Studying the influence of adding lexical-semantic knowledge to Principal Component Analysis technique for multilingual summarization
Abstract
The objective of automatic text summarization is to reduce the dimension of a text keeping the relevant information. In this paper we analyse and apply the language-independent Principal Component Analysis technique for generating extractive single-document multilingual summaries. This technique will be studied to evaluate its performance with and without adding lexical-semantic knowledge through language-dependent resources and tools. Experiments were conducted using two different corpora: newswire and Wikipedia articles in three languages (English, German and Spanish) to validate the use of this technique in several scenarios. The proposed approaches show very competitive results compared to multilingual available systems, indicating that, although there is still room for improvement with respect to the technique and the type of knowledge to be taken into consideration, this has great potential for being applied in other contexts and for other languages.
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