Abstract
Disambiguation to Wikipedia (D2W) is the task of linking mentions of concepts in text to their corresponding Wikipedia entries. Most previous work has focused on linking terms in formal texts (e.g. newswire) to Wikipedia. Linking terms in short informal texts (e.g. tweets) is difficult for systems and humans alike as they lack a rich disambiguation context. We first evaluate an existing Twitter dataset as well as the D2W task in general. We then test the effects of two tweet context expansion methods, based on tweet authorship and topic-based clustering, on a state-of-the-art D2W system and evaluate the results.
| Original language | English (US) |
|---|---|
| Pages | 441-456 |
| Number of pages | 16 |
| State | Published - 2012 |
| Externally published | Yes |
| Event | 24th International Conference on Computational Linguistics, COLING 2012 - Mumbai, India Duration: Dec 8 2012 → Dec 15 2012 |
Other
| Other | 24th International Conference on Computational Linguistics, COLING 2012 |
|---|---|
| Country/Territory | India |
| City | Mumbai |
| Period | 12/8/12 → 12/15/12 |
Keywords
- Disambiguation context
- Disambiguation to wikipedia (D2W)
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Language and Linguistics
- Linguistics and Language
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