论文信息 - Multidocument Summarization via Information Extraction - 字舞流文

Multidocument Summarization via Information Extraction

We present and evaluate the initial version of RIPTIDES, a system that combines information extraction, extraction-based summarization, and natural language generation to support user-directed multidocument summarization.

Claire Cardie | David R. Pierce | Kiri Wagstaff | Vincent Ng | Michael White | Tanya Korelsky | Tanya Korelsky | Claire Cardie | K. Wagstaff | Vincent Ng | D. Pierce | Michael White

[1] Claire Cardie,et al. Empirical Methods in Information Extraction , 1997, AI Mag..

[2] Eugene Charniak,et al. A Maximum-Entropy-Inspired Parser , 2000, ANLP.

[3] Regina Barzilay,et al. Sentence Ordering in Multidocument Summarization , 2001, HLT.

[4] Raymond J. Mooney,et al. Active Learning for Natural Language Parsing and Information Extraction , 1999, ICML.

[5] Michael White,et al. EXEMPLARS: A Practical, Extensible Framework For Dynamic Text Generation , 1998, INLG.

[6] Ellen Riloff,et al. Automatically Generating Extraction Patterns from Untagged Text , 1996, AAAI/IAAI, Vol. 2.

[7] Michael White,et al. Polishing : Surface-Oriented Smoothing of Generated Text via Markup-Based Revision Rules , 2001 .

[8] Christiane Fellbaum,et al. Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[9] Jaime Carbonell,et al. Multi-Document Summarization By Sentence Extraction , 2000 .

[10] Dragomir R. Radev,et al. Generating Natural Language Summaries from Multiple On-Line Sources , 1998, CL.

[11] Beatrice Santorini,et al. Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.

[12] Ellen Riloff,et al. Learning Dictionaries for Information Extraction by Multi-Level Bootstrapping , 1999, AAAI/IAAI.