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Implicit readabilit...
Implicit readability ranking using the latent variable of a Bayesian Probit model
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- Falkenjack, Johan (author)
- SICS East Swedish ICT AB,NLPLAB
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- Jönsson, Arne, 1955- (author)
- SICS East Swedish ICT AB
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(creator_code:org_t)
- Uppsala universitet Humanistisk-samhällsvetenskapliga vetenskapsområdet, 2016
- 2016
- English.
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In: CL4LC 2016 - Computational Linguistics for Linguistic Complexity. - : Uppsala universitet Humanistisk-samhällsvetenskapliga vetenskapsområdet. - 9784879747099 ; , s. 104-112
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Abstract
Subject headings
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- Data driven approaches to readability analysis for languages other than English has been plagued by a scarcity of suitable corpora. Often, relevant corpora consist only of easy-to-read texts with no rank information or empirical readability scores, making only binary approaches, such as classification, applicable. We propose a Bayesian, latent variable, approach to get the most out of these kinds of corpora. In this paper we present results on using such a model for readability ranking. The model is evaluated on a preliminary corpus of ranked student texts with encourag- ing results. We also assess the model by showing that it performs readability classification on par with a state of the art classifier while at the same being transparent enough to allow more sophisticated interpretations.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Language Technology (hsv//eng)
Publication and Content Type
- ref (subject category)
- kon (subject category)
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