MUSEEC: A Multilingual Text Summarization Tool
The MUSEEC (MUltilingual SEntence Extraction and Compression) summarization tool implements several extractive summarization techniques at the level of complete and compressed sentences that can be applied, with some minor adaptations, to documents in multiple languages. The current version of MUSEEC provides the following summarization methods: (1) MUSE a supervised summarizer, based on a genetic algorithm (GA) that ranks document sentences and extracts top ranking sentences into a summary, (2) POLY an unsupervised summarizer, based on linear programming (LP) that selects the best extract of document sentences, and (3) WECOM an unsupervised extension of POLY that compiles a document summary from compressed sentences. In this paper, we provide an overview of MUSEEC methods and its architecture in general.
ACL