Towards a Flexible Author Name Disambiguation Framework
Bolikowski, Łukasz; Dendek, Piotr Jan
- Towards a Digital Mathematics Library. Bertinoro, Italy, July 20-21st, 2011, Publisher: Masaryk University Press(Brno, Czech Republic), page 27-37
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topBolikowski, Łukasz, and Dendek, Piotr Jan. "Towards a Flexible Author Name Disambiguation Framework." Towards a Digital Mathematics Library. Bertinoro, Italy, July 20-21st, 2011. Brno, Czech Republic: Masaryk University Press, 2011. 27-37. <http://eudml.org/doc/220965>.
@inProceedings{Bolikowski2011,
abstract = {In this paper we propose a flexible, modular framework for author name disambiguation. Our solution consists of the core which orchestrates the disambiguation process, and replaceable modules performing concrete tasks. The approach is suitable for distributed computing, in particular it maps well to the MapReduce framework. We describe each component in detail and discuss possible alternatives. Finally, we propose procedures for calibration and evaluation of the described system.},
author = {Bolikowski, Łukasz, Dendek, Piotr Jan},
booktitle = {Towards a Digital Mathematics Library. Bertinoro, Italy, July 20-21st, 2011},
keywords = {name disambiguation; problem decomposition; scoring functions; single-linkage clustering; MapReduce framework; machine learning},
location = {Brno, Czech Republic},
pages = {27-37},
publisher = {Masaryk University Press},
title = {Towards a Flexible Author Name Disambiguation Framework},
url = {http://eudml.org/doc/220965},
year = {2011},
}
TY - CLSWK
AU - Bolikowski, Łukasz
AU - Dendek, Piotr Jan
TI - Towards a Flexible Author Name Disambiguation Framework
T2 - Towards a Digital Mathematics Library. Bertinoro, Italy, July 20-21st, 2011
PY - 2011
CY - Brno, Czech Republic
PB - Masaryk University Press
SP - 27
EP - 37
AB - In this paper we propose a flexible, modular framework for author name disambiguation. Our solution consists of the core which orchestrates the disambiguation process, and replaceable modules performing concrete tasks. The approach is suitable for distributed computing, in particular it maps well to the MapReduce framework. We describe each component in detail and discuss possible alternatives. Finally, we propose procedures for calibration and evaluation of the described system.
KW - name disambiguation; problem decomposition; scoring functions; single-linkage clustering; MapReduce framework; machine learning
UR - http://eudml.org/doc/220965
ER -
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