On inference rules of logic-based information retrieval systems

Chen, Patrick Shicheng

doi:10.1016/0306-4573(94)90023-x

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…For example, assuming that sparrows are similar to pigeons (sparrow∼pigeon), we may infer that migrating sparrows are similar to migrating pigeons (migrate⊕sparrow∼migrate⊕pigeon). The Modus Substituens rule originates from a plausible inference rule of the same name documented in (Bruza, 1993; Chen, 1994).…”

Section: Similarity Versus Aboutnessmentioning

confidence: 99%

Aboutness from a commonsense perspective

Bruza

Song

Wong

2000

J. Am. Soc. Inf. Sci.

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Information retrieval (IR) is driven by a process that decides whether a document is about a query. Recent attempts spawned from a logic‐based information retrieval theory have formalized properties characterizing “aboutness,” but no consensus has yet been reached. The proposed properties are largely determined by the underlying framework within which aboutness is defined. In addition, some properties are only sound within the context of a given IR model, but are not sound from the perspective of the user. For example, a common form of aboutness, namely overlapping aboutness, implies precision degrading properties such as compositional monotonicity. Therefore, the motivating question for this article is: independent of any given IR model, and examined within an information‐based, abstract framework, what are commonsense properties of aboutness (and its dual, nonaboutness)? We propose a set of properties characterizing aboutness and nonaboutness from a commonsense perspective. Special attention is paid to the rules prescribing conservative behavior of aboutness with respect to information composition. The interaction between aboutness and nonaboutness is modeled via normative rules. The completeness, soundness, and consistency of the aboutness proof systems are analyzed and discussed. A case study based on monotonicity shows that many current IR systems are either monotonic or nonmonotonic. An interesting class of IR models, namely those that are conservatively monotonic, is identified.

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Section: Similarity Versus Aboutnessmentioning

confidence: 99%

Aboutness from a commonsense perspective

Bruza

Song

Wong

2000

J. Am. Soc. Inf. Sci.

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“…We will then compare those dimensions with the usefulness measure we are proposing here. However, to have a fair comparison, we need to reformulate those dimensions in a logical setting (Abdulahhad et al ., 2019; Lalmas, 1998; Chen, 1994).…”

Section: An Example Of Application To Irmentioning

confidence: 99%

Usefulness of Information for Achieving Goals with Disjunctive Premises

da Costa Pereira,

Cholvy

2024

The Knowledge Engineering Review

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We propose a logic-based framework to model a system whose aim is to help provide the user with those pieces of information that are useful with respect to his/her current information need, as well as relevant to his/her query. More precisely, we propose three measures of information usefulness which take into account the fact that the user can be represented as a cognitive agent endowed with some beliefs—a partial “picture” about what it already knows—and goals—a certain state of affairs in which the agent would like to be. This paper extends a previous version of the framework by considering a more realistic hypothesis, according to which there are several ways to achieve goals. We present three different approaches: the binary approach, the ordinal approach, and the numerical approach. We take information retrieval (IR) as a particular application domain, and we compare some existing measures with the usefulness measure we introduce here.

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“…(C) Logic IR models. See Chen (1994), Chiaramella (1992), Crestani and van Rijsbergen (1994, 1995a, b), daSilva and Milidiu (1993), Fuhr and Roelleke (1997, 1998), Huibers and Bruza (1996), Lalmas and van Rijsbergen (1992, 1993), Meghini et al (1993), Nie (1989, 1992), Nie et al (1995), Sebastiani (1994), van Rijsbergen (1986a, b, >1989), Watters (1989), and Wong and Yao (1995).…”

Section: Introductionmentioning

confidence: 99%