Retrieving and Ranking Similar Questions from Question-Answer Archives Using Topic Modelling and Topic Distribution Regression
June 12, 2016 Β· Declared Dead Β· π International Conference on Theory and Practice of Digital Libraries
"No code URL or promise found in abstract"
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Authors
Pedro Chahuara, Thomas Lampert, Pierre Gancarski
arXiv ID
1606.03783
Category
cs.IR: Information Retrieval
Cross-listed
cs.CL,
cs.LG
Citations
6
Venue
International Conference on Theory and Practice of Digital Libraries
Last Checked
4 months ago
Abstract
Presented herein is a novel model for similar question ranking within collaborative question answer platforms. The presented approach integrates a regression stage to relate topics derived from questions to those derived from question-answer pairs. This helps to avoid problems caused by the differences in vocabulary used within questions and answers, and the tendency for questions to be shorter than answers. The performance of the model is shown to outperform translation methods and topic modelling (without regression) on several real-world datasets.
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