Anecdote Recognition and Recommendation

Wei Song, Ruiji Fu, Lizhen Liu, Hanshi Wang, Ting Liu


Abstract
We introduce a novel task Anecdote Recognition and Recommendation. An anecdote is a story with a point revealing account of an individual person. Recommending proper anecdotes can be used as evidence to support argumentative writing or as a clue for further reading. We represent an anecdote as a structured tuple — < person, story, implication >. Anecdote recognition runs on archived argumentative essays. We extract narratives containing events of a person as the anecdote story. More importantly, we uncover the anecdote implication, which reveals the meaning and topic of an anecdote. Our approach depends on discourse role identification. Discourse roles such as thesis, main ideas and support help us locate stories and their implications in essays. The experiments show that informative and interpretable anecdotes can be recognized. These anecdotes are used for anecdote recommendation. The anecdote recommender can recommend proper anecdotes in response to given topics. The anecdote implication contributes most for bridging user interested topics and relevant anecdotes.
Anthology ID:
C16-1244
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Editors:
Yuji Matsumoto, Rashmi Prasad
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
2592–2602
Language:
URL:
https://aclanthology.org/C16-1244
DOI:
Bibkey:
Cite (ACL):
Wei Song, Ruiji Fu, Lizhen Liu, Hanshi Wang, and Ting Liu. 2016. Anecdote Recognition and Recommendation. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2592–2602, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Anecdote Recognition and Recommendation (Song et al., COLING 2016)
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PDF:
https://aclanthology.org/C16-1244.pdf