Kevin Ros
ABSTRACT
Online discussions are a ubiquitous aspect of everyday life. An Internet user who interacts with an online discussion may benefit from seeing hyperlinks to webpages relevant to the discussion because the relevant webpages can provide added context, act as citations for background sources, or condense information so that conversations can proceed seamlessly at a high level. In this paper, we propose and study a new task of retrieving relevant webpages given an online discussion. We frame the task as a novel retrieval problem where we treat a sequence of comments in an online discussion as a query and use such a query to retrieve relevant webpages. We construct a new data set using Reddit, an online discussion forum, to study this new problem. We explore and evaluate multiple representative retrieval methods to examine their effectiveness for solving this new problem. We also propose to leverage the comments that contain hyperlinks as training data to enable supervised learning and further improve retrieval performance. We find that results using modern retrieval methods are promising and that leveraging comments with hyperlinks as training data can further improve performance. We release our data set and code to enable additional research in this direction.
Supplemental Material
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Index Terms
- Retrieving Webpages Using Online Discussions
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