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Marujo, L., Ling, W., Ribeiro, R., Gershman, A., Carbonell, J., de Matos, D....Neto, J. P. (2016). Exploring events and distributed representations of text in multi-document summarization. Knowledge-Based Systems. 94, 33-42
L. Marujo et al., "Exploring events and distributed representations of text in multi-document summarization", in Knowledge-Based Systems, vol. 94, pp. 33-42, 2016
@article{marujo2016_1711677772911, author = "Marujo, L. and Ling, W. and Ribeiro, R. and Gershman, A. and Carbonell, J. and de Matos, D. and Neto, J. P.", title = "Exploring events and distributed representations of text in multi-document summarization", journal = "Knowledge-Based Systems", year = "2016", volume = "94", number = "", doi = "10.1016/j.knosys.2015.11.005", pages = "33-42", url = "http://www.sciencedirect.com/science/article/pii/S0950705115004323" }
TY - JOUR TI - Exploring events and distributed representations of text in multi-document summarization T2 - Knowledge-Based Systems VL - 94 AU - Marujo, L. AU - Ling, W. AU - Ribeiro, R. AU - Gershman, A. AU - Carbonell, J. AU - de Matos, D. AU - Neto, J. P. PY - 2016 SP - 33-42 SN - 0950-7051 DO - 10.1016/j.knosys.2015.11.005 UR - http://www.sciencedirect.com/science/article/pii/S0950705115004323 AB - In this article, we explore an event detection framework to improve multi-document summarization. Our approach is based on a two-stage single-document method that extracts a collection of key phrases, which are then used in a centrality-as-relevance passage retrieval model. We explore how to adapt this single-document method for multi-document summarization methods that are able to use event information. The event detection method is based on Fuzzy Fingerprint, which is a supervised method trained on documents with annotated event tags. To cope with the possible usage of different terms to describe the same event, we explore distributed representations of text in the form of word embeddings, which contributed to improve the summarization results. The proposed summarization methods are based on the hierarchical combination of single-document summaries. The automatic evaluation and human study performed show that these methods improve upon current state-of-the-art multi-document summarization systems on two mainstream evaluation datasets, DUC 2007 and TAC 2009. We show a relative improvement in ROUGE-1 scores of 16% for TAC 2009 and of 17% for DUC 2007. ER -