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Action-Centered Information Retrieval

Published online by Cambridge University Press:  09 August 2019

MARCELLO BALDUCCINI  and
EMILY C. LEBLANC
MARCELLO BALDUCCINI
Affiliation:
Saint Joseph’s University, Philadelphia, PA, USA (e-mail: marcello.balduccini@gmail.com)
EMILY C. LEBLANC
Affiliation:
Drexel University, Philadelphia, PA, USA (e-mail: ecl38@drexel.edu)
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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.

Keywords

reasoning about actions and changeanswer set programminginformation retrieval
Type
Technical Note
Information
Theory and Practice of Logic Programming , Volume 20 , Issue 2 , March 2020 , pp. 249 - 272
Copyright
© Cambridge University Press 2019 

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