Abstract
Many articles in the online encyclopedia Wikipedia have hyperlinks to ambiguous article titles; these ambiguous links should be replaced with links to unambiguous articles, a process known as disambiguation. We propose a novel statistical topic model based on link text, which we refer to as the Link Text Topic Model (LTTM), that we use to suggest new link targets for ambiguous links. To evaluate our model, we describe a method for extracting ground truth for this link disambiguation task from edits made to Wikipedia in a specific time period. We use this ground truth to demonstrate the superiority of LTTM over other existing link- and content-based approaches to disambiguating links in Wikipedia. Finally, we build a web service that uses LTTM to make suggestions to human editors wanting to fix ambiguous links in Wikipedia.
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