Abstract
Wikipedia has become a widely accepted reference point for information of all kinds; real-world events (e.g., natural disasters, man-made incidents, and political events) as well as specific entities like politicians, celebrities, and entities involved in an event. Due to its open construction and negotiation, Wikipedia is an important new cultural and societal phenomenon, and the content of Wikipedia articles is a valuable source for different applications. For instance, the edit history and view logs of Wikipedia can be leveraged for detecting an event and its associated entities. In this study, we analyze temporal anchor texts extracted from the edit history. We propose a model for Wikipedia and anchor texts viewed as a temporal resource and a probabilistic method for ranking temporal anchor texts. Our preliminary results show that relevant anchor texts composed of evolving information (e.g., the changes of names and semantic roles, as well as evolving context) that reflects societal trends and perceptions,
thus being candidates for capturing entity evolution.
thus being candidates for capturing entity evolution.
| Originalsprog | Engelsk |
|---|---|
| Titel | SIGIR 2014 Workshop on Temporal, Social and Spatially-aware Information Access (TAIA'2014) |
| Antal sider | 4 |
| Publikationsdato | 2014 |
| Sider | 1-4 |
| Status | Udgivet - 2014 |
| Udgivet eksternt | Ja |