PPT-Summarization I Presented By:

Author : pamella-moone | Published Date : 2020-04-05

Ameet Deshpande March 24 2020 TASK Text Summarization is the reduction of data to a minimal subset which represents the original data Two types of Summarization

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Ameet Deshpande March 24 2020 TASK Text Summarization is the reduction of data to a minimal subset which represents the original data Two types of Summarization techniques Extractive Summarization. video -Object driven Vs. Story driven. Presented By: Elad Osherov Jan 2013. Today’s talk. Motivation. Related Work. Object driven summarization. Story driven summarization. Results. Future Development. Luis . Herranz. Arribas. Supervisor: Dr. José M. Martínez Sánchez. Video Processing and Understanding Lab. Universidad . Aut. ónoma. de Madrid. Outline. Introduction. Integrated. . summarization. (Combined Method). 1. Tatsuro. . Oya. Extractive Summarization DA Recognition. . Locate . important sentences . in email and model . dialogue . acts . simultaneously. .. 2. Outline. Introduction. Date. : . 2014/08/11. Author . : . Lidan. . Shou. , . Zhenhua. Wang, . Ke. Chen, Gang Chen. Source. : . SIGIR’13. Advisor: . Jia. -ling . Koh. Speaker. : . Sz-Han,Wang. O. utline. Introduction. 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. Abigail See, Peter J. Liu, Christopher D. Manning. Presented by: Matan . Eyal. Agenda. Introduction. Word Embeddings. RNNs. Sequence-to-Sequence. Attention. Pointer Networks. Coverage Mechanism. Introduction . 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 Diversity driven Attention Model for Query-based Abstractive Summarization Preksha Nema *,  Mitesh Khapra *,  Anirban Laha* # ,   Balaraman Ravindran * * Indian Institute of Technology Madras, India 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. (Combined Method). 1. Tatsuro. . Oya. Extractive Summarization + DA Recognition. . Locate . important sentences . in email and model . dialogue . acts . simultaneously. .. 2. Outline. Introduction. Tal . Baumel. , Rafi Cohen, Michael Elhadad. Jan 2014. Generic Summarization. Generic Extractive Multi-doc Summarization:. Given a set of documents Di. Identify a set of sentences . Sj. . s.t.. |. Sj. 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:. DDX : . intertrigo,candidiasis. , tinea . cruris. , seborrheic dermatitis, psoriasis. DX : tinea . cruris. Adult female presented with dome shaped papule, yellowish in color, with central depression, not itchy for several weeks with similar lesions in nearby area..

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