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Synopsis
Part I Background and Fundamentals .- 1.Automatic Text Summarization: Past, Present and Future. Horacio Saggion and Thierry Poibeau.- Information Extraction: Past, Present and Future. Jakub Piskorski and Roman Yangarber.- Part II Named Entity in a Multilingual Context.- Learning to Match Names Across Languages. Inderjeet Mani, Alex Yeh, and Sherri Condon.- Computational Methods for Name Normalization Using Hypocoristic Personal Name Variants. Patricia Driscoll.- Entity Linking: Finding Extracted Entities in a Knowledge Base. Delip Rao, Paul McNamee, and Mark Dredze.- A Study of the Effect of Document Representations in Clustering-based Cross-document Coreference Resolution. Horacio Saggion.- Part III Information Extraction.- Interactive Topic Graph Extraction and Exploration of Web Content. Günter Neumann and Sven Schmeier.- Predicting Relevance of Event Extraction for the End User. Silja Huttunen, Arto Vihavainen, Mian Du, and Roman Yangarber.- Open-domain Multi-Document Summarization via Information Extraction: Challenges and Prospects. Heng Ji, Benoit Favre, Wen-Pin Lin, Dan Gillick, Dilek Hakkani-Tur, and Ralph Grishman.- Part IV Multi-document Summarization.- Generating Update Summaries: Using an Unsupervized Clustering Algorithm to Cluster Sentences. Aurélien Bossard.- Multilingual Statistical News Summarization. Mijail Kabadjov, Josef Steinberger and Ralf Steinberger.- A Bottom-up Approach to Sentence Ordering for Multi-document Summarization. Danushka Bollegala, Naoaki Okazaki, and Mitsuru Ishizuka.- Improving Speech-to-Text Summarization by Using Additional Information Sources. Ricardo Ribeiro and David Martins de Matos.- Multi-Document Summarization Techniques for Generating Image Descriptions: A Comparative Analysis. Ahmet Aker, Laura Plaza, Elena Lloret, and Robert Gaizauskas.- Index.
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