Graduate School and Research Center in Digital Sciences

Learning with the Web: Spotting named entities on the intersection of NERD and machine learning

Van Erp, Marieke; Rizzo, Giuseppe; Troncy, Raphaël

WWW 2013, 3rd International Workshop on Making Sense of Microposts (#MSM'13), Concept Extraction Challenge, May 13, 2013, Rio de Janeiro, Brazil

Microposts shared on social platforms instantaneously report facts, opinions or emotions. In these posts, entities are often used but they are continuously changing depending on what is currently trending. In such a scenario, recognising these named entities is a challenging task, for which off-the-shelf approaches are not well equipped. We propose NERD-ML, an approach that unifies the benefits of a crowd entity recognizer through Web entity extractors combined with the linguistic strengths of a machine learning classifier.  

Document Bibtex

Title:Learning with the Web: Spotting named entities on the intersection of NERD and machine learning
Keywords:Named Entity Recognition, NERD, Machine Learning
Type:Conference
Language:English
City:Rio de Janeiro
Country:BRAZIL
Date:
Department:Data Science
Eurecom ref:3968
Copyright: © ACM, 2013. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in WWW 2013, 3rd International Workshop on Making Sense of Microposts (#MSM'13), Concept Extraction Challenge, May 13, 2013, Rio de Janeiro, Brazil
Bibtex: @inproceedings{EURECOM+3968, year = {2013}, title = {{L}earning with the {W}eb: {S}potting named entities on the intersection of {NERD} and machine learning}, author = {{V}an {E}rp, {M}arieke and {R}izzo, {G}iuseppe and {T}roncy, {R}apha{\"e}l}, booktitle = {{WWW} 2013, 3rd {I}nternational {W}orkshop on {M}aking {S}ense of {M}icroposts (\#{MSM}'13), {C}oncept {E}xtraction {C}hallenge, {M}ay 13, 2013, {R}io de {J}aneiro, {B}razil }, address = {{R}io de {J}aneiro, {BRAZIL}}, month = {05}, url = {http://www.eurecom.fr/publication/3968} }
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