Automatic generation of natural language summaries
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Summary
This thesis presents a new competitive sentence extraction method that assigns relevance scores to the sentences of the texts to be summarized, and proposes two novel sentence compression methods, which rewrite a source sentence in a shorter form, retaining the most important information.
- Type
- dissertation
- Published
- 2012-01-01
- Cited by
- 2
- References
- 135
- Access
- Open access
- OpenAlex
- https://openalex.org/W4867410
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:17855268
Keywords
Grammaticality, Automatic summarization, Computer science, Natural language processing, Sentence
References
- Hitting the Right Paraphrases in Good Time
- Text compaction for display on very small screens
- CLASSY and TAC 2008 Metrics
- Sentence Trimming and Selection: Mixing and Matching
- Microsoft Research at DUC2006: Task-Focused Summarization with Sentence Simplification and Lexical Expansion
- Multi-Document Summarization via the Minimum Dominating Set
- Re-evaluating the Role of Bleu in Machine Translation Research
- Foundations of Statistical Natural Language Processing
- Discriminative Sentence Compression with Soft Syntactic Evidence
- Multiple alternative sentence compressions as a tool for automatic summarization tasks
- Generating Typed Dependency Parses from Phrase Structure Parses
- Automated Summarization Evaluation with Basic Elements.
- Learning to classify text using support vector machines - methods, theory and algorithms
- Computing Locally Coherent Discourses
- Opinion Summarization with Integer Linear Programming Formulation for Sentence Extraction and Ordering
- Large Margin Synchronous Generation and its Application to Sentence Compression
- SRILM - an extensible language modeling toolkit
- Generating and Validating Abstracts of Meeting Conversations: a User Study
- Sentence Reduction for Automatic Text Summarization
- The use of domain-specific concepts in biomedical text summarization
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