4 documents found, page 1 of 1
Event-based summarization using a centrality-as-relevance model
Marujo, L.; Ribeiro, R.; Gershman, A.; de Matos, D. M.; Neto, J. P.; Carbonell, J.Event detection is a fundamental information extraction task, which has been explored largely in the context of question answering, topic detection and tracking, knowledge base population, news recommendation, and automatic summarization. In this article, we explore an event detection framework to improve a key phrase-guided centrality-based summarization model. Event detection is based on the fuzzy fingerprint...
Exploring events and distributed representations of text in multi-document summ...
Marujo, L.; Ling, W.; Ribeiro, R.; Gershman, A.; Carbonell, J.; de Matos, D.; Neto, J. P.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 ev...
Summarization of films and documentaries based on subtitles and scripts
Aparício, M.; Figueiredo, P.; Raposo, F.; de Matos, D.; Ribeiro, R.; Marujo, L.We assess the performance of generic text summarization algorithms applied to films and documentaries, using extracts from news articles produced by reference models of extractive summarization. We use three datasets: (i) news articles, (ii) film scripts and subtitles, and (iii) documentary subtitles. Standard ROUGE metrics are used for comparing generated summaries against news abstracts, plot summaries, and s...
Key phrase extraction of lightly filtered broadcast news
Marujo, L.; Ribeiro, R.; Matos, D. M. de.; Neto, J. P.; Gershman, A.; Carbonell, J.This paper explores the impact of light filtering on automatic key phrase extraction (AKE) applied to Broadcast News (BN). Key phrases are words and expressions that best characterize the content of a document. Key phrases are often used to index the document or as features in further processing. This makes improvements in AKE accuracy particularly important. We hypothesized that filtering out marginally releva...