Abstract: Representative embodiments disclose mechanisms to validate statements made as part of a document creation or editing process. As the user edits or creates a document using a document creation/editing application, statements made in the document can be submitted to a validation service in a proactive or reactive manner. The statement validation service receives the statement, resolves any coreferences using a coreference resolution process. Once coreferences in the statement have been resolved and replaced, entities are resolved using an entity resolution process. Predicates are then resolved using a predicate resolution process. Entity-predicate pairs are then used to traverse a knowledge graph to extract information relevant to the statement. Suggested corrections are created from the extracted information and presented to the user via the document creation/editing application.

Abstract: Representative embodiments disclose mechanisms to validate statements made as part of a document creation or editing process. As the user edits or creates a document using a document creation/editing application, statements made in the document can be submitted to a validation service in a proactive or reactive manner. The statement validation service receives the statement, resolves any coreferences using a coreference resolution process. Once coreferences in the statement have been resolved and replaced, entities are resolved using an entity resolution process. Predicates are then resolved using a predicate resolution process. Entity-predicate pairs are then used to traverse a knowledge graph to extract information relevant to the statement. Suggested corrections are created from the extracted information and presented to the user via the document creation/editing application.

Abstract: Architecture that includes an automated content recommendation engine to enhance the quality of content being delivered, and machine learning for the content recommendation. Content recommendation is improved for users and the dissatisfaction rate of displayed content lowered, thereby improving the overall user experience. More specifically, the architecture enables and obtains direct user feedback (e.g., like/dislike) and crowdsourced user feedback of the content, merges content features with the user feedback to build the content recommendation engine, uses the content recommendation engine to detect other content that the user may like or dislike, and, thereby reduces the DSAT rate of display content using the content recommendation engine.