Abstract: Techniques performed by a data processing system for predicting availability of a user include receiving, from a first computing device over a network connection, a first request for predicted availability of a first user to participate in an online communication session, wherein the first request includes an identifier associated with the first user and a time period for the predicted availability of the user, in response to receiving the first request, determining a first predicted availability of the first user over the predicted time period using a first machine learning model trained with user information from a plurality of data sources, the user information being indicative of when the user is likely to be available to participate in the online communication session, and sending, to the first computing device over the network connection, availability information including the first predicted availability of the first user.

Abstract: Techniques performed by a data processing system for predicting availability of a user include receiving, from a first computing device over a network connection, a first request for predicted availability of a first user to participate in an online communication session, wherein the first request includes an identifier associated with the first user and a time period for the predicted availability of the user, in response to receiving the first request, determining a first predicted availability of the first user over the predicted time period using a first machine learning model trained with user information from a plurality of data sources, the user information being indicative of when the user is likely to be available to participate in the online communication session, and sending, to the first computing device over the network connection, availability information including the first predicted availability of the first user.

Abstract: A system for extracting differential topics from a dataset including a user interface, a memory for storing executable program code, and one or more electronic processors coupled to the memory and the user interface. The electronics processors are configured to receive a dataset from one or more servers, wherein the dataset comprises user feedback data associated with a software program. The electronic processors are also configured to extract text from the dataset, convert the extracted text to vector data, and determine anomalous data clusters associated with the vector data using statistical analysis. The electronic processors are also configured to differentiate overlapping anomalous data clusters using a classification algorithm, wherein the differentiated overlapping anomalous data clusters are associated with specific topics, and export each specific topic associated with the differentiated overlapping data cluster.