Quantifying French Document Complexity
This work addresses the challenge of quantifying text complexity for French documents, which is incremental as it extends existing methods to a new language and corpus.
The paper tackled the problem of measuring document complexity for French texts by introducing a new corpus and methodology, achieving a general-purpose measurement of text complexity in French.
Measuring a document's complexity level is an open challenge, particularly when one is working on a diverse corpus of documents rather than comparing several documents on a similar topic or working on a language other than English. In this paper, we define a methodology to measure the complexity of French documents, using a new general and diversified corpus of texts, the "French Canadian complexity level corpus", and a wide range of metrics. We compare different learning algorithms to this task and contrast their performances and their observations on which characteristics of the texts are more significant to their complexity. Our results show that our methodology gives a general-purpose measurement of text complexity in French.