Author Disambiguation using Error-driven Machine Learning with a Ranking Loss Function

@inproceedings{Culotta2007AuthorDU,
  title={Author Disambiguation using Error-driven Machine Learning with a Ranking Loss Function},
  author={Aron Culotta and Pallika Kanani and Robert Hall and Michael Wick and Andrew McCallum},
  year={2007}
}
Author disambiguation is the problem of determining whether records in a publications database refer to the same person. A common supervised machine learning approach is to build a classifier to predict whether a pair of records is coreferent, followed by a clustering step to enforce transitivity. However, this approach ignores powerful evidence obtainable by examining sets (rather than pairs) of records, such as the number of publications or co-authors an author has. In this paper we propose a… CONTINUE READING
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