Salience-based Content Characterisafion of Text Documents
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Summary
This paper describes a novel approach to content characterisation of text documents that is domain- and genre-independent, by virtue of not requiring an in-depth analysis of the full meaning of the source document, and remains closer to the core meaning.
- Type
- article
- Published
- 1997-01-01
- Cited by
- 135
- References
- 48
- OpenAlex
- https://openalex.org/W2087556494
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:1592006
Keywords
Computer science, Salience (neuroscience), Natural language processing, Coherence (philosophical gambling strategy), Meaning (existential)
References
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- Automated Text Summarization in SUMMARIST
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- Automatic documents summarization using ontology based methodologies
- Using Cohesion and Coherence Models for Text Summarization
- Summarizing Similarities and Differences Among Related Documents
- Pruning UNL texts for Summarizing Purposes
- Summarization of Documents That Include Graphics
- Automatic Creation of Opinion-Based Summary Representations
- The generation of compound nominals to represent the essence of text : the COMMIX system
- Automatically Characterizing Salience Using Readers' Feedback
- Evaluation of Text Summarization in a Cross-lingual Information Retrieval Framework
- Generating Natural Language Summaries from Multiple On-Line Sources
- SemanticRank: Ranking Keywords and Sentences Using Semantic Graphs
- Dynamic visual metaphors for news story abstractions
- Literature Review of Automatic Single Document Text Summarization Using NLP
- Dynamic presentation of document content for rapid on-line skimming
- Automatic Summarization of Conversational Multi-Party Speech
- Using Lexical Chains for Text Summarization
- Learning Document Similarity Using Natural Language Processing
- A Flexible Multitask Summarizer for Documents from Different Media, Domain and Language