PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Learning from evolving data streams: online triage of bug reports
Grzegorz Chrupala
In: EACL 2012, Avignon, France(2012).

Abstract

Open issue trackers are a type of social media that has received relatively little attention from the text-mining community. We investigate the problems inherent in learning to triage bug reports from time-varying data. We demonstrate that concept drift is an important consideration. We show the effectiveness of online learning algorithms by evaluating them on several bug report datasets collected from open issue trackers associated with large open-source projects. We make this collection of data publicly available.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Natural Language Processing
ID Code:8858
Deposited By:Grzegorz Chrupala
Deposited On:21 February 2012