Explorations in Automatic Book Summarization
By Rada Mihalcea, Hakan Ceylan. 2007
89 citations recorded by the source corpus.
Subfields: Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Natural Language Processing
- Mohit Bansal
- Caiming Xiong
- Dragomir R. Radev
- Yejin Choi
- Lu Wang
- Graham Neubig
- Mirella Lapata
- Nazneen Rajani
Citations in the corpus
- Recursively Summarizing Books with Human Feedback (2021, methodology): “Abstractive book summarization is a difficult task, where dataset collection is challenging (Mihalcea and Ceylan, 2007; Ladhak et al., 2020; Kry´sci´nski et al., 2021) and existing methods are typically either extractive (Radev et al., 2004; Mihalcea and Tarau, 2004; Bamman and Smith, 2013; Ladhak…”
- BookSum: A Collection of Datasets for Long-form Narrative Summarization (2021, background): “Mihalcea and Ceylan (2007) introduced the task of book summarization along with a set of resources and baselines.”
- Exploring Content Selection in Summarization of Novel Chapters (2020, methodology): “Relatively little work has been done in summarization of novels, but early work (Mihalcea and Ceylan, 2007) provided a dataset of novel/summary pairs drawn from CliffsNotes and GradeSaver and developed an unsupervised system based on Meade (Radev et al.”
- SummScreen: A Dataset for Abstractive Screenplay Summarization (2021, background): “There have been attempts in summarizing longform text (other than screenplays), such as books (Mihalcea and Ceylan, 2007), scientific articles (PubMed and arXiv; Cohan et al.”
- A new sentence similarity measure and sentence based extractive technique for automatic text summarization (2009, methodology): “After representing each sentence by a vector of features, the classification function can be trained in two different manners (Mihalcea & Ceylan, 2007).”
- Generating Character Descriptions for Automatic Summarization of Fiction (2019, methodology): “The most relevant dataset was created by Mihalcea and Ceylan (2007), consisting of 50 books, each with two manually created summaries.”
- Efficient Attentions for Long Document Summarization (2021, background): “Summarizing long inputs has been investigated in many domains, including books (Mihalcea and Ceylan, 2007), patents (Trappey et al.”