Resource-Bounded Information Gathering for Correlation Clustering

Kanani, Pallika H.; McCallum, Andrew

doi:10.1007/978-3-540-72927-3_46

Resource-Bounded Information Gathering for Correlation Clustering

Pallika H. Kanani, Andrew McCallum

COLT 2007 pp. 625-627

doi:10.1007/978-3-540-72927-3_46 /colt/2007/kanani2007colt-resource/

Abstract

We present a new class of problems, called resource-bounded information gathering for correlation clustering . Our goal is to perform correlation clustering under circumstances in which accuracy may be improved by augmenting the given graph with additional information. This information is obtained by querying an external source under resource constraints. The problem is to develop the most effective query selection strategy to minimize some loss function on the resulting partitioning. We motivate the problem using an entity resolution task.

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Cite

Text

Kanani and McCallum. "Resource-Bounded Information Gathering for Correlation Clustering." Annual Conference on Computational Learning Theory, 2007. doi:10.1007/978-3-540-72927-3_46

Markdown

[Kanani and McCallum. "Resource-Bounded Information Gathering for Correlation Clustering." Annual Conference on Computational Learning Theory, 2007.](https://mlanthology.org/colt/2007/kanani2007colt-resource/) doi:10.1007/978-3-540-72927-3_46

BibTeX

@inproceedings{kanani2007colt-resource,
  title     = {{Resource-Bounded Information Gathering for Correlation Clustering}},
  author    = {Kanani, Pallika H. and McCallum, Andrew},
  booktitle = {Annual Conference on Computational Learning Theory},
  year      = {2007},
  pages     = {625-627},
  doi       = {10.1007/978-3-540-72927-3_46},
  url       = {https://mlanthology.org/colt/2007/kanani2007colt-resource/}
}