Abstract: A machine may be configured to perform high confidence digital content treatment. For example, the machine accesses a message reported as objectionable by a member of a Social Networking Service (SNS). The machine identifies a digital content item included in the message reported as objectionable based on pre-processing the message. The machine determines one or more degrees of similarity between the digital content item and one or more other digital content items included in one or more other messages previously reported as objectionable by members of the SNS. The machine generates a final score value associated with the digital content item based on the one or more degrees of similarity values between the digital content item and one or more other digital content items. The machine executes a treatment for the message reported as objectionable based on the final score value associated with the content of the message.

Abstract: A device receives a request for information regarding a debt resolution plan available for a delinquent account. The request includes a first input indicating a payment amount, a second input indicating a payment frequency, and a third input indicating a payment start date. The device obtains account data associated with the delinquent account and determines, using a first model, a score for the delinquent account based on the first input, the second input, the third input, and the account data. The device determines, using a second model, a plurality of debt resolution plan parameters for at least a first and a second debt resolution plan. The device transmits the plurality of debt resolution plan parameters associated with the first and second debt resolution plans, receives an enrollment request, enrolls the delinquent account in a selected debt resolution plan, and causes an action to be performed based on the enrolling.

Abstract: A machine may be configured to perform detecting and treating unauthorized duplicate digital content. For example, the machine accesses a digital content item published on a server of a social networking service (SNS) by a member of the SNS. The machine determines that the digital content item does not include a reference indicator that indicates that the digital content item is copied original content. The machine determines that the digital content item is at least one of a near-duplicate or an exact duplicate of an original digital content item based on a comparison between data pertaining to the digital content item and data pertaining to the original digital content item. The machine enhances the server based on executing a treatment of the digital content item. The executing of the treatment includes causing an automatic alteration of a state associated with the digital content item in the record of the database.

Abstract: A machine is configured to correct erroneous automatic treatment of digital content items identified using, for instance, a locality sensitive hash model or a pattern matching model, and to address operational problems. For example, the machine accesses a signal value indicating that a content item is non-objectionable. The machine generates, based on one or more signal values associated with one or more near-duplicates of the content item, a score associated with the content item. The score indicates a level of objectionability of the content item. The machine modifies a status of the content item based on determining that the score does not exceed a threshold value associated with a treatment of content items. The modified status indicates that the content item is non-objectionable. The machine causes a display of an identifier associated with the content item in a user interface. The identifier indicates that the content item is non-objectionable.

Abstract: A machine may be configured to perform high confidence digital content treatment. For example, the machine accesses a message reported as objectionable by a member of a Social Networking Service (SNS). The machine identifies a digital content item included in the message reported as objectionable based on pre-processing the message. The machine determines one or more degrees of similarity between the digital content item and one or more other digital content items included in one or more other messages previously reported as objectionable by members of the SNS. The machine generates a final score value associated with the digital content item based on the one or more degrees of similarity values between the digital content item and one or more other digital content items. The machine executes a treatment for the message reported as objectionable based on the final score value associated with the content of the message.