Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
Proceedings of the 17th International Conference on Data Engineering
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
CLOSET+: searching for the best strategies for mining frequent closed itemsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Finding recent frequent itemsets adaptively over online data streams
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Distributed regression: an efficient framework for modeling sensor network data
Proceedings of the 3rd international symposium on Information processing in sensor networks
Moment: Maintaining Closed Frequent Itemsets over a Stream Sliding Window
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
An Algorithm for In-Core Frequent Itemset Mining on Streaming Data
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
In-Network Outlier Detection in Wireless Sensor Networks
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
Programming sensor networks using abstract regions
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
Approximate frequency counts over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Event detection services using data service middleware in distributed sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Online algorithms for mining inter-stream associations from large sensor networks
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Proactive context-aware sensor networks
EWSN'06 Proceedings of the Third European conference on Wireless Sensor Networks
Efficient Signal Processing and Anomaly Detection in Wireless Sensor Networks
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Event Correlations in Sensor Networks
ICCS 2009 Proceedings of the 9th International Conference on Computational Science
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
A decentralized approach for mining event correlations in distributed system monitoring
Journal of Parallel and Distributed Computing
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Today it is possible to deploy sensor networks in the real world and collect large amounts of raw sensory data. However, it remains a major challenge to make sense of sensor data, i.e., to extract high-level knowledge from the raw data. In this paper we present a novel in-network knowledge discovery technique, where high-level information is inferred from raw sensor data directly on the sensor nodes. In particular, our approach supports the discovery of frequent distributed event patterns, which characterize the spatial and temporal correlations between events observed by sensor nodes in a confined network neighborhood. One of the key challenges in realizing such a system are the constrained resources of sensor nodes. To this end, our solution offers a declarative query language that allows to trade off detail and scope of the sought patterns for resource consumption. We implement our proposal on real hardware and evaluate the trade-off between scope of the query and resource consumption.