Graph-Based Methods for Multi-document Summarization: Exploring Relationship Maps, Complex Networks and Discourse Information

Ribaldo, Rafael; Akabane, Ademar Takeo; Rino, Lucia Helena Machado; Pardo, Thiago Alexandre Salgueiro

doi:10.1007/978-3-642-28885-2_30

Cited by 25 publications

(83 citation statements)

References 15 publications

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“…Once the network is built, sentence ranking is performed by using graph and complex network measures, as degree, clustering coefficient and shortest path, and the best ranked sentences are selected to compose the summary. Using some of the measures, such method was also adapted for MDS summarization for the Portuguese language [20,12], producing good results. Such system was named RCSumm.…”

Section: Text Summarizationmentioning

confidence: 99%

“…The first two methods adapted from [3] (Bushy Path and Depth-first Path) were already evaluated for MDS of texts written in Portuguese [12]. Using such methods for MDS, as we discuss later, implies in dealing with the multi-document phenomena, mainly with redundancy.…”

Section: Text Summarizationmentioning

confidence: 99%

“…The authors have proposed single document summarization methods that are referred by "relationship maps", since a text is represented as a graph (a "map") of interrelated text segments and different traversing techniques are used to select the segments to compose a summary. We have already adapted two of the methods (called "bushy" and "depth-first" paths) for multi-document summarization (as reported in [12]). Here, we adapt and explore the most sophisticated method, the "Segmented Bushy Path", which addresses the subtopic issues for producing better summaries.…”

Section: Figure 2 Summary Produced By Gistsumm Systemmentioning

confidence: 99%

“…It has been widely used in the area and produces good results. It was tested for Portuguese in [12]. To the best of our knowledge, GistSumm [7] was the first MDS system for Portuguese.…”

Section: Text Summarizationmentioning

confidence: 99%

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Exploring the subtopic-based relationship map strategy for multi-document summarization

Ribaldo

Cardoso²,

Pardo³

2016

RITA

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Neste artigo, foi adaptada e explorada uma estratégia de geração de sumários multidocumento com base na abordagem de mapas de relacionamento, a qual representa textos como grafos (mapas) de segmentos inter-relacionados e aplica técnicas de percurso em grafo para produzir os sumários. Em particular, utilizou-se o Caminho Denso-Segmentado, um método sofisticado que tenta representar em um sumário os principais subtópicos dos textos de origem, mantendo a informatividade do sumário. Além disso, também foram investigadas algumas técnicas de segmentação e agrupamento de subtópicos bem conhecidas, a fim de selecionar corretamente as informações mais relevantes para compor o sumário final. Mostra-se que este método de sumarização baseado em subtópicos supera outros métodos de sumarização multidocumento e atinge resultados do estado da arte, competindo com os métodos de sumarização profundos mais sofisticados da área. Explorando mapas de relacionamento com base em subtópicos para sumarização multidocumento Abstract: In this paper we adapt and explore a strategy for generating multidocument summaries based on the relationship map approach, which represent texts as graphs (maps of interrelated segments and apply traversing techniques for producing the summaries. In particular, we work on the Segmented Bushy Path, a sophisticated method which tries to represent in a summary the main subtopics from the source texts while keeping its informativeness. In addition, we also investigate some well-known subtopic segmentation and clustering techniques in order to correctly select the most relevant information to compose the final summary. We show that this subtopic-based summarization method outperforms other methods for multi-document summarization and achieves state of the art results, competing with the most sophisticated deep summarization methods in the area.

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Section: Text Summarizationmentioning

confidence: 99%

Section: Text Summarizationmentioning

confidence: 99%

Section: Figure 2 Summary Produced By Gistsumm Systemmentioning

confidence: 99%

“…It has been widely used in the area and produces good results. It was tested for Portuguese in [12]. To the best of our knowledge, GistSumm [7] was the first MDS system for Portuguese.…”

Section: Text Summarizationmentioning

confidence: 99%

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Exploring the subtopic-based relationship map strategy for multi-document summarization

Ribaldo

Cardoso²,

Pardo³

2016

RITA

Self Cite

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“…In [4], a hybrid graph-based method was presented annotating relationship maps with cross-document Structure Theory [5], and using network metrics [6]. It helped for Portuguese multi-document summarization.…”

Section: Introductionmentioning

confidence: 99%

Graph Ranking on Maximal Frequent Sequences for Single Extractive Text Summarization

Ledeneva

García-Hernández

Gelbukh

2014

Computational Linguistics and Intelligent Text Processing

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Abstract. We suggest a new method for the task of extractive text summarization using graph-based ranking algorithms. The main idea of this paper is to rank Maximal Frequent Sequences (MFS) in order to identify the most important information in a text. MFS are considered as nodes of a graph in term selection step, and then are ranked in term weighting step using a graphbased algorithm. We show that the proposed method produces results superior to the-state-of-the-art methods; in addition, the best sentences were found with this method. We prove that MFS are better than other terms. Moreover, we show that the longer is MFS, the better are the results. If the stop-words are excluded, we lose the sense of MFS, and the results are worse. Other important aspect of this method is that it does not require deep linguistic knowledge, nor domain or language specific annotated corpora, which makes it highly portable to other domains, genres, and languages.

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Automatic Mining of Discourse Connectives for Russian

Toldova

Kobozeva

Pisarevskaya

2018

Communications in Computer and Information Science

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Graph-Based Methods for Multi-document Summarization: Exploring Relationship Maps, Complex Networks and Discourse Information

Cited by 25 publications

References 15 publications

Exploring the subtopic-based relationship map strategy for multi-document summarization

Exploring the subtopic-based relationship map strategy for multi-document summarization

Graph Ranking on Maximal Frequent Sequences for Single Extractive Text Summarization

Automatic Mining of Discourse Connectives for Russian

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