Estimating cognitive text complexity with aggregation of quantile-based models

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A3KLG9ANG" target="_blank" >RIV/00216208:11320/23:3KLG9ANG - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175547918&doi=10.28995%2f2075-7182-2023-22-525-538&partnerID=40&md5=8eea1c304a8f0a5bae343687a9a47675" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175547918&doi=10.28995%2f2075-7182-2023-22-525-538&partnerID=40&md5=8eea1c304a8f0a5bae343687a9a47675</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.28995/2075-7182-2023-22-525-538" target="_blank" >10.28995/2075-7182-2023-22-525-538</a>

Result language

angličtina

Original language name

Estimating cognitive text complexity with aggregation of quantile-based models

Original language description

"In this paper, we introduce a novel approach to estimating the cognitive complexity of a text at different levels of language: phonetic, morphemic, lexical, and syntactic. The proposed method detects tokens with an abnormal frequency of complexity scores. The frequencies are taken from the empirical distributions calculated over the reference corpus of texts. We use the Russian Wikipedia for this purpose. Ensemble models are combined from individual models from different language levels. We created datasets of pairs of text fragments taken from social studies textbooks of different grades to train the ensembles. Empirical evidence shows that the proposed approach outperforms existing methods, such as readability indices, in estimating text complexity in terms of accuracy. The purpose of this study is to create one of the important components of the system of recommendation of scientific and educational content. © Dialogue 2023.All rights reserved."

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

—

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

"Komp'ut. Lingvist. Intellekt. Tehnol."

ISBN

—

ISSN

2221-7932

e-ISSN

—

Number of pages

15

Pages from-to

539-553

Publisher name

ABBYY PRODUCTION LLC

Place of publication

—

Event location

Cham

Event date

Jan 1, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—