International Business Machines Corporation

Leman Akoglu

Hanghang Tong

Kun-Lung Wu

Srinivasan Parthasarathy

Deepak Rajan

Rohit Madhukar Khandekar

Vibhore Kumar

Techniques are provided for anomaly, association and clustering detection. At least one code table is built for each attribute in a set of data. A first code table corresponding to a first attribute and a second code table corresponding to a second attribute are selected. The first code table and the second code table are merged into a merged code table, and a determination is made to accept or reject the merged code table. An anomaly is detected when a total compression cost for a data point is greater than a threshold compression cost inferred from one or more code tables. An association in a data table is detected by merging attribute groups, splitting data groups, and assigning data points to data groups. A cluster is inferred from a matrix of data and code words for each of the one or more code tables.

Anomaly, association and clustering detection

Techniques are provided for dynamic anomaly, association and clustering detection. At least one code table is built for each attribute in a set of data containing one or more attributes. One or more clusters associated with one or more of the code tables are established. One or more new data points are received. A determination is made if a given one of the new data points is an anomaly. At least one of the one or more code tables is updated responsive to the determination. When a compression cost of a given one of the new data points is greater than a threshold compression cost for each of the one or more clusters, the given one of the new data points is an anomaly.

Dynamic anomaly, association and clustering detection

A method, an apparatus and an article of manufacture for processing a random-walk based vertex-proximity query on a graph. The method includes computing at least one vertex cluster and corresponding meta-information from a graph, dynamically updating the clustering and corresponding meta-information upon modification of the graph, and identifying a vertex cluster relevant to at least one query vertex and aggregating corresponding meta-information of the cluster to process the query.

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Pittsburgh, PA, United States of America

Leman Akoglu