Towards an Active Learning System for Company Name Disambiguation in Microblog Streams

  • Maria-Hendrike Peetz
  • Damiano Spina
  • Julio Gonzalo
  • Maarten de Rijke
CLEF 2013 Evaluation Labs and Workshop Online Working Notes, 2013

In this paper we describe the collaborative participation of UvA & UNED at RepLab 2013. We propose an active learning approach for the filtering subtask, using features based on the detected semantics in the tweet (using Entity Linking with Wikipedia), as well as tweet-inherent features such as hashtags and usernames. The tweets manually inspected during the active learning process is at most 1% of the test data. While our baseline does not perform well, we can see that active learning does improve the results.

@inproceedings{replab2013uvauned,
  author = {Peetz, M.H. and Spina D. and Gonzalo, J. and de Rijke, M.},
  booktitle = {{CLEF 2013 Eval. Labs and Workshop Online Working Notes}},
  date-modified = {2013-10-14 10:45:42 +0000},
  organization = {CLEF},
  title = {{Towards an Active Learning System for Company Name Disambiguation in Microblog Streams}},
  year = {2013}
}
Damiano Spina
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