Abstract: Systems and methods for detecting and using semantic relatedness to classify segments of digital text are disclosed. More particularly, embodiments determine the semantic relatedness of segments of text to abstract categories where the abstract categories are not defined by a single word or semantic concept. Detecting semantic relatedness includes analyzing text, embedding the text, and determining semantic relatedness to a set of concepts for a category where each concept may include a set of words/phrases embedded in a similar fashion. The text embedding can be projected onto each concept embedding and reduced to a score representing semantic relatedness. The text is classified based on the semantic relatedness.

Abstract: Technology is disclosed for detecting imposters of a brand account. The technology can store a brand profile of the brand account, detect that a message has been publicly communicated to the brand account from a social media account, monitor messages sent publicly to the social media account from other social media accounts by repeatedly comparing the brand profile to metadata of each of the monitored messages, and identify at least one of the other social media accounts as an imposter account based on the comparing. The technology can cease the comparing at predetermined expiration time occurring after the detection of the message that was sent publicly to the brand account.

Abstract: Technology is disclosed for detecting imposters of a brand account. The technology can store a brand profile of the brand account, detect that a message has been publicly communicated to the brand account from a social media account, monitor messages sent publicly to the social media account from other social media accounts by repeatedly comparing the brand profile to metadata of each of the monitored messages, and identify at least one of the other social media accounts as an imposter account based on the comparing. The technology can cease the comparing at predetermined expiration time occurring after the detection of the message that was sent publicly to the brand account.

Abstract: A security and compliance platform ingests content from heterogeneous collaboration platforms and processes the content to detect potential regulatory, privacy, and security risks in the conversations. One of the detections that can be applied is the identification of application windows appearing during a collaboration screen share. Because these applications may contain sensitive personally identifiable information (PII), technical trade secrets, or highly confidential corporate information, there is meaningful utility in identifying instances when these applications are shared. If applications shared on screen is detected, a corresponding workflow action may be implemented, for example flagging a session for further analysis in a review screen of the security and compliance platform.

Abstract: The disclosed invention provides methods supporting systems that processes video communication(s) provided by an organization subject to internal or external regulations such as a specific financial services firm or a specific consumer product goods company. In various embodiments, video content is analyzed through a pipeline process of multiple extraction scripts, programs, and/or services and processes the content for participant likeness through facial recognition, voice recognition, and voice-to-text and stores the output in a normalized, searchable data store. A policy analysis is performed based on the stored data and external regulatory compliance, internal rules such as acceptable use policies, community-based regulations, or any combination thereof, to determine a risk score.

Abstract: The disclosed invention provides methods supporting systems that processes video communication(s) provided by an organization subject to internal or external regulations such as a specific financial services firm or a specific consumer product goods company. In various embodiments, video content is analyzed through a pipeline process of multiple extraction scripts, programs, and/or services and processes the content for participant likeness through facial recognition, voice recognition, and voice-to-text and stores the output in a normalized, searchable data store. A policy analysis is performed based on the stored data and external regulatory compliance, internal rules such as acceptable use policies, community-based regulations, or any combination thereof, to determine a risk score.

Abstract: Systems and methods for detecting and using semantic relatedness to classify segments of digital text are disclosed. More particularly, embodiments determine the semantic relatedness of segments of text to abstract categories where the abstract categories are not defined by a single word or semantic concept. Detecting semantic relatedness includes analyzing text, embedding the text, and determining semantic relatedness to a set of concepts for a category where each concept may include a set of words/phrases embedded in a similar fashion. The text embedding can be projected onto each concept embedding and reduced to a score representing semantic relatedness. The text is classified based on the semantic relatedness.

Abstract: Technology is disclosed for detecting imposters of a brand account. The technology can store a brand profile of the brand account, detect that a message has been publicly communicated to the brand account from a social media account, monitor messages sent publicly to the social media account from other social media accounts by repeatedly comparing the brand profile to metadata of each of the monitored messages, and identify at least one of the other social media accounts as an imposter account based on the comparing. The technology can cease the comparing at predetermined expiration time occurring after the detection of the message that was sent publicly to the brand account.

Abstract: Technology is disclosed for detecting imposters of a brand account. The technology can store a brand profile of the brand account, detect that a message has been publicly communicated to the brand account from a social media account, monitor messages sent publicly to the social media account from other social media accounts by repeatedly comparing the brand profile to metadata of each of the monitored messages, and identify at least one of the other social media accounts as an imposter account based on the comparing. The technology can cease the comparing at predetermined expiration time occurring after the detection of the message that was sent publicly to the brand account.

Abstract: Methods of and systems for identifying a discrete participant among a plurality of participants in an audio/video communication (e.g., video content, digital video content, audio content, and audio-visual content) that include: receiving the audio/video communication; identifying from the audio/video communication content (e.g., using metadata from the broadcast content to identify each participant) multiple identification-related features for each participant; associating a first identification-related feature of a first participant to a second identification-related feature of the first participant; organizing the associated identification-related features of the first participant into a feature class(es); logically relating a first feature class to a second feature class; and attributing a grouping of logically-related feature classes to the discrete participant.

Abstract: Methods of and systems for identifying a discrete participant among a plurality of participants in an audio/video communication (e.g., video content, digital video content, audio content, and audio-visual content) that include: receiving the audio/video communication; identifying from the audio/video communication content (e.g., using metadata from the broadcast content to identify each participant) multiple identification-related features for each participant; associating a first identification-related feature of a first participant to a second identification-related feature of the first participant; organizing the associated identification-related features of the first participant into a feature class(es); logically relating a first feature class to a second feature class; and attributing a grouping of logically-related feature classes to the discrete participant.

Abstract: Technology is disclosed for detecting imposters of a brand account. The technology can store a brand profile of the brand account, detect that a message has been publicly communicated to the brand account from a social media account, monitor messages sent publicly to the social media account from other social media accounts by repeatedly comparing the brand profile to metadata of each of the monitored messages, and identify at least one of the other social media accounts as an imposter account based on the comparing. The technology can cease the comparing at predetermined expiration time occurring after the detection of the message that was sent publicly to the brand account.