Previous research on mining sequential patterns mainly focused on discovering patterns from point-based event data and interval - based event data, where a pair of time values is associated with each event. Since many areas of research includes data on a snapshot of time points as well as time intervals, it is necessary to define a new temporal pattern. In this paper, based on the existing thirteen temporal relationships, a new variant of temporal pattern is defined for interval-based as well as point - based event data. Then, a hybrid pattern mining technique is proposed. Experimental results show that the completeness and accuracy of the proposed hybrid technique are more efficient than the existing algorithm.