Correlation Clustering with Active Learning of Pairwise Similarities
- URL: http://arxiv.org/abs/2302.10295v4
- Date: Mon, 12 Feb 2024 19:43:38 GMT
- Title: Correlation Clustering with Active Learning of Pairwise Similarities
- Authors: Linus Aronsson, Morteza Haghir Chehreghani
- Abstract summary: Correlation clustering is a well-known unsupervised learning setting that deals with positive and negative pairwise similarities.
In this paper, we study the case where the pairwise similarities are not given in advance and must be queried in a cost-efficient way.
We develop a generic active learning framework for this task that benefits from several advantages.
- Score: 3.86170450233149
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Correlation clustering is a well-known unsupervised learning setting that
deals with positive and negative pairwise similarities. In this paper, we study
the case where the pairwise similarities are not given in advance and must be
queried in a cost-efficient way. Thereby, we develop a generic active learning
framework for this task that benefits from several advantages, e.g.,
flexibility in the type of feedback that a user/annotator can provide,
adaptation to any correlation clustering algorithm and query strategy, and
robustness to noise. In addition, we propose and analyze a number of novel
query strategies suited to this setting. We demonstrate the effectiveness of
our framework and the proposed query strategies via several experimental
studies.
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