Abstract: A natural language query can be received at a main natural language processor inside a data protection compliance boundary in a computer system. The natural language query can be processed via the main natural language processor. The data from the query can be transmitted to a data protection computer component. It can be determined via the data protection component whether the data from the query includes protected data whose transmission to a computerized extension would violate a computer-readable data protection rule. The extension is outside the compliance boundary in the computer system and is configured to participate in responding to natural language queries received by the main natural language processor. In response to determining that the data from the query includes the protected data, transmission of the protected data from the main natural language processor to the extension as part of responding to the query can be inhibited.

Abstract: Systems, methods, and software are disclosed herein for enhancing group collaboration in the context of productivity applications. In an implementation, a productivity application includes a user interface in which a document may be presented. In addition, a view of a groups feature provided by a social network service may be presented in the user interface to the productivity application. The view may include various options or interacting with the groups feature, such as the ability to create a new group, the ability to post comments to a group in the social network service, and the ability to upload documents to a group.

Abstract: A natural language query can be received at a main natural language processor inside a data protection compliance boundary in a computer system. The natural language query can be processed via the main natural language processor. The data from the query can be transmitted to a data protection computer component. It can be determined via the data protection component whether the data from the query includes protected data whose transmission to a computerized extension would violate a computer-readable data protection rule. The extension is outside the compliance boundary in the computer system and is configured to participate in responding to natural language queries received by the main natural language processor. In response to determining that the data from the query includes the protected data, transmission of the protected data from the main natural language processor to the extension as part of responding to the query can be inhibited.

Abstract: A natural language query can be processed via a main natural language processor. A request to produce an intent of the query can be dispatched from the main natural language processor to an extension natural language processor. An intent of the query can be generated via the extension natural language processor in response to the dispatched request, with the generating of the intent being performed independently of the main natural language processor. The intent of the natural language query can be passed from the extension natural language processor to the main natural language processor in response to the request to produce the intent of the query. A selection of a conversation query processor for responding to the intent can be produced via the main natural language processor. Additionally, an instruction to respond to the intent of the query can be passed to the selected conversation query processor.

Abstract: A natural language query can be received at a main natural language processor inside a data protection compliance boundary in a computer system. The natural language query can be processed via the main natural language processor. The data from the query can be transmitted to a data protection computer component. It can be determined via the data protection component whether the data from the query includes protected data whose transmission to a computerized extension would violate a computer-readable data protection rule. The extension is outside the compliance boundary in the computer system and is configured to participate in responding to natural language queries received by the main natural language processor. In response to determining that the data from the query includes the protected data, transmission of the protected data from the main natural language processor to the extension as part of responding to the query can be inhibited.

Abstract: A natural language query can be received at a main natural language processor inside a data protection compliance boundary in a computer system. The natural language query can be processed via the main natural language processor. The data from the query can be transmitted to a data protection computer component. It can be determined via the data protection component whether the data from the query includes protected data whose transmission to a computerized extension would violate a computer-readable data protection rule. The extension is outside the compliance boundary in the computer system and is configured to participate in responding to natural language queries received by the main natural language processor. In response to determining that the data from the query includes the protected data, transmission of the protected data from the main natural language processor to the extension as part of responding to the query can be inhibited.

Abstract: A natural language query can be processed via a main natural language processor. A request to produce an intent of the query can be dispatched from the main natural language processor to an extension natural language processor. An intent of the query can be generated via the extension natural language processor in response to the dispatched request, with the generating of the intent being performed independently of the main natural language processor. The intent of the natural language query can be passed from the extension natural language processor to the main natural language processor in response to the request to produce the intent of the query. A selection of a conversation query processor for responding to the intent can be produced via the main natural language processor. Additionally, an instruction to respond to the intent of the query can be passed to the selected conversation query processor.

Abstract: Systems, methods, and software are disclosed herein for enhancing group collaboration in the context of productivity applications. In an implementation, a productivity application includes a user interface in which a document may be presented. In addition, a view of a groups feature provided by a social network service may be presented in the user interface to the productivity application. The view may include various options or interacting with the groups feature, such as the ability to create a new group, the ability to post comments to a group in the social network service, and the ability to upload documents to a group.

Abstract: Content is received and compared against rules for identifying a type of content. Each rule has both segmented and unsegmented patterns. The content is matched against the patterns and assigned a confidence score that is higher if the content matches a segmented pattern and lower if the content matches an unsegmented pattern.

Abstract: System and methods for the implementation and/or enforcement of an email policy for an organization's email system are presented. A Data Loss Prevention (DLP) policy may be implemented on top of the email system. In one embodiment, the DLP policy may comprise modules and/or processing that tests emails for such sensitive data within emails. If an email comprises such sensitive data, then the DLP policy directives may specify processing to be applied as part of each stage of mail processing, from authoring to mail processing on the server and delivery. A single policy may be authored and managed that will apply the policy directives uniformly across all aspects of the message lifecycle. Each of the message policy enforcement systems may evaluate the single policy definition and apply the policy directives in a manner consistent with the contextual evaluation of the policy.

Abstract: An authoring component determines the sensitivity of an authored document and generates a user interface conveying contextual educational information about data dissemination policies that apply to the document. The user interface also provides user input mechanisms that allow the user to provide inputs affect the enforcement of a given data dissemination policy on the document.

Abstract: Content is received and compared against rules for identifying a type of content. Each rule has both segmented and unsegmented patterns. The content is matched against the patterns and assigned a confidence score that is higher if the content matches a segmented pattern and lower if the content matches an unsegmented pattern.

Abstract: Content is received and compared against rules for identifying a type of content. Each rule has both segmented and unsegmented patterns. The content is matched against the patterns and assigned a confidence score that is higher if the content matches a segmented pattern and lower if the content matches an unsegmented pattern.

Abstract: An authoring component determines the sensitivity of an authored document and generates a user interface conveying contextual educational information about data dissemination policies that apply to the document. The user interface also provides user input mechanisms that allow the user to provide inputs affect the enforcement of a given data dissemination policy on the document.

Abstract: An authoring component determines the sensitivity of an authored document and generates a user interface conveying contextual educational information about data dissemination policies that apply to the document. The user interface also provides user input mechanisms that allow the user to provide inputs affect the enforcement of a given data dissemination policy on the document.

Abstract: System and methods for the implementation and/or enforcement of an email policy for an organization's email system are presented. A Data Loss Prevention (DLP) policy may be implemented on top of the email system. In one embodiment, the DLP policy may comprise modules and/or processing that tests emails for such sensitive data within emails. If an email comprises such sensitive data, then the DLP policy directives may specify processing to be applied as part of each stage of mail processing, from authoring to mail processing on the server and delivery. A single policy may be authored and managed that will apply the policy directives uniformly across all aspects of the message lifecycle. Each of the message policy enforcement systems may evaluate the single policy definition and apply the policy directives in a manner consistent with the contextual evaluation of the policy.

Abstract: Content is received and compared against rules for identifying a type of content. Each rule has both segmented and unsegmented patterns. The content is matched against the patterns and assigned a confidence score that is higher if the content matches a segmented pattern and lower if the content matches an unsegmented pattern.

Abstract: An authoring component determines the sensitivity of an authored document and generates a user interface conveying contextual educational information about data dissemination policies that apply to the document. The user interface also provides user input mechanisms that allow the user to provide inputs affect the enforcement of a given data dissemination policy on the document.

Abstract: Similarity is determined between documents based on a method for identifying documents that are likely to be based on another document. The method can include the determination of a containment coefficient, which can indicate when a template document is a subset or substantially a subset of another document. Based on this determination, an appropriate document management action can be taken, such as implementing a security policy or modifying the display of messages from a user interface.