Abstract: Non-limiting examples of the present disclosure describe creation and management of a contact associated with a document. A contact for a document in a first application may be created. The contact may be used to add content, from a second application, to the document. The contact may be stored. Contact data for the contact may be transmitted to one or more processing devices. An exemplary created contact may be used to transfer content from one or more applications to a document of another application. Other examples are also described.

Abstract: A method and system for providing data imbalance detection and validation for a trained a ML model includes receiving a request to perform data imbalance detection on the trained ML model, identifying a feature of a dataset associated with the trained model for which data imbalance detection is to be performed, receiving access to the dataset, receiving access to the trained ML model, examining at least one of the dataset or outcome data generated by the trained ML model to determine a distribution of the feature or a distribution of the outcome data, and determining if the trained ML model exhibits data imbalance based at least in part on the distribution of the feature or the distribution of the outcome data.

Abstract: A method and system for performing semi or fully automatic data imbalance detection and correction in training a machine-learning (ML) model includes receiving a request to train the ML model, receiving access to a dataset for use in training the ML model, identifying a feature of the dataset for which data imbalance detection is to be performed, examining the dataset to determine a distribution of the feature across the dataset, determining if the distribution of the feature across the dataset indicates data imbalance, upon determining that the distribution of the feature across the dataset indicates data imbalance, identifying a desired distribution for the identified feature, selecting a subset of the dataset that corresponds with the selected feature and the desired distribution, and using the subset to train the ML model.

Abstract: A method and system for detecting imbalanced distribution of data that may signal bias in a dataset associated with training a machine-learning (ML) model includes receiving a request to perform data imbalance detection on the dataset associated with training the machine-learning (ML) model, identifying a feature of the dataset for which data imbalance detection is to be performed and examining the dataset to determine a distribution of the feature across the dataset. The result of the determination may then be presented in a user interface element to help identify data imbalance in the dataset.

Abstract: A method and system for providing tone detection and modification for a content segment may include receiving a request to detect a tone for the content segment, inputting the content segment into a first machine-learning (ML) model to detect the tone for the content segment, obtaining the detected tone as a first output from the first ML model, inputting the content segment into a second ML model for modifying the tone from the detected tone to a modified tone, obtaining at least one rephrased content segment as a second output from the second ML model, the rephrased content segment modifying the tone of the content segment from the detected tone to the modified tone, and providing at least one of the detected tone or the at least one rephrased content segment for display to a user.

Abstract: A semantic based document editor is provided. An application such as a document processing application displays previews of a document. The previews include semantic styles. In response to a selection of one of the previews, a semantic style associated with the selected preview is applied to a section of the document. The semantic style is rendered in the selected preview. A suggestion is displayed on the section. The suggestion identifies the section. The suggestion is also formatted based on the semantic style.

Abstract: Non-limiting examples of the present disclosure describe creation and management of a contact associated with a document. A contact for a document in a first application may be created. The contact may be used to add content, from a second application, to the document. The contact may be stored. Contact data for the contact may be transmitted to one or more processing devices. An exemplary created contact may be used to transfer content from one or more applications to a document of another application. Other examples are also described.

Abstract: Non-limiting examples of the present disclosure describe creation and management of a contact associated with a document. A contact for a document in a first application may be created. The contact may be used to add content, from a second application, to the document. The contact may be stored. Contact data for the contact may be transmitted to one or more processing devices. An exemplary created contact may be used to transfer content from one or more applications to a document of another application. Other examples are also described.

Abstract: The description relates to opportunity events. One example can filter events based upon at least one parameter from a profile of a user. The filtering can produce potential opportunity events for the user. The example can compare the potential opportunity events to the user profile utilizing a similarity threshold such that the potential opportunity events that satisfy the similarity threshold are considered opportunity events. The example can rank the opportunity events by confidence level of matching the user profile. The example can also automatically populate high ranking individual opportunity events onto a calendar of the user. The example can further notify the user about the automatically populating.

Abstract: A method and system for performing semi or fully automatic data imbalance detection and correction in training a machine-learning (ML) model includes receiving a request to train the ML model, receiving access to a dataset for use in training the ML model, identifying a feature of the dataset for which data imbalance detection is to be performed, examining the dataset to determine a distribution of the feature across the dataset, determining if the distribution of the feature across the dataset indicates data imbalance, upon determining that the distribution of the feature across the dataset indicates data imbalance, identifying a desired distribution for the identified feature, selecting a subset of the dataset that corresponds with the selected feature and the desired distribution, and using the subset to train the ML model.

Abstract: A method and system for correcting imbalanced distribution of data that may signal bias in a dataset associated with training a machine-learning (ML) model includes receiving a request to perform a data imbalance correction on a dataset associated with training a machine-learning (ML) model, identifying a feature of the dataset for which data imbalance correction is to be performed, identifying a desired distribution for the identified feature, selecting a subset of the dataset that corresponds with the selected feature and the desired distribution, and using the subset to train a ML model.

Abstract: A method and system for detecting imbalanced distribution of data that may signal bias in a dataset associated with training a machine-learning (ML) model includes receiving a request to perform data imbalance detection on the dataset associated with training the machine-learning (ML) model, identifying a feature of the dataset for which data imbalance detection is to be performed and examining the dataset to determine a distribution of the feature across the dataset. The result of the determination may then be presented in a user interface element to help identify data imbalance in the dataset.

Abstract: A method and system for providing data imbalance detection and validation for a trained a ML model includes receiving a request to perform data imbalance detection on the trained ML model, identifying a feature of a dataset associated with the trained model for which data imbalance detection is to be performed, receiving access to the dataset, receiving access to the trained ML model, examining at least one of the dataset or outcome data generated by the trained ML model to determine a distribution of the feature or a distribution of the outcome data, and determining if the trained ML model exhibits data imbalance based at least in part on the distribution of the feature or the distribution of the outcome data.

Abstract: Systems, methods, and software are disclosed herein for indicating a change to content in a document to a user. A document is displayed in a user interface to an application. Content then is introduced into the document from a source external to the document. After the content has been introduced into the document, the source of the content is queried for any changes to the content at the source. If a change has occurred, an indication of the change to the content at the source is introduced in the document.

Abstract: Non-limiting examples of the present disclosure describe creation and management of a contact associated with a document. A contact for a document in a first application may be created. The contact may be used to add content, from a second application, to the document. The contact may be stored. Contact data for the contact may be transmitted to one or more processing devices. An exemplary created contact may be used to transfer content from one or more applications to a document of another application. Other examples are also described.

Abstract: A user input is detected that triggers a contextual command bar to be surfaced. A commanding context, in an application that the user has open, is identified and a set of commands to be surfaced in the contextual command bar is identified, based upon the context. The identified set of commands is surfaced on the contextual command bar for user interaction.

Abstract: Non-limiting examples of the present disclosure describe creation and management of a contact associated with a document. A contact for a document in a first application may be created. The contact may be used to add content, from a second application, to the document. The contact may be stored. Contact data for the contact may be transmitted to one or more processing devices. An exemplary created contact may be used to transfer content from one or more applications to a document of another application. Other examples are also described.

Abstract: Architecture that provides enhanced tag telemetry in a microblogging communications infrastructure. The architecture provides efficient discovery and tracking of topics that are of interest to a specific user by enabling users to follow (track) hash tags (#tag) and to receive and view all messages tagged with the hash tag appear in the user's personal feed. Each hash tag has a persisted tag page that aggregates all the associated activity, and includes a list that includes, but is not limited to, the tag followers, the most frequent user (uses the tag the most often in a specific time frame), a description, related tags, for example. The user can receive all the updates in the user's personal feed, and see an aggregation of all the messages and conversations associated with the tag in single place. The user can also mute the tag to prevent the receiving of tag information.

Abstract: Collaboration communication tools within a document editor are provided. An application such as a document authoring application displays a document and a communication panel adjacent to the document. The communication panel presents a conversation associated with the document. Communications and/or conversations associated with the documents may be obtained from different applications and aggregated to be presented in conjunction with the document. A new entry is detected for an insertion into the conversation associated with the document. The new entry is inserted into the conversation. An insertion of a section of the document into the conversation is also detected. The section of the document is tracked. The section of the document is displayed embedded into the conversation within the communication panel.

Abstract: Systems, methods, and software are disclosed herein for indicating a change to content in a document to a user. A document is displayed in a user interface to an application. Content then is introduced into the document from a source external to the document. After the content has been introduced into the document, the source of the content is queried for any changes to the content at the source. If a change has occurred, an indication of the change to the content at the source is introduced in the document.