Abstract: In some implementations, a classification system may receive credentials associated with a data source and may receive, from the data source and using the credentials, a set of structured data including input events and output events. The classification system may filter the set of structured data by applying a first set of rules to generate a filtered set of structured data and may convert the filtered set of structured data to one or more numerical vectors, where a vector space associated with the one or more numerical vectors is infinite-dimensional. The classification system may further cluster the one or more numerical vectors using a first machine learning model to generate one or more clusters. Accordingly, the classification system may determine one or more classifications based on the set of structured data, each of the one or more classifications being associated with a corresponding frequency and a corresponding category.

Abstract: In some implementations, a server may receive, from a user device, one or more credentials associated with a data source. Accordingly, the server may receive, from the data source and using the one or more credentials, a set of structured data including a plurality of entries. The server may identify at least one recurring event based on one or more entries in the plurality of entries, and may determine, for the at least one recurring event, one or more derived properties. The server may generate a data structure indicating the at least one recurring event and the one or more derived properties, and may transmit, to the user device, the generated data structure.