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By Thierry Poibeau, Horacio Saggion, Jakub Piskorski, Roman Yangarber

Information extraction (IE) and textual content summarization (TS) are robust applied sciences for locating correct items of knowledge in textual content and proposing them to the person in condensed shape. the continued details explosion makes IE and TS severe for winning functioning in the details society.

These applied sciences face specific demanding situations as a result inherent multi-source nature of the knowledge explosion. The applied sciences needs to now deal with no longer remoted texts or person narratives, yet fairly large-scale repositories and streams---in basic, in a number of languages---containing a multiplicity of views, evaluations, or commentaries on specific themes, entities or occasions. there's therefore a necessity to conform current innovations and enhance new ones to house those challenges.

This quantity encompasses a choice of papers that current quite a few methodologies for content material id and extraction, in addition to for content material fusion and regeneration. The chapters disguise quite a few elements of the demanding situations, looking on the character of the data sought---names vs. events,--- and the character of the sources---news streams vs. photograph captions vs. medical examine papers, and so on. This quantity goals to provide a large and consultant pattern of reports from this very lively examine field.

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Lang. Engin. 8, 43–68 (2002). 1017/S1351324901002741. 973864 38. : Advances in Automatic Text Summarization. MIT, Cambridge (1999) 39. : Rhetorical structure theory: towards a functional theory of text organization. Text 8(3), 243–281 (1988) 40. : From discourse structures to text summaries. In: The Proceedings of the ACL’97/EACL’97 Workshop on Intelligent Scalable Text Summarization, Madrid, pp. 82–88 (1997) 41. : Architectural elements of language engineering robustness. J. Nat. Lang. Engin. Spec.

SCISOR [28] was an integrated system incorporating IE for the extraction of facts related to corporate mergers and acquisitions from online news. html. 34 J. Piskorski and R. Yangarber the security domain are described, for example, in [34, 35]. All the above systems and other early IE systems were developed using the Knowledge Engineering (KE) approach [4], where the creation of linguistic knowledge in the form of rules, or patterns, for detecting and extracting the target information from text is performed by human experts, through inspection of the test corpus and intuition.

Association for Computational Linguistics, Stroudsburg (2009) 7. : The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: Research and Development in Information Retrieval, pp. 335–336. The Association for Computing Machinery, New York (1998) 8. : Unsupervised learning of narrative schemas and their participants. In: ACL/AFNLP, Singapore, pp. 602–610. Association for Computational Linguistics, Stroudsburg (2009) 18 H. Saggion and T. Poibeau 9. : Sentence compression as tree transduction.

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