Probabilistic temporal databases, I: algebra
ACM Transactions on Database Systems (TODS)
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Discovering Temporal Patterns for Interval-Based Events
DaWaK 2000 Proceedings of the Second International Conference on Data Warehousing and Knowledge Discovery
Exploiting k-constraints to reduce memory overhead in continuous queries over data streams
ACM Transactions on Database Systems (TODS)
Discovering Frequent Arrangements of Temporal Intervals
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Mining Nonambiguous Temporal Patterns for Interval-Based Events
IEEE Transactions on Knowledge and Data Engineering
Mining relationships among interval-based events for classification
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Sequence Pattern Query Processing over Out-of-Order Event Streams
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
ZStream: a cost-based query processor for adaptively detecting composite events
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
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In pervasive computing environments, complex event processing has become increasingly important in modern applications. A key aspect of complex event processing is to extract patterns from event streams to make informed decisions in real-time. However, network latencies and machine failures may cause events to arrive out-of-order. In addition, existing literatures assume that events do not have any duration, but events in many real world application have durations, and the relationships among these events are often complex. In this work, we first analyze the preliminaries of time semantics and propose a model of it. A hybrid solution including time-interval to solve out-of-order events is also introduced, which can switch from one level of output correctness to another based on real time. The experimental study demonstrates the effectiveness of our approach.