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Statements

Subject Item
n2:RIV%2F61989592%3A15310%2F13%3A33146213%21RIV14-MSM-15310___
rdf:type
skos:Concept n12:Vysledek
dcterms:description
In many practical situations, it is necessary to describe an image in words. From the purely logical viewpoint, to describe the same object, we can use concepts of different levels of abstraction: e.g., when the image includes a dog, we can say that it is a dog, or that it is a mammal, or that it is a German Shepherd. In such situations, humans usually select a concept which, to them, in the most natural; this concept is called the basic level concept. However, the notion of a basic level concept is difficult to describe in precise terms; as a result, computer systems for image analysis are not very good in selecting concepts of basic level. At first glance, since the question is how to describe human decisions, we should use notions from a (well-developed) decision theory - such as the notion of utility. However, in practice, a well-founded utility-based approach to selecting basic level concepts is not as efficient as a purely heuristic %22similarity%22 approach. In this paper, we explain this seeming contradiction by showing that the similarity approach can be actually explained in utility terms - if we use a more accurate description of the utility of different alternatives. In many practical situations, it is necessary to describe an image in words. From the purely logical viewpoint, to describe the same object, we can use concepts of different levels of abstraction: e.g., when the image includes a dog, we can say that it is a dog, or that it is a mammal, or that it is a German Shepherd. In such situations, humans usually select a concept which, to them, in the most natural; this concept is called the basic level concept. However, the notion of a basic level concept is difficult to describe in precise terms; as a result, computer systems for image analysis are not very good in selecting concepts of basic level. At first glance, since the question is how to describe human decisions, we should use notions from a (well-developed) decision theory - such as the notion of utility. However, in practice, a well-founded utility-based approach to selecting basic level concepts is not as efficient as a purely heuristic %22similarity%22 approach. In this paper, we explain this seeming contradiction by showing that the similarity approach can be actually explained in utility terms - if we use a more accurate description of the utility of different alternatives.
dcterms:title
Similarity Approach to Defining Basic Level of Concepts Explained from the Utility Viewpoint Similarity Approach to Defining Basic Level of Concepts Explained from the Utility Viewpoint
skos:prefLabel
Similarity Approach to Defining Basic Level of Concepts Explained from the Utility Viewpoint Similarity Approach to Defining Basic Level of Concepts Explained from the Utility Viewpoint
skos:notation
RIV/61989592:15310/13:33146213!RIV14-MSM-15310___
n12:predkladatel
n15:orjk%3A15310
n4:aktivita
n5:P
n4:aktivity
P(EE2.3.20.0060)
n4:dodaniDat
n13:2014
n4:domaciTvurceVysledku
n17:9965181
n4:druhVysledku
n10:O
n4:duvernostUdaju
n11:S
n4:entitaPredkladatele
n16:predkladatel
n4:idSjednocenehoVysledku
105104
n4:idVysledku
RIV/61989592:15310/13:33146213
n4:jazykVysledku
n18:eng
n4:klicovaSlova
Basic Level Concepts, Similarity
n4:klicoveSlovo
n14:Basic%20Level%20Concepts n14:Similarity
n4:kontrolniKodProRIV
[5B3A1823855B]
n4:obor
n7:IN
n4:pocetDomacichTvurcuVysledku
1
n4:pocetTvurcuVysledku
2
n4:projekt
n8:EE2.3.20.0060
n4:rokUplatneniVysledku
n13:2013
n4:tvurceVysledku
Trnečka, Martin Lorkowski, Joe
n6:organizacniJednotka
15310