# Action-Centered Information Retrieval

## TL;DR

This paper introduces a novel approach to information retrieval involving event sequences and their effects, using formal logic and answer set programming to improve semantic matching beyond traditional methods.

## Contribution

It presents a formalization of event-based IR using an action language and automates the retrieval process with answer set programming, addressing semantic complexity.

## Key findings

- Formalization of event-based IR using action language
- Implementation of IR automation with answer set programming
- Enhanced semantic matching for event sequence documents

## Abstract

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.