Applying Lexical-Conceptual Knowledge for Multilingual Multi-document Summarization

摘要

We define Multilingual Multi-Document Summarization (MMDS) as the process of identifying the main information of a cluster with (at least) two texts, one in the user's language and one in a foreign language, and presenting it as a summary in the user's language. Although it is a relevant task due to the increasing amount of on-line information in different languages, there are only baselines for (Brazilian) Portuguese, which apply machine-translation to obtain a monolingual input and superficial features for sentence extraction. We report our investigation on the application of conceptual frequency measure to build a summary in Portuguese from a bilingual cluster (Portuguese and English). The methods tackle two additional challenges: using Princeton WordNet for nouns annotation and applying MT to translate selected sentences in English to Portuguese. The experiments were performed using a corpus of 20 clusters, and show that lexical-conceptual knowledge improves the linguistic quality and informativeness of extracts.