Journal of Algorithms
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Outlier detection for high dimensional data
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Mining top-n local outliers in large databases
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
Distance-based outliers: algorithms and applications
The VLDB Journal — The International Journal on Very Large Data Bases
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
An Efficient Algorithm for Discovering Frequent Subgraphs
IEEE Transactions on Knowledge and Data Engineering
AutoPart: parameter-free graph partitioning and outlier detection
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Non-negative tensor factorization with applications to statistics and computer vision
ICML '05 Proceedings of the 22nd international conference on Machine learning
Neighborhood Formation and Anomaly Detection in Bipartite Graphs
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
The devil and packet trace anonymization
ACM SIGCOMM Computer Communication Review
A first look at modern enterprise traffic
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Discovering Structural Anomalies in Graph-Based Data
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Colibri: fast mining of large static and dynamic graphs
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Incremental tensor analysis: Theory and applications
ACM Transactions on Knowledge Discovery from Data (TKDD)
SPARCL: Efficient and Effective Shape-Based Clustering
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
ACM Computing Surveys (CSUR)
Ranking-based clustering of heterogeneous information networks with star network schema
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Design of a Snort-Based Hybrid Intrusion Detection System
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Substructure discovery using minimum description length and background knowledge
Journal of Artificial Intelligence Research
DBpedia - A crystallization point for the Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
A comparison of algorithms for fitting the PARAFAC model
Computational Statistics & Data Analysis
Tensor Decompositions and Applications
SIAM Review
TripleRank: Ranking Semantic Web Data by Tensor Decomposition
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Coupled semi-supervised learning for information extraction
Proceedings of the third ACM international conference on Web search and data mining
Flickr group recommendation based on tensor decomposition
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Ranking-based classification of heterogeneous information networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
MultiAspectForensics: Pattern Mining on Large-Scale Heterogeneous Networks with Tensor Analysis
ASONAM '11 Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining
OddBall: spotting anomalies in weighted graphs
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
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Modern applications such as web knowledge bases, network traffic monitoring and online social networks involve an unprecedented amount of 'heterogeneous' network data, with rich types of interactions among nodes. How can we find patterns and anomalies for heterogeneous networks with millions of edges that have high dimensional attributes, in a scalable way? We introduce MultiAspectForensics, a novel tool to automatically detect and visualise bursts of specific sub-graph patterns within a local community of nodes as anomalies in a heterogeneous network, leveraging scalable tensor analysis methods. One such pattern consists of a set of vertices that form a dense bipartite graph, whose edges share exactly the same set of attributes. We present empirical results of the proposed method on three datasets from distinct application domains, and discuss insights derived from these patterns discovered. Moreover, we empirically show that our algorithm can be feasibly applied to higher dimensional datasets.