The tipping point: F-score as a function of the number of retrieved items

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Standard

The tipping point : F-score as a function of the number of retrieved items. / Guns, Raf; Lioma, Christina; Larsen, Birger.

In: Information Processing & Management, Vol. 48, No. 6, 2012, p. 1171-1180.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Guns, R, Lioma, C & Larsen, B 2012, 'The tipping point: F-score as a function of the number of retrieved items', Information Processing & Management, vol. 48, no. 6, pp. 1171-1180. https://doi.org/10.1016/j.ipm.2012.02.009

APA

Guns, R., Lioma, C., & Larsen, B. (2012). The tipping point: F-score as a function of the number of retrieved items. Information Processing & Management, 48(6), 1171-1180. https://doi.org/10.1016/j.ipm.2012.02.009

Vancouver

Guns R, Lioma C, Larsen B. The tipping point: F-score as a function of the number of retrieved items. Information Processing & Management. 2012;48(6):1171-1180. https://doi.org/10.1016/j.ipm.2012.02.009

Author

Guns, Raf ; Lioma, Christina ; Larsen, Birger. / The tipping point : F-score as a function of the number of retrieved items. In: Information Processing & Management. 2012 ; Vol. 48, No. 6. pp. 1171-1180.

Bibtex

@article{b60af43f664a4c7a92606e154cd54bca,
title = "The tipping point: F-score as a function of the number of retrieved items",
abstract = "One of the best known measures of information retrieval (IR) performance is the F-score, the harmonic mean of precision and recall. In this article we show that the curve of the F-score as a function of the number of retrieved items is always of the same shape: a fast concave increase to a maximum, followed by a slow decrease. In other words, there exists a single maximum, referred to as the tipping point, where the retrieval situation is {\textquoteleft}ideal{\textquoteright} in terms of the F-score. The tipping point thus indicates the optimal number of items to be retrieved, with more or less items resulting in a lower F-score. This empirical result is found in IR and link prediction experiments and can be partially explained theoretically, expanding on earlier results by Egghe. We discuss the implications and argue that, when comparing F-scores, one should compare the F-score curves{\textquoteright} tipping points.",
keywords = "Information Retrieval, Evaluation",
author = "Raf Guns and Christina Lioma and Birger Larsen",
year = "2012",
doi = "10.1016/j.ipm.2012.02.009",
language = "English",
volume = "48",
pages = "1171--1180",
journal = "Information Processing & Management",
issn = "0306-4573",
publisher = "Elsevier",
number = "6",

}

RIS

TY - JOUR

T1 - The tipping point

T2 - F-score as a function of the number of retrieved items

AU - Guns, Raf

AU - Lioma, Christina

AU - Larsen, Birger

PY - 2012

Y1 - 2012

N2 - One of the best known measures of information retrieval (IR) performance is the F-score, the harmonic mean of precision and recall. In this article we show that the curve of the F-score as a function of the number of retrieved items is always of the same shape: a fast concave increase to a maximum, followed by a slow decrease. In other words, there exists a single maximum, referred to as the tipping point, where the retrieval situation is ‘ideal’ in terms of the F-score. The tipping point thus indicates the optimal number of items to be retrieved, with more or less items resulting in a lower F-score. This empirical result is found in IR and link prediction experiments and can be partially explained theoretically, expanding on earlier results by Egghe. We discuss the implications and argue that, when comparing F-scores, one should compare the F-score curves’ tipping points.

AB - One of the best known measures of information retrieval (IR) performance is the F-score, the harmonic mean of precision and recall. In this article we show that the curve of the F-score as a function of the number of retrieved items is always of the same shape: a fast concave increase to a maximum, followed by a slow decrease. In other words, there exists a single maximum, referred to as the tipping point, where the retrieval situation is ‘ideal’ in terms of the F-score. The tipping point thus indicates the optimal number of items to be retrieved, with more or less items resulting in a lower F-score. This empirical result is found in IR and link prediction experiments and can be partially explained theoretically, expanding on earlier results by Egghe. We discuss the implications and argue that, when comparing F-scores, one should compare the F-score curves’ tipping points.

KW - Information Retrieval

KW - Evaluation

U2 - 10.1016/j.ipm.2012.02.009

DO - 10.1016/j.ipm.2012.02.009

M3 - Journal article

VL - 48

SP - 1171

EP - 1180

JO - Information Processing & Management

JF - Information Processing & Management

SN - 0306-4573

IS - 6

ER -

ID: 38240608