactions events with respect to specific content, specific types of companies like software companies, etc. These are all different disparate data, as they are not alike. This is consistent with Applicant’s specification at paragraphs 0113-0114)).
and including at least one software development item to be completed; (see paragraphs 0148-0150 and Figure 3A, Examiner’s note: Further software aggregating information to provide suggested alerts on a user display of work to be completed for example like immediate attention required which reads on the broad “software development work to be completed” (see paragraphs 0148-0150 and Figure 3A).
Determine, via a machine learning model configured to analyze the disparate data formats of the candidate actionable items, a prioritized actionable item suggestion set based at least in part on the actionable item data, the prioritized actionable item suggestion set comprising at least one prioritized actionable item, (see paragraphs 0078, 0093, 0107, 0120, and 0136, Examiner’s note: teaches using many different types of software environment interactions to determine information including click through, hovers, syntactically similar, metadata, dwell time, average scroll speed, time to interaction, number of interactions events with respect to specific content, specific types of companies like software companies, etc. (see paragraphs 0078, 0093, 0107, and 0120). Further teaches in paragraph 0136 machine learning).
generate a prioritized actionable item insight interface component comprising the prioritized actionable item suggestion set; (see paragraphs 0057, 0062, 0149-0150, and 0157, Examiner’s note: teaches ranking actions and providing content based on ranks)
output the prioritized actionable item insight interface component for rendering to a project management user interface of a computing device associated with the detected prioritized actionable item insight interface component request. (see Figure 3a and paragraphs 0083 and 0150, examiner’s note: can sort by score. Further teaches a client uses a device).
And refine the machine leaning model based on one or more user feedback data objects received from the computing device, the user feedback data objects generated based on user interaction with the prioritized actionable item insight interface component (see paragraph 0113-0117, Examiner’s note: predictive model that is updated or trained based on previous interactions).
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) 7 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Chung (United States Patent Application Publication Number: US 2021/0081459) further in view of Degrazia (United States Patent Application Publication Number: US 2022/0020085).
As per claim 7, Chung teaches
wherein the program code is further configured to, with the at least one processor, cause the apparatus to: detect a hover user interaction corresponding to a selected prioritized actionable item of the prioritized actionable item suggestion set rendered to the prioritized actionable item insight interface component; identify an actionable item identifier associated with the selected prioritized actionable item corresponding to the detected hover user interaction; generate an informational interface component associated with the actionable item identifier, wherein the informational interface component comprises an actionable item relationship data object associated with the actionable item identifier; and output the informational interface component for rendering to the prioritized actionable item insight interface component in association with the selected prioritized actionable item (see paragraphs 0047, Examiner’s note: teaches a user interacting with a message after a hover).
While Chung clearly teaches providing a content in response to a hover, Chung does not expressly teach this happens in real time.
However, DeGrazia which is in the art of automated predictive information for a user interface (See abstract ) teaches this happens in real time (see paragraph 0074 and Figure 3B, Examiner’s note: teaches generating responses to hover in real time).
Before the effective filing date of the claimed invention it would have been obvious for one of ordinary skill in the art to have modified Chung with the aforementioned teachings from DeGrazia with the motivation of providing a common interface element of providing a response to a selection in real time (see DeGrazia paragraph 0074 and Figure 3B), when providing responses to selections on a user interface is known (see Chung paragraph 0047).
As per claim 18, Chung teaches
further comprising: detecting a hover user interaction corresponding to a selected prioritized actionable item of the prioritized actionable item suggestion set rendered to the prioritized actionable item insight interface component; identifying an actionable item identifier associated with the selected prioritized actionable item corresponding to the detected hover user interaction; generating an informational interface component associated with the actionable item identifier, wherein the informational interface component comprises an actionable item relationship data object associated with the actionable item identifier; and outputting the informational interface component for rendering to the prioritized actionable item insight interface component in association with the selected prioritized actionable item(see paragraphs 0047, Examiner’s note: teaches a user interacting with a message after a hover).
While Chung clearly teaches providing a content in response to a hover, Chung does not expressly teach this happens in real time.
However, DeGrazia which is in the art of automated predictive information for a user interface (See abstract ) teaches this happens in real time (see paragraph 0074 and Figure 3B, Examiner’s note: teaches generating responses to hover in real time).
Before the effective filing date of the claimed invention it would have been obvious for one of ordinary skill in the art to have modified Chung with the aforementioned teachings from DeGrazia with the motivation of providing a common interface element of providing a response to a selection in real time (see DeGrazia paragraph 0074 and Figure 3B), when providing responses to selections on a user interface is known (see Chung paragraph 0047).
Claim(s) 10, 13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Chung (United States Patent Application Publication Number: US 2021/0081459) further in view of Singh et al. (United States Patent Application Publication Number: US 2019/0102719).
As per claim 10, Chung teaches
wherein the program code is further configured to, with the at least one processor, cause the apparatus to: (see paragraph 0017-0018, Examiner’s note: software stored in a medium running on a computer).
Detect a prioritized actionable item insight interface component request; and perform corresponding actions (see paragraphs 0049 and 0148, Examiner’s note: hovering and buttons that if pressed by the users will be provide additional content or context to the user).
Chung does not expressly teach cancelling out or stopping a recommendation or more specifically as recited in the claims detect a suppress prioritized actionable item insight interface component request; and cause stopping of the rendering of the prioritized actionable item insight interface component.
However, Singh et al. which is in the art of recommendations (See abstract) teaches cancelling out or stopping a recommendation or more specifically as recited in the claims detect a suppress prioritized actionable item insight interface component request; and cause stopping of the rendering of the prioritized actionable item insight interface component (see Figure 6D and paragraph 0161, Examiner’s note: selection of the X to reject the service may remove the service from the recommendations tab and may cause the dashboard to refrain from displaying the service in future recommendations).
Before the effective filing date of the claimed invention it would have been obvious for one of ordinary skill in the art to have modified Chung with the aforementioned teachings from Singh et al. with the motivation of providing a common interface element of when you cancel out of something not displaying it anymore (see Singh et al. Figure 6D and paragraph 0161), when interacting with interface elements to provide information is known (see Chung paragraphs 0049 and 0148)
As per claim 13, Chung teaches
wherein the program code is further configured to, with the at least one processor, cause the apparatus to: (see paragraph 0017-0018, Examiner’s note: software stored in a medium running on a computer).
Chung does not expressly teach marking a task complete and updating the list based on the completion or more specifically as recited in the claims of receive a completion notification associated with the selected prioritized actionable item; update the prioritized actionable item suggestion set, wherein updating the prioritized actionable suggestion set comprises removing the selected prioritized actionable item; and cause rendering of the updated prioritized actionable item suggestion set to the prioritized actionable item insight interface component.
However, Singh et al. which is in the art of recommendations (See abstract) teaches marking a task complete and updating the list based on the completion or more specifically as recited in the claims of receive a completion notification associated with the selected prioritized actionable item; update the prioritized actionable item suggestion set, wherein updating the prioritized actionable suggestion set comprises removing the selected prioritized actionable item; and cause rendering of the updated prioritized actionable item suggestion set to the prioritized actionable item insight interface component (see Figure 6D and paragraph 0161, Examiner’s note: selection of mark as implemented, or save or later and moving it to another tab).
Before the effective filing date of the claimed invention it would have been obvious for one of ordinary skill in the art to have modified Chung with the aforementioned teachings from Singh et al. with the motivation of providing a common interface element of marking an element complete to move it off of a task list and update the list (see Singh et al. Figure 6D and paragraph 0161), when interacting with interface elements to provide information is known (see Chung paragraphs 0049 and 0148)
As per claim 19, Chung teaches
further comprising: detecting user interaction with an embedded tool link associated with a selected prioritized actionable item; generating and transmitting an access module to the project management user interface, the access module providing access to a corresponding software development tool of the plurality of software development tools associated with the selected prioritized actionable item; (see paragraph 0136, 0148, and 0157, Examiner’s note: user selects a button like 308b and is provided additional content as to why the selected is of high urgency, this is access to a “software development tool” as broadly recited in the claims as this the results of the machine learning, paragraphs 0136 and 0157).
Chung does not expressly teach marking a task complete and updating the list based on the completion or more specifically as recited in the claims of receiving a completion notification associated with the selected prioritized actionable item; updating the prioritized actionable item suggestion set, wherein updating the prioritized actionable suggestion set comprises removing the selected prioritized actionable item; and rendering the updated prioritized actionable item suggestion set to the prioritized actionable item insight interface component.
However, Singh et al. which is in the art of recommendations (See abstract) teaches marking a task complete and updating the list based on the completion or more specifically as recited in the claims of receiving a completion notification associated with the selected prioritized actionable item; updating the prioritized actionable item suggestion set, wherein updating the prioritized actionable suggestion set comprises removing the selected prioritized actionable item; and rendering the updated prioritized actionable item suggestion set to the prioritized actionable item insight interface component (see Figure 6D and paragraph 0161, Examiner’s note: selection of mark as implemented, or save or later and moving it to another tab).
Before the effective filing date of the claimed invention it would have been obvious for one of ordinary skill in the art to have modified Chung with the aforementioned teachings from Singh et al. with the motivation of providing a common interface element of marking an element complete to move it off of a task list and update the list (see Singh et al. Figure 6D and paragraph 0161), when interacting with interface elements to provide information is known (see Chung paragraphs 0049 and 0148)
Claim(s) 11 is rejected under 35 U.S.C. 103 as being unpatentable over Chung (United States Patent Application Publication Number: US 2021/0081459) further in view of Singh et al. (United States Patent Application Publication Number: US 2019/0102719) further Schulman et al. (United States Patent Application Publication Number: US 2022/0179527).
As per claim 11, Chung teaches
wherein the program code is further configured to, with the at least one processor, cause the apparatus to: (see paragraph 0017-0018, Examiner’s note: software stored in a medium running on a computer).
detect an expand prioritized actionable item insight interface component request; and cause rendering of the prioritized actionable item insight interface component. (see paragraphs 0049 and 0148, Examiner’s note: hovering and buttons that if pressed by the users will be provide additional content or context to the user).
Chung in view of Singh et al. does not expressly teach providing a cancelling out or stopping recommended content element or more specifically as recited in the claims subsequent to causing stopping of the rendering of the prioritized actionable item insight interface component
However, Schulman et al. which is in the art of computer interfaces (see abstract) teaches providing a cancelling out or stopping recommended content element or more specifically as recited in the claims subsequent to causing stopping of the rendering of the prioritized actionable item insight interface component (see paragraph 0037, Examiner’s note: teaches a user can expand an interface element and then remove items).
Before the effective filing date of the claimed invention it would have been obvious for one of ordinary skill in the art to have modified Chung in view of Singh et al. with the aforementioned teachings from Schulman et al with the motivation of providing a common user interface element that a user can expand and then remove items (see Schulman et al. paragraph 0037), when providing an interface a user can interact with and provide interactions to receive additional information is known (see Chung paragraphs 0049 and 0148).
Claim(s) 14 is rejected under 35 U.S.C. 103 as being unpatentable over Chung (United States Patent Application Publication Number: US 2021/0081459) further in view of Cheng et al. (United States Patent Application Publication Number: US 2019/0197364).
As per claim 14, Chung teaches
wherein the program code is further configured to, with the at least one processor, cause the apparatus to: (see paragraph 0017-0018, Examiner’s note: software stored in a medium running on a computer).
Chung does not expressly teach a show more feature by for example a button or more specifically as recited in the claims detect a show more prioritized actionable items request; and cause rendering of additional prioritized actionable items of the prioritized actionable item suggestion set to the prioritized actionable item insight interface component.
However, Cheng et al. which is in the art of interfaces and suggestions (see abstract and paragraphs 0122 and 0125) teaches a show more feature by for example a button or more specifically as recited in the claims detect a show more prioritized actionable items request; and cause rendering of additional prioritized actionable items of the prioritized actionable item suggestion set to the prioritized actionable item insight interface component (see paragraph 0125 and Figure 5, Examiner’s note: showing more information button).
Before the effective filing date of the claimed invention it would have been obvious for one of ordinary skill in the art to have modified Chung with the aforementioned teachings from Cheng et al. with the motivation of providing a common interface element of providing additional information beyond the top suggestions (see Cheng et al. paragraphs 0125 and Figure 5), when allowing a user to interact with an interface is known (See Chung paragraphs 0147-0149)
Conclusion
THIS ACTION IS MADE FINAL. 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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Wilde et al. (United States Patent Application Publication Number: US 2022/0343258) teaches a system and interface for tracking and aggregating projects (see abstract)
Ansar et al. (United States Patent Application Publication Number: US 2023/0289729) teaches a system for managing a mega project on an interface (see abstract and Figures 5-7)
Bezemer et al. (United States Patent Application Publication Number: US 2010/0153160) teaches providing a coherent view of a large set of disparate event related information for an organization related based on machine learning. This information can be from emails, meeting agenda and meeting minutes for example (see paragraph 0045 and Figures 11a-11b)
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/KIERSTEN V SUMMERS/Primary Examiner, Art Unit 3626
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