scholarly journals Automatic Summarization of Student Course Feedback

2016 ◽  
Author(s):  
Wencan Luo ◽  
Fei Liu ◽  
Zitao Liu ◽  
Diane Litman
Keyword(s):  
Automatic Summarization

scholarly journals Automatic summarization of search engine hit lists

2000 ◽  
Author(s):  
Dragomir R. Radev ◽  
Weiguo Fan
Keyword(s):  
Search Engine ◽  
Automatic Summarization

Automatic Summarization

2012 ◽  
Vol 5 (3) ◽  
pp. 235-422 ◽  
Author(s):  
Martha Larson
Keyword(s):  
Automatic Summarization

scholarly journals An investigation of linguistic problems in automatic multi-document summaries / Uma investigação de problemas linguísticos em sumários automáticos multidocumento

2021 ◽  
Vol 29 (2) ◽  
pp. 859
Author(s):  
Márcio De Souza Dias ◽  
Ariani Di Felippo ◽  
Amanda Pontes Rassi ◽  
Paula Cristina Figueira Cardoso ◽  
Fernando Antônio Asevedo Nóbrega ◽  
...  
Keyword(s):  
State Of The Art ◽  
Brazilian Portuguese ◽  
Source Material ◽  
Corpus Annotation ◽  
Automatic Summarization ◽  
Document Summarization ◽  
Art Methods ◽  
Characterization Studies ◽  
Linguistic Problem ◽  
Support Research

Abstract: Automatic summaries commonly present diverse linguistic problems that affect textual quality and thus their understanding by users. Few studies have tried to characterize such problems and their relation with the performance of the summarization systems. In this paper, we investigated the problems in multi-document extracts (i.e., summaries produced by concatenating several sentences taken exactly as they appear in the source texts) generated by systems for Brazilian Portuguese that have different approaches (i.e., superficial and deep) and performances (i.e., baseline and state-of-the art methods). For that, we first reviewed the main characterization studies, resulting in a typology of linguistic problems more suitable for multi-document summarization. Then, we manually annotated a corpus of automatic multi-document extracts in Portuguese based on the typology, which showed that some of linguistic problems are significantly more recurrent than others. Thus, this corpus annotation may support research on linguistic problems detection and correction for summary improvement, allowing the production of automatic summaries that are not only informative (i.e., they convey the content of the source material), but also linguistically well structured.Keywords: automatic summarization; multi-document summary; linguistic problem; corpus annotation.Resumo: Sumários automáticos geralmente apresentam vários problemas linguísticos que afetam a sua qualidade textual e, consequentemente, sua compreensão pelos usuários. Alguns trabalhos caracterizam tais problemas e os relacionam ao desempenho dos sistemas de sumarização. Neste artigo, investigaram-se os problemas em extratos (isto é, sumários produzidos pela concatenação de sentenças extraídas na íntegra dos textos-fonte) multidocumento em Português do Brasil gerados por sistemas que apresentam diferentes abordagens (isto é, superficial e profunda) e desempenho (isto é, métodos baseline e do estado-da-arte). Para tanto, as principais caracterizações dos problemas linguísticos em sumários automáticos foram investigadas, resultando em uma tipologia mais adequada à sumarização multidocumento. Em seguida, anotou-se manualmente um corpus de extratos com base na tipologia, evidenciando que alguns tipos de problemas são significativamente mais recorrentes que outros. Assim, essa anotação gera subsídios para as tarefas automáticas de detecção e correção de problemas linguísticos com vistas à produção de sumários automáticos não só mais informativos (isto é, que cobrem o conteúdo do material de origem), como também linguisticamente bem-estruturados.Palavras-chave: sumarização automática; sumário multidocumento; problema linguístico; anotação de corpus.

scholarly journals Automatic Summarization in Chinese Product Reviews

2017 ◽  
Vol 15 (1) ◽  
pp. 373
Author(s):  
Li Zhen Liu ◽  
Wan Di Du ◽  
Han Shi Wang ◽  
Wei Song
Keyword(s):  
Product Reviews ◽  
Automatic Summarization

scholarly journals Automatic Summarization of Open-Domain Multiparty Dialogues in Diverse Genres

2002 ◽  
Vol 28 (4) ◽  
pp. 447-485 ◽  
Author(s):  
Klaus Zechner
Keyword(s):  
Average Duration ◽  
Research Area ◽  
Global Evaluation ◽  
Ranking Algorithm ◽  
Open Domain ◽  
Automatic Summarization ◽  
Term Weighting ◽  
Written Text ◽  
Summarization System ◽  
New Research

Automatic summarization of open-domain spoken dialogues is a relatively new research area. This article introduces the task and the challenges involved and motivates and presents an approach for obtaining automatic-extract summaries for human transcripts of multiparty dialogues of four different genres, without any restriction on domain. We address the following issues, which are intrinsic to spoken-dialogue summarization and typically can be ignored when summarizing written text such as news wire data: (1) detection and removal of speech disfluencies; (2) detection and insertion of sentence boundaries; and (3) detection and linking of cross-speaker information units (question-answer pairs). A system evaluation is performed using a corpus of 23 dialogue excerpts with an average duration of about 10 minutes, comprising 80 topical segments and about 47,000 words total. The corpus was manually annotated for relevant text spans by six human annotators. The global evaluation shows that for the two more informal genres, our summarization system using dialogue-specific components significantly outperforms two baselines: (1) a maximum-marginal-relevance ranking algorithm using TF*IDF term weighting, and (2) a LEAD baseline that extracts the first n words from a text.

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