Time-travel Translator: Automatically Contextualizing News Articles

Fully understanding an older news article requires context knowledge from the time of article creation. Finding information about such context is a tedious and time-consuming task, which distracts the reader. Simple contextualization via Wikification is not sufficient here. The retrieved context information has to be time-aware, concise (not full Wiki pages) and focused on the coherence of the article topic. In this paper, we present Contextualizer, a web-based system that acquires additional information for supporting interpretations of a news article of interest that requires a mapping, in this case, a kind of time-travel translation between present context knowledge and context knowledge at time of text creation. For a given article, the system provides a GUI that allows users to highlight their interested keywords which are then used to construct appropriate queries for retrieving contextualization candidates. Contextualizer exploits different kinds of information such as temporal similarity and textual complementarity to re-rank the candidates and presents to users in a friendly and interactive web-based interface.