Abstract: Techniques are described herein for selecting an advertisement using user search history segmentation. Instances of queries that are provided by a user are referred to collectively as the search history of the user. The search history is segmented into sessions that correspond to respective tasks of the user. Each of the sessions includes a respective subset of the query instances that are included in the user's search history. A weight is assigned to each session based on attribute(s) of the respective session. A session that includes a first subset of the query instances is selected based on the weight that is assigned to that session. Features are extracted from query instances that are included in the first subset. Weights are assigned to the extracted features based on attribute(s) of the first subset. An advertisement is selected to be provided to the user based on the extracted features and corresponding weights.