Multiple indicators, partially ordered sets, and linear extensions: Multi-criterion ranking and prioritization

Patil, G. P.; Taillie, C.

doi:10.1023/b:eest.0000027209.93218.d9

Cited by 111 publications

(56 citation statements)

References 7 publications

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“…The number of linear extensions of the diagram grows with factorial complexity with respect to the number of vertices. This was not a concern for nine algorithms (vertices) in our case, but Patil and Taillie (2004) suggest using Markov Chain Monte Carlo sampling for very large sets if needed.…”

Section: Computational Complexitymentioning

confidence: 96%

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Performance measures for object detection evaluation

Ozdemir

Aksoy

Eckert

et al. 2010

Pattern Recognition Letters

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a b s t r a c tWe propose a new procedure for quantitative evaluation of object detection algorithms. The procedure consists of a matching stage for finding correspondences between reference and output objects, an accuracy score that is sensitive to object shapes as well as boundary and fragmentation errors, and a ranking step for final ordering of the algorithms using multiple performance indicators. The procedure is illustrated on a building detection task where the resulting rankings are consistent with the visual inspection of the detection maps.

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Section: Computational Complexitymentioning

confidence: 96%

“…Alternatively, Patil and Taillie (2004) proposed a ranking method that uses Hasse diagrams that represent partial orderings in the indicator space. A Hasse diagram is a planar graph used for representing partially ordered sets.…”

Section: Multi-criteria Rankingmentioning

confidence: 99%

Performance measures for object detection evaluation

Ozdemir

Aksoy

Eckert

et al. 2010

Pattern Recognition Letters

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show abstract

“…where Bin ( · ) is the operator that sets to 1 all the non-null elements of its argument (Patil and Taillie 2004 ) .…”

Section: The Weighting Proceduresmentioning

confidence: 99%

From Composite Indicators to Partial Orders: Evaluating Socio-Economic Phenomena Through Ordinal Data

Fattore

Maggino

Colombo

2012

Social Indicators Research Series

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The present debate on well-being measurement is clearly pointing out that a valuable evaluation process has to take into account many different and complementary aspects, in order to get a comprehensive picture of the problem and to effectively support decision-making. Assessing well-being requires sharing a conceptual framework about its determinants and about society and needs the identi fi cation of the most consistent and effective methodologies for building indicators and for communicating purposes. From a statistical perspective, one of the critical points concerns the preservation of the true nature of the socio-economic phenomena to be analysed. This calls for an adequate methodological approach. Several socio-economic phenomena have an intrinsic ordinal nature (e.g. material deprivation, democratic development, employment status), and correspondingly, there has been an increasing availability of ordinal datasets. Nevertheless, ordinal data have been often conceived as just a rough approximation of truly numerical and precise, yet non-observable, features, as if a numerical latent structure would exist under ordinal appearances. As a result, the search for alternative statistical procedures has been slowed down, and many epistemological, methodological and statistical problems regarding ordinal data treatment are still open and unsolved:

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“…In the second stage, a Hasse diagram is created from the set 269 of candidate phrases. Finally, an optimal set of keyphrases is selected using the ranking method described in [6].…”

Section: Extracting Keyphrases Using Multi-criterion Rankingmentioning

confidence: 99%

Turkish keyphrase extraction using multi-criterion ranking

Ozdemir

Çiçekli

2009

2009 24th International Symposium on Computer and Information Sciences

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Abstract-Keyphrases have been extensively used for indexing and searching in databases and information retrieval systems. In addition, they provide useful information about semantic content of a document. In this paper, we propose an algorithm for automating Turkish keyphrase extraction. Several features of candidate phrases are exploited and form the extraction task as a problem of finding optimal set of candidate phrases. We use multi-criterion ranking to tackle this problem.

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Multiple indicators, partially ordered sets, and linear extensions: Multi-criterion ranking and prioritization

Cited by 111 publications

References 7 publications

Performance measures for object detection evaluation

Performance measures for object detection evaluation

From Composite Indicators to Partial Orders: Evaluating Socio-Economic Phenomena Through Ordinal Data

Turkish keyphrase extraction using multi-criterion ranking

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