Abstract: In an embodiment, the disclosed technologies include extracting, from at least one search log, session data including at least three semantically related queries and corresponding timestamp data; using the session data, creating a training sequence that includes source query data, context query data, and target query data, the source query data having both a temporal relationship and a lexical relationship to the target query data and the context query data having a temporal relationship to the source query data; creating a learned model by, using a machine learning-based modeling process, learning a mapping of a semantic representation of the context query data and the source query data to a semantic representation of the target query data; in response to a new query, using the learned model to generate at least one recommended query that is semantically related to the new query.

Abstract: In an embodiment, the disclosed technologies include extracting, from at least one search log, session data including at least three semantically related queries and corresponding timestamp data; using the session data, creating a training sequence that includes source query data, context query data, and target query data, the source query data having both a temporal relationship and a lexical relationship to the target query data and the context query data having a temporal relationship to the source query data; creating a learned model by, using a machine learning-based modeling process, learning a mapping of a semantic representation of the context query data and the source query data to a semantic representation of the target query data; in response to a new query, using the learned model to generate at least one recommended query that is semantically related to the new query.