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Authors: Roy B. Ofer 1 ; Adi Eldar 1 ; Adi Shalev 2 and Yehezkel S. Resheff 3

Affiliations: 1 Microsoft ILDC, Israel ; 2 Hebrew University of Jerusalem, Israel ; 3 Hebrew University, Israel

ISBN: 978-989-758-222-6

Keyword(s): Data Mining, Pattern Mining, Software Telemetry, Failure Analysis, Subspace Clustering.

Related Ontology Subjects/Areas/Topics: Applications ; Clustering ; Data Engineering ; Information Retrieval ; Learning in Process Automation ; Learning of Action Patterns ; Ontologies and the Semantic Web ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: As the cost of collecting and storing large amounts of data continues to drop, we see a constant rise in the amount of telemetry data collected by software applications and services. With the data mounding up, there is an increasing need for algorithms to automatically and efficiently mine insights from the collected data. One interesting case is the description of large tables using frequently occurring patterns, with implications for failure analysis and customer engagement. Finding frequently occurring patterns has applications both in an interactive usage where an analyst repeatedly query the data and in a completely automated process queries the data periodically and generate alerts and or reports based on the mining. Here we propose two novel mining algorithms for the purpose of computing such predominant patterns in relational data. The first method is a fast heuristic search, and the second is based on an adaptation of the apriori algorithm. Our methods are demonstrated on rea l-world datasets, and extensions to some additional fundamental mining tasks are discussed. (More)

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Paper citation in several formats:
B. Ofer, R.; Eldar, A.; Shalev, A. and S. Resheff, Y. (2017). Algorithms for Telemetry Data Mining using Discrete Attributes.In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, pages 309-317. DOI: 10.5220/0006117903090317

@conference{icpram17,
author={Roy B. Ofer. and Adi Eldar. and Adi Shalev. and Yehezkel S. Resheff.},
title={Algorithms for Telemetry Data Mining using Discrete Attributes},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={309-317},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006117903090317},
isbn={978-989-758-222-6},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Algorithms for Telemetry Data Mining using Discrete Attributes
SN - 978-989-758-222-6
AU - B. Ofer, R.
AU - Eldar, A.
AU - Shalev, A.
AU - S. Resheff, Y.
PY - 2017
SP - 309
EP - 317
DO - 10.5220/0006117903090317

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