Open-Set Web Genre Identification Using Distributional Features and Nearest Neighbors Distance Ratio

Pritsos, Dimitrios A.; Rocha, Anderson; Stamatatos, Efstathios

doi:10.1007/978-3-030-15719-7_1

Cited by 2 publications

(2 citation statements)

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“…There are also a few studies [32,112,113] utilizing Nearest Neighbor models on this topic. Júnior et al [20] pro-posed the Nearest Neighbor Distance Ratio (NNDR) classifier, which in turn, is a multiclass open-set extension for the Nearest Neighbor (NN) algorithm and is referred to as Open Set NN (OSNN).…”

Section: Statistical Approachesmentioning

confidence: 99%

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A Survey on Open Set Recognition

Mahdavi,

Carvalho

2021

Preprint

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Recognition (OSR) is about dealing with unknown situations that were not learned by the models during training. In this paper, we provide a survey of existing works about OSR and distinguish their respective advantages and disadvantages to help out new researchers interested in the subject. The categorization of OSR models is provided along with an extensive summary of recent progress. Additionally, the relationships between OSR and its related tasks including multi-class classification and novelty detection are analyzed. It is concluded that OSR can appropriately deal with unknown instances in the real-world where capturing all possible classes in the training data is not practical. Lastly, applications of OSR are highlighted and some new directions for future research topics are suggested.

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Section: Statistical Approachesmentioning

confidence: 99%

“…This ratio is defined by = ( , )∕ ( , ), where Euclidean distance of two samples and ′ is shown by ( , ′ ). Recently, Pritsos et al [112] viewed WGI as an open-set task and applied the NNDR algorithm to its setup to better deal with incomplete genre palettes.…”

Section: Statistical Approachesmentioning

confidence: 99%