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 doc...

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Published in:Theory and practice of logic programming 2020-03, Vol.20 (2), p.249-272
Main Authors: BALDUCCINI, MARCELLO, LEBLANC, EMILY C.
Format: Article
Language:English
Subjects:
Declarative programming
Information retrieval
Mathematical programming
Side effects
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description 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.
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ispartof Theory and practice of logic programming, 2020-03, Vol.20 (2), p.249-272
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1475-3081
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subjects Declarative programming
Information retrieval
Mathematical programming
Side effects
title Action-Centered Information Retrieval
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