Corpus-based Sentence Deletion and Split Decisions for Spanish Text Simplification
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| Format: | Artículo científico |
| Language: | en |
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Instituto Politécnico Nacional
2013
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| _version_ | 1876466944069074944 |
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| author | Sanja Štajner |
| author_facet | Sanja Štajner |
| contents | Corpus-based Sentence Deletion and Split Decisions for Spanish Text Simplification Sanja Štajner Biljana Drndarevic Horacio Saggion Computación supervised learning sentence classification Spanish text simplification This study addresses the automatic simplification of texts in Spanish in order to make them more accessible to people with cognitive disabilities. A corpus analysis of original and manually simplified news articles was undertaken in order to identify and quantify relevant operations to be implemented in a text simplification system. The articles were further compared at sentence and text level by means of automatic feature extraction and various machine learning classification algorithms, using three different groups of features (POS frequencies, syntactic information, and text complexity measures) with the aim of identifying features that help separate original documents from their simple equivalents. Finally, it was investigated whether these features can be used to decide upon simplification operations to be carried out at the sentence level (split, delete, and reduce). Automatic classification of original sentences into those to be kept and those to be eliminated outperformed the classification that was previously conducted on the same corpus. Kept sentences were further classified into those to be split or significantly reduced in length and those to be left largely unchanged, with the overall F-measure up to 0.92. Both experiments were conducted and compared on two different sets of features: all features and the best subset returned by an attribute selection algorithm. 2013 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61527437015 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.2 Vol.17 |
| format | Artículo científico |
| id | redalyc_61527437015 |
| institution | Redalyc |
| language | en |
| publishDate | 2013 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Corpus-based Sentence Deletion and Split Decisions for Spanish Text Simplification Sanja Štajner Computación supervised learning sentence classification Spanish text simplification Corpus-based Sentence Deletion and Split Decisions for Spanish Text Simplification Sanja Štajner Biljana Drndarevic Horacio Saggion Computación supervised learning sentence classification Spanish text simplification This study addresses the automatic simplification of texts in Spanish in order to make them more accessible to people with cognitive disabilities. A corpus analysis of original and manually simplified news articles was undertaken in order to identify and quantify relevant operations to be implemented in a text simplification system. The articles were further compared at sentence and text level by means of automatic feature extraction and various machine learning classification algorithms, using three different groups of features (POS frequencies, syntactic information, and text complexity measures) with the aim of identifying features that help separate original documents from their simple equivalents. Finally, it was investigated whether these features can be used to decide upon simplification operations to be carried out at the sentence level (split, delete, and reduce). Automatic classification of original sentences into those to be kept and those to be eliminated outperformed the classification that was previously conducted on the same corpus. Kept sentences were further classified into those to be split or significantly reduced in length and those to be left largely unchanged, with the overall F-measure up to 0.92. Both experiments were conducted and compared on two different sets of features: all features and the best subset returned by an attribute selection algorithm. 2013 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61527437015 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.2 Vol.17 |
| title | Corpus-based Sentence Deletion and Split Decisions for Spanish Text Simplification |
| topic | Computación supervised learning sentence classification Spanish text simplification |
| url | https://www.redalyc.org/articulo.oa?id=61527437015 |