Action-Centered Information Retrieval
  Information Retrieval (IR) aims at retrieving documents that are most
relevant to a query provided by a user. Traditional techniques rely mostly on
syntactic methods. In some cases, however, links at a deeper semantic level
must be considered. In this paper, we explore a type of IR task in which
documents describe sequences of events, and queries are about the state of the
world after such events. In this context, successfully matching documents and
query requires considering the events' possibly implicit, uncertain effects and
side-effects. We begin by analyzing the problem, then propose an action
language based formalization, and finally automate the corresponding IR task
using Answer Set Programming.
