Finding the Best Approach for Multi-lingual Text Summarisation: A Comparative Analysis

Proceedings of Recent Advances in Natural Language Processing, pages 194–201, Hissar, Bulgaria, 12-14 September 2011. Finding the Best Approach for Multi-lingual Text Summarisation: A Comparative Analysis Elena Lloret University of Alicante Apdo. de Correos 99 E-03080, Alicante, Spain elloret@dlsi.ua.es Manuel Palomar University of Alicante Apdo. de Correos 99 E-03080, Alicante, Spain mpalomar@dlsi.ua.es Abstract This paper addresses the problem of multi- lingual text summarisation. The goal is to analyse three approaches for generat- ing summaries in four languages (English, Spanish, German and French), in order to determine the best one to adopt when tack- ling this issue. The proposed approaches rely on: i) language-independent tech- niques; ii) language-specific resources; and iii) machine translation resources ap- plied to a mono-lingual summariser. The evaluation carried out employing the JRC corpus – a corpus specifically created for multi-lingual summarisation – shows that the approach which uses language- specific resources is the most appropriate in our comparison framework, performing better than state-of-the-art multi-lingual summarisers. Moreover, the readability assessment conducted over the resulting summaries for this approach proves that they are also very competitive with respect to their quality. 1 Introduction In the current society, information plays a crucial role that brings competitive advantages to users, when it is managed correctly. However, due to the vast amount of available information, users cannot cope with it, and therefore research into new meth- ods and approaches based on Natural Language Processing (NLP) is crucial, thus resulting in con- siderable benefits for the society. Specifically, one of these NLP research areas is Text Summarisa- tion (TS) which is essential to condense informa- tion keeping, at the same time, the most relevant facts or pieces of information. However, to pro- duce a summary automatically is very challeng- ing. Issues such as redundancy, temporal dimen- sion, coreference or sentence ordering, to name a few, have to be taken into consideration especially when summarising a set of documents (multi- document summarisation), thus making this field even more difficult (Goldstein et al., 2000). Such difficulty also increases when the information is stated in several languages and we want to be ca- pable of producing a summary in those languages, thus not restricting the summariser to a single lan- guage (multi-lingual summarisation). The gener- ation of multi-lingual summaries improves con- siderably the capabilities of TS systems, allowing users to be able to understand the essence of doc- uments in other languages by only reading their corresponding summaries. Therefore, the aim of this paper is to carry out a comparative analysis of several approaches for generating extractive1 multi-lingual summaries in four languages (English, French, German and Spanish). These approaches comprise the use of: i) language-independent techniques; ii) language- specific resources; and iii) machine translation re- sources applied to a mono-lingual summariser. In this way, we can study the advantages and lim- itations of each approach, as well as to deter- mine which is the most appropriate to adopt for this type of summaries. Although the language- specific resources are limited and perform differ- ently for …

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