arXiv subjects
Publications and source records attributed to Alejandro Molina.
This article focuses on the description and evaluation of a new unsupervised learning method of clustering of definitions in Spanish according to their semantic. Textual Energy was used as a clustering measure, and we study an adaptation of the Precision and Recall to evaluate our method.
Previous works demonstrated that Automatic Text Summarization (ATS) by sentences extraction may be improved using sentence compression. In this work we present a sentence compressions approach guided by level-sentence discourse segmentation and probabilistic language models (LM). The results presented here show that the proposed solution is able to generate coherent summaries with grammatical compressed sentences. The approach is simple enough to be transposed into other languages.