Tackling redundancy in text summarization through different levels of language analysis

One of the main challenges to be addressed in text summarization concerns the detection of redundant information. This paper presents a detailed analysis of three methods for achieving such goal. The proposed methods rely on different levels of language analysis: lexical, syntactic and semantic. Moreover, they are also analyzed for detecting relevance in texts. The results show that semantic-based methods are able to detect up to 90% of redundancy, compared to only the 19% of lexical-based ones. This is also reflected in the quality of the generated summaries, obtaining better summaries when employing syntactic- or semantic-based approaches to remove redundancy.

Building bridges… and properties aplenty: cultural problems in Spanish real estate marketing for prospective British buyers

N.B. reproduced with permission of Peter Lang Verlag. For citation, please, use the original reference, that is Campos Pardillos, M.A. and Balteiro Fernández, I. 2009. “Building bridges… and properties aplenty: cultural problems in Spanish real estate marketing for prospective British buyers”. In: Guillén-Nieto, V., C. Marimón-Llorca and C. Vargas-Sierra. Eds. Intercultural Business Communication and Simulation and Gaming Methodology. Bern: Peter Lang. Pp. 155-174.