A Probabilistic Framework for Time-Sensitive Search
Dhruv Gupta, Klaus Berberich · MPG.PuRe (Max Planck Society) · 2016
This research article presents TimeSearch, a probabilistic framework, that competed in the Temporalia-2 task.The subtasks in Temporalia-2 require an information retrieval system to be informed of the temporal expressions (e.g.1990s) in documents and queries to identify relevant documents.Analysis of these temporal expressions like natural language understanding is challenging.TimeSearch utilizes an unique time model to address these challenges and to understand temporal expressions.Building on this model it identifies interesting time intervals for a given keyword query.These time intervals are then used to rank and diversify documents in a time-sensitive manner.In this article we describe TimeSearch and its performance in Temporalia-2.