PPT-Concept based Multi-Document Text Summarization

By asef poormasoomi Supervisor Dr Kahani autumn 2010 Ferdowsi University of Mashad Introduction summary brief but accurate representation of the contents of a document. Content. Bouts . Sayasenh. (Literacy Consultant, Albury) & Sharon . Tooney. (Assistant Principal, Albury). Why a Concept Based Approach?. Quality programming. “When translating NSW syllabuses into specific classroom programs, lessons and learning activities, the first thing teachers will need to do is select and . A. KARTELJ and V. FILIPOVIC. School of Mathematics, University of Belgrade, Serbia. and. V. MILUTINOVIC. School of Electrical Engineering, University of Belgrade, Serbia. Agenda. Problem overview. Classification of the existing solutions. Jie Tang. *. , Limin Yao. #. , and Dewei Chen. *. *. Dept. of Computer Science and Technology. Tsinghua University. #. Dept. of Computer Science, University of Massachusetts Amherst. April, 2009. ?. What are the major topics in the returned docs?. Overview. Ling573. Systems & Applications. March 31. , 2016. Roadmap. Dimensions . of the problem. Architecture . of a Summarization system. Summarization and resources. Evaluation. Logistics Check-. Reviews & Speech. Ling 573. Systems and Applications. May . 26, 2016. Roadmap. Abstractive summarization example. Using Abstract Meaning Representation. Review . summarization:. Basic approach. Learning what users want. Kathleen McKeown. Department of Computer Science. Columbia University. What is Summarization?. Data as input (database, software trace, expert system), text summary as output. Text as input (one or more articles), paragraph summary as output. and Organization for User-content Interaction. References. : 1. “Spoken Document Understanding and Organization”, IEEE Signal . Processing Magazine, Sept. 2005, Special Issue on Speech Technology. Kathleen McKeown. Department of Computer Science. Columbia University. What is Summarization?. Data as input (database, software trace, expert system), text summary as output. Text as input (one or more articles), paragraph summary as output. Access Pipeline Protests (NoDAPL). CS 5984/4984 Big Data Text Summarization Report. . Xiaoyu Chen*, Haitao Wang, Maanav Mehrotra, Naman Chhikara, Di Sun. {xiaoyuch, wanght, maanav, namanchhikara, sdi1995} @vt.edu. Document Summarization Abhirut Gupta Mandar Joshi Piyush Dungarwal Motivation The advent of WWW has created a large reservoir of data A short summary, which conveys the essence of the document, helps in finding relevant information quickly and Organization for User-content Interaction. References. : 1. “Spoken Document Understanding and Organization”, IEEE Signal . Processing Magazine, Sept. 2005, Special Issue on Speech Technology. Kathleen McKeown. Department of Computer Science. Columbia University. Today. HW3 assigned. Summarization (switch in order of topics). WEKA tutorial (for HW3). Midterms back. What is Summarization?. Data as input (database, software trace, expert system), text summary as output. Reddit. Posts. with Multi-level Memory Networks. . [. NAACL . 2019]. Group Presentation. WANG, Yue. 04/15/2019. Outline. Background. Dataset. Method. Experiment. Conclusion. 2. /16. Background. Challenge:. Authors: . Kexiang. Wang, . Zhifang. Sui, et al.. Organization: Peking University. Speaker: . Kexiang. Wang. E-mail: wkx@pku.edu.cn. Outline. Overview of Our Paper. Aim. We propose the adjustable affinity-preserving random walk method for generic and query-focused multi-document summarization to enforce the .