A lot of future-related information is available in news articles or Web pages. This information can however differ to large extent and may fluctuate over time. It is therefore difficult for users to manually compare and aggregate it, and to re-construct the most probable course of future events. In this paper we approach a problem of automatically generating summaries of future events related to queries using data obtained from news archive collections or from the Web. We propose two methods, explicit and implicit future-related information detection. The former is based on analyzing the context of future temporal expressions in documents, while the latter relies on detecting periodical patterns in historical document collections. We present a graph-based visualization of future-related information and demonstrate its usefulness through several examples.
Jatowt et al. REF proposed a method for future event extraction from news articles or Web pages.
Supporting analysis of future-related information in news archives and the web
JCDL '09
Computer Science