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    <abstract>Comparable or parallel corpora are beneficial for many NLP tasks. The automatic collection of corpora enables large-scale resources, even for less-resourced languages, which in turn can be useful for deducing rules and patterns for text rewriting algorithms, a subtask of automatic text simplification. We present two methods for the alignment of Swedish easy-to-read text segments to text segments from a reference corpus. The first method (M1) was originally developed for the task of text reuse detection, measuring sentence similarity by a modified version of a TF-IDF vector space model. A second method (M2), also accounting for part-of-speech tags, was developed, and the methods were compared. For evaluation, a crowdsourcing platform was built for human judgement data collection, and preliminary results showed that cosine similarity relates better to human ranks than the Dice coefficient. We also saw a tendency that including syntactic context to the TF-IDF vector space model is beneficial for this kind of paraphrase alignment task.</abstract>
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%0 Conference Proceedings
%T Similarity-Based Alignment of Monolingual Corpora for Text Simplification Purposes
%A Albertsson, Sarah
%A Rennes, Evelina
%A Jönsson, Arne
%Y Brunato, Dominique
%Y Dell’Orletta, Felice
%Y Venturi, Giulia
%Y François, Thomas
%Y Blache, Philippe
%S Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F albertsson-etal-2016-similarity
%X Comparable or parallel corpora are beneficial for many NLP tasks. The automatic collection of corpora enables large-scale resources, even for less-resourced languages, which in turn can be useful for deducing rules and patterns for text rewriting algorithms, a subtask of automatic text simplification. We present two methods for the alignment of Swedish easy-to-read text segments to text segments from a reference corpus. The first method (M1) was originally developed for the task of text reuse detection, measuring sentence similarity by a modified version of a TF-IDF vector space model. A second method (M2), also accounting for part-of-speech tags, was developed, and the methods were compared. For evaluation, a crowdsourcing platform was built for human judgement data collection, and preliminary results showed that cosine similarity relates better to human ranks than the Dice coefficient. We also saw a tendency that including syntactic context to the TF-IDF vector space model is beneficial for this kind of paraphrase alignment task.
%U https://aclanthology.org/W16-4118/
%P 154-163

Markdown (Informal)

[Similarity-Based Alignment of Monolingual Corpora for Text Simplification Purposes](https://aclanthology.org/W16-4118/) (Albertsson et al., CL4LC 2016)

• Similarity-Based Alignment of Monolingual Corpora for Text Simplification Purposes (Albertsson et al., CL4LC 2016)

ACL

• Sarah Albertsson, Evelina Rennes, and Arne Jönsson. 2016. Similarity-Based Alignment of Monolingual Corpora for Text Simplification Purposes. In Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC), pages 154–163, Osaka, Japan. The COLING 2016 Organizing Committee.