Abstract: In one example, a content catalog system may process a bulk set of errors to prioritize those errors that may benefit from manual review by a human error administrator. A catalog quality management sub-system of the content catalog system may receive an error output describing a catalog error for a product aspect of a product in a content catalog from an error detection module. The catalog quality management sub-system may categorize the catalog error by a degree of human interaction with an error fix determined from an error metric in the error output. The catalog quality management sub-system may apply an error fix to the catalog error based on the degree of human interaction.

Abstract: In one example, a content catalog system may process a bulk set of errors to prioritize those errors that may benefit from manual review by a human error administrator. A catalog quality management sub-system of the content catalog system may receive an error output describing a catalog error for a product aspect of a product in a content catalog from an error detection module. The catalog quality management sub-system may categorize the catalog error by a degree of human interaction with an error fix determined from an error metric in the error output. The catalog quality management sub-system may apply an error fix to the catalog error based on the degree of human interaction.

Abstract: In one example, a content catalog system may process a bulk set of errors to prioritize those errors that may benefit from manual review by a human error administrator. A catalog quality management sub-system of the content catalog system may receive an error output describing a catalog error for a product aspect of a product in a content catalog from an error detection module. The catalog quality management sub-system may categorize the catalog error by a degree of human interaction with an error fix determined from an error metric in the error output. The catalog quality management sub-system may apply an error fix to the catalog error based on the degree of human interaction.

Abstract: Aspects of an abuse detection system for a web service include an abuse detection engine executing on a server. The abuse detection engine includes a pre-processing module for aggregating a data set for processing and analysis; a suspiciousness test module for identifying suspicious content owners and suspicious users; a graphing module for finding connections between suspicious content owners and suspicious users; an analysis module for determining which groups are constituted of fraudulent or abusive accounts; and a notification generation and output module for generating a list of abusive entities and a notification for output to at least one of: the abusive entity, a digital content distribution company associated with the abusive entity, and a legal department or other entity for further investigation or action. Additionally, royalties for content consumptions associated with abusive accounts may be held.

Abstract: In one example, a content catalog system may process a bulk set of errors to prioritize those errors that may benefit from manual review by a human error administrator. A catalog quality management sub-system of the content catalog system may receive an error output describing a catalog error for a product aspect of a product in a content catalog from an error detection module. The catalog quality management sub-system may categorize the catalog error by a degree of human interaction with an error fix determined from an error metric in the error output. The catalog quality management sub-system may apply an error fix to the catalog error based on the degree of human interaction.

Abstract: In one example, a content catalog system may process a bulk set of errors to prioritize those errors that may benefit from manual review by a human error administrator. A catalog quality management sub-system of the content catalog system may receive an error output describing a catalog error for a product aspect of a product in a content catalog from an error detection module. The catalog quality management sub-system may categorize the catalog error by a degree of human interaction with an error fix determined from an error metric in the error output. The catalog quality management sub-system may apply an error fix to the catalog error based on the degree of human interaction.

Abstract: Aspects of an abuse detection system for a web service include an abuse detection engine executing on a server. The abuse detection engine includes a pre-processing module for aggregating a data set for processing and analysis; a suspiciousness test module for identifying suspicious content owners and suspicious users; a graphing module for finding connections between suspicious content owners and suspicious users; an analysis module for determining which groups are constituted of fraudulent or abusive accounts; and a notification generation and output module for generating a list of abusive entities and a notification for output to at least one of: the abusive entity, a digital content distribution company associated with the abusive entity, and a legal department or other entity for further investigation or action. Additionally, royalties for content consumptions associated with abusive accounts may be held.

Abstract: Aspects of an abuse detection system for a web service include an abuse detection engine executing on a server. The abuse detection engine includes a pre-processing module for aggregating a data set for processing and analysis; a suspiciousness test module for identifying suspicious content owners and suspicious users; a graphing module for finding connections between suspicious content owners and suspicious users; an analysis module for determining which groups are constituted of fraudulent or abusive accounts; and a notification generation and output module for generating a list of abusive entities and a notification for output to at least one of: the abusive entity, a digital content distribution company associated with the abusive entity, and a legal department or other entity for further investigation or action. Additionally, royalties for content consumptions associated with abusive accounts may be held.

Abstract: In one example, a content catalog system may process a bulk set of errors to prioritize those errors that may benefit from manual review by a human error administrator. A catalog quality management sub-system of the content catalog system may receive an error output describing a catalog error for a product aspect of a product in a content catalog from an error detection module. The catalog quality management sub-system may categorize the catalog error by a degree of human interaction with an error fix determined from an error metric in the error output. The catalog quality management sub-system may apply an error fix to the catalog error based on the degree of human interaction.

Abstract: Aspects of an abuse detection system for a web service include an abuse detection engine executing on a server. The abuse detection engine includes a pre-processing module for aggregating a data set for processing and analysis; a suspiciousness test module for identifying suspicious content owners and suspicious users; a graphing module for finding connections between suspicious content owners and suspicious users; an analysis module for determining which groups are constituted of fraudulent or abusive accounts; and a notification generation and output module for generating a list of abusive entities and a notification for output to at least one of: the abusive entity, a digital content distribution company associated with the abusive entity, and a legal department or other entity for further investigation or action. Additionally, royalties for content consumptions associated with abusive accounts may be held.