A system for summary-document similarity in notary domain

Chai, Duck Jin; Jin, Long; Hwang, Baik; Ryu, Keun Ho

doi:10.1109/dexa.2007.77

Cited by 6 publications

(2 citation statements)

References 3 publications

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“…Although most work in TS has traditionally focused on newswire (Gotti et al 2007;Nenkova et al 2005;Nenkova 2005), scientific documents (Jaoua and Hamadou 2003;Teufel and Moens 2002), or even legal documents (Saravanan et al 2006;Cesarano et al 2007), these are not the unique scenarios in which TS approaches have been tested on. Next, several new scenarios in which TS has been also applied are described.…”

Section: New Scenarios For Text Summarisationmentioning

confidence: 98%

Text summarisation in progress: a literature review

2011

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This paper contains a large literature review in the research field of Text Summarisation (TS) based on Human Language Technologies (HLT). TS helps users manage the vast amount of information available, by condensing documents' content and extracting the most relevant facts or topics included in them. The rapid development of emerging technologies poses new challenges to this research field, which still need to be solved. Therefore, it is essential to analyse its progress over the years, and provide an overview of the past, present and future directions, highlighting the main advances achieved and outlining remaining limitations. With this purpose, several important aspects are addressed within the scope of this survey. On the one hand, the paper aims at giving a general perspective on the state-ofthe-art, describing the main concepts, as well as different summarisation approaches, and relevant international forums. Furthermore, it is important to stress upon the fact that the birth of new requirements and scenarios has led to new types of summaries with specific purposes (e.g. sentiment-based summaries), and novel domains within which TS has proven to be also suitable for (e.g. blogs). In addition, TS is successfully combined with a number of intelligent systems based on HLT (e.g. information retrieval, question answering, and text classification). On the other hand, a deep study of the evaluation of summaries is also conducted in this paper, where the existing methodologies and systems are explained, as well as new research that has emerged concerning the automatic evaluation of summaries' quality. Finally, some thoughts about TS in general and its future will encourage the reader to think of novel approaches, applications and lines to conduct research in the next years. The analysis of these issues allows the reader to have a wide and useful background on the main important aspects of this research field.

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Section: New Scenarios For Text Summarisationmentioning

confidence: 98%

Text summarisation in progress: a literature review

2011

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“…Another issue that is changing in the TS field is the domain of the documents for generating the summaries. Traditionally, newswire and scientific articles have been the most common domains to perform TS on (Hsin-Hsi and Chuan-Jie, 2000), (McKeown and Radev, 1999), (Teufel and Moens, 2002), but currently, a wide range of novel domains has been exploited as well, including legal domain (Cesarano et al, 2007), short stories (Kazantseva, 2006), books (Mihalcea and Ceylan, 2007), or image captioning (Plaza et al, 2010). …”

Section: Text Summarizationmentioning

confidence: 99%

Towards a unified framework for opinion retrieval, mining and summarization

et al. 2012

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The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained shows the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.

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A Gradual Combination of Features for Building Automatic Summarisation Systems

Lloret

Palomar

2009

Text, Speech and Dialogue

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A system for summary-document similarity in notary domain

Cited by 6 publications

References 3 publications

Text summarisation in progress: a literature review

Text summarisation in progress: a literature review

Towards a unified framework for opinion retrieval, mining and summarization

A Gradual Combination of Features for Building Automatic Summarisation Systems

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