Generic technologies for single- and multi-document summarization

Moens, Marie‐Francine; Angheluta, Roxana; Dumortier, Jos

doi:10.1016/j.ipm.2003.12.006

Cited by 18 publications

(7 citation statements)

References 26 publications

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“…We see a current research interest in moving beyond extraction towards compressing and generating suitable summary sentences (e.g., [3,8,21,31]). However, research into summarisation of Dutch texts is limited (e.g., [24]: summarisation of court decisions; [32,33]: summarisation of speech; [23]: summarisation of magazine articles). Studies that integrate into the summarisation certain pragmatic communication roles of the content are new.…”

Section: Problem Definitionmentioning

confidence: 99%

Question Answering of InformativeWeb Pages: How Summarisation Technology Helps

Belder

Kok

Noord

et al. 2012

Essential Speech and Language Technology for Dutch

Self Cite

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Section: Problem Definitionmentioning

confidence: 99%

Question Answering of InformativeWeb Pages: How Summarisation Technology Helps

Belder

Kok

Noord

et al. 2012

Essential Speech and Language Technology for Dutch

Self Cite

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“…The automatic execution of some of the tasks in knowledge flows can be supported by individual systems such as expert locater system (McDonald and Ackerman 1998) summarization systems (Moens et al 2005) and filtering systems. However, each of these systems has to be individually invoked by the user to accomplish the knowledge goal.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the intelligent services enhanced knowledge flow, the use of a filtering service (Sarnikar et al 2004) denoted by ''F'' prevents the distribution of the message to non-relevant experts. The use of summarization and aggregation services (Moens et al 2005), denoted by ''S'' and ''A'', prevents overloading the user.…”

Section: An Example Of Knowledge Workflow Automationmentioning

confidence: 99%

Pattern-based knowledge workflow automation: concepts and issues

Sarnikar

Zhao

2007

Inf Syst E-Bus Manage

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As the result of business process automation, more and more knowledge is codified and stored in knowledge repositories and scattered in employees' computers across functionally and geographically separated business units. While several alternative mechanisms such as chat rooms, search engines, recommender systems exist to retrieve and access knowledge, satisfying a knowledge requirement often involves the coordination of multiple tasks and the use of several technologies. However, there is no existing technology for orchestrating various collaboration, communication and information retrieval components to satisfy the knowledge needs in corporations. In order to address this gap, we propose the approach of pattern-based knowledge workflow that can enable the automation of knowledge flows across an organization. In this paper, we present an overview of the patternbased knowledge workflow approach and propose extensions to the conventional workflow paradigm. We demonstrate the feasibility of implementing knowledge workflows by means of a Business Process Execution Language (BPEL) specification for executing knowledge workflows in a business setting. We then discuss the engineering challenges and research issues that need to be addressed to further develop this approach.

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“…Pattern recognition is done with grammars in some of them; grammars are appropriate because patterns in legal documents have a high level of regularity. Outside the legal domain, references (mainly scientific references) have also been the target of several efforts [7,6,4,8].…”

Section: Related Workmentioning

confidence: 99%

Reference Extraction and Resolution for Legal Texts

González

Fuente

Vicente

2005

Lecture Notes in Computer Science

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An application to the legal domain of information extraction is presented. Its goal is to automate the extraction of references from legal documents, their resolution, and the storage of their information in order to facilitate an automatic treatment of these information items by services offered in digital libraries. References are extracted matching the texts in the collection against sets of patterns, using grammars.

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Generic technologies for single- and multi-document summarization

Cited by 18 publications

References 26 publications

Question Answering of InformativeWeb Pages: How Summarisation Technology Helps

Question Answering of InformativeWeb Pages: How Summarisation Technology Helps

Pattern-based knowledge workflow automation: concepts and issues

Reference Extraction and Resolution for Legal Texts

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