Abstract: Technologies are disclosed herein for generating and utilizing machine-learning generated classifiers configured to identify document relationships. Manually-generated data is captured that indicates if documents in a document corpus have a relationship with one another, such as duplicates or variations. A determination may then be made as to whether a classifier is to be generated based on the duplicate decision data. If a classifier is to be generated, machine learning may be performed using training documents from the document corpus and the duplicate decision data to generate a classifier. The machine-learning generated classifier may then be utilized in a production environment to determine whether a new document is a duplicate of documents in the document corpus and/or to identify other relationships between documents in the document corpus, such as documents that are similar or are variations of one another.

Abstract: Embodiments of the present invention include information services, methods and systems to facilitate gathering and management of information by home users and professional users of information gathering, processing, and distribution services, and user interfaces through which users communicate with information services. In one embodiment of the present invention, a central information gathering, processing, and distribution service provides a simple, but robust and highly functional, interface to remote home users and professional users to allow the home users and professional users to continuously receive updated information gleaned from continuous searching of the Internet and other information sources by the information service. The interface allows users to define, refine, and stably store interests that define information searches continuously carried out, on behalf of the user, by the information gathering, processing, and distribution service.