A probabilistic semantic-based framework is presented to explicitly perform diverse inference tasks.

The framework combines Markov logic networks with 15 relations between activities.

Advanced pattern mining techniques are introduced to learn intricate temporal rules.

Performances can be improved by logical reasoning with the mined rules under uncertainty.

Our approach is robust to the incomplete or incorrect observations of intervals.