Abstract: A real-time event processing system receives event data containing telemetric data and one or more personal identifiers. The personal identifier in the event data is replaced with an obfuscated value so that the telemetric data may be used without reference to the personal identifier. A reversible map is used to reverse the obfuscated personal identifier to its original value. In the case when a request is received to delete the mapped personal identifier, the link to the entry in the reversible map is broken by associating the personal identifier with a different obfuscated value.

Abstract: An offline batch processing system classifies sensitive data contained in consumer data, such as telemetric data, using a manual classification process and a machine learning model. The machine learning model is used to recheck the policy settings used in the manual classification process and to learn relationships between the features in the consumer data in order to identify sensitive data. The identified sensitive data is then scrubbed so that the remaining data may be used.

Abstract: A code completion system predicts candidates to complete a code fragment with a tag name and/or an attribute name in source code written in a hierarchically-structured language. Candidates for predicting a tag name are based on a first-order tag Markov chain model generated from usage patterns of relationships of tag names found in a training dataset. Candidates for predicting an attribute name are based on a second-order attribute Markov chain model generated from usage patterns of sequences of attribute names associated with each tag name found in the training dataset.

Abstract: A code completion tool uses machine learning models generated for custom or proprietary classes associated with a custom library of classes of a programming language and for overlapping classes associated with a standard library of classes for the programming language. The machine learning models are trained with features from usage patterns of the custom classes and overlapping classes found in two different sources of training data. An n-order Markov chain model is trained for each custom class and each overlapping class from the usage patterns to generate probabilities to predict a method invocation more likely to follow a sequence of method invocations for a custom class and for an overlapping class.

Abstract: A code completion tool uses machine learning models to more precisely predict the likelihood of an invocation of a particular overloaded method completing a code fragment that follows one or more method invocations of a same class in a same document during program development. In one aspect, the machine learning model is a n-order Markov chain model that is trained on features that represent the method signatures of overloaded methods in order to generate ordered sequences of method signatures of overloaded method invocations.

Abstract: A code completion tool uses machine learning models to more precisely predict the likelihood of a method invocation completing a code fragment that follows one or more method invocations of a same class in a same document during program development. In one aspect, the machine learning model is a n-order Markov chain model that is trained on features that represent characteristics of the context of method invocations of a class in commonly-used programs from a sampled population.

Abstract: Methods, systems, and computer-readable media for categorizing sender domains are provided. An advertisement platform includes targeting components, databases, mail servers, and client devices. Recipients interact with the client devices to receive electronic mail from the mail servers. The mail servers store records of sender domains where the recipient performed a specified action to a message having a sender domain. The mail server transmits a log of the sender domains, actions, and an anonymous identifier for the recipient to the targeting system. The targeting components extract the sender domains that are used by the advertisement platform to communicate to the database to retrieve advertisement categories that correspond to the sender domains. The advertisement categories are used by the advertisement platform to direct content, including advertisements, to the recipients via the anonymous identifier.