Tata Consultancy Services Limited

Sarmimala Saikia

Gautam Shroff

Puneet Kumar Agarwal

Ashwin Srinivasan

Lovekesh Vig

Richa Rawat

Puneet Agarwal

A method and system for interpreting a dataset is described herein. The method include computing a rule set pertaining to the dataset, followed by generating a rule cover pertinent to a subset of the rule set. Further, a plurality of distances between the plurality of rule pairs in the rule cover is calculated and a distance matrix based on the calculated plurality of distances is generated. Consequently, the overlapping rules within the rule cover are clustered using the distance matrix and a representative rule from each cluster is selected. Further, at least one exception for each representative rule is determined and the dataset is interpreted using the representative rules and the at least one exception. Thereby, the method provides succinct results in terms of rules and exceptions along with multiple interpretations of the same set of transactions from the dataset, thereby providing a holistic view about the dataset.

Interpretation of a dataset for co-occurring itemsets using a cover rule and clustering

This disclosure relates generally to multi-sensor data, and more particularly to summarizing multi-sensor data. In one embodiment, the method includes computing plurality of histograms from sensor data associated with a plurality of sensors. The respective histograms of each sensor are clustered into a first plurality of sensor-clusters, and a first set of rules is extracted therefrom. First set of rules defines patterns of histograms of a set of sensors occurring frequently over a time-period. Two or more sensor-clusters from amongst the first plurality of sensor-clusters are merged selectively to obtain a second plurality of sensor-clusters. Second set of rules are extracted from the second plurality of sensor-clusters, and a set of correlated sensors are identified therefrom based on the second set of rules. Third set of rules are extracted from the set of correlated sensors, the third set of rules summarizes the multi-sensor data to represent prominent co-occurring sensor behaviors.

Multi-sensor data summarization

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Noida, India

Sarmimala Saikia