PPT-Top-k Graph Summarization on Hierarchical DAGs
Author : jaena | Published Date : 2024-03-13
Xuliang Zhu Xin Huang Byron Choi Jianliang Xu Hong Kong Baptist University Hong Kong China Outlines Motivations Related Work KDAGProblem Algorithms Experiments
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Top-k Graph Summarization on Hierarchical DAGs: Transcript
Xuliang Zhu Xin Huang Byron Choi Jianliang Xu Hong Kong Baptist University Hong Kong China Outlines Motivations Related Work KDAGProblem Algorithms Experiments Conclusions Motivations. E. asy-to-. U. nderstand English . Sum. maries for . Non-Native Readers. Authors : . Xiaojun. Wan (. 副研究員. ). http://www.icst.pku.edu.cn/intro/content_409.htm. Huiying. Li . Jianguo. Xiao (. . Inference. . of. . Hierarchies. . in. . Networks. BY. . Yu. . Shuzhi. 27,. . Mar. . 2014. Content. 1.. . Background. 2. .. . Hierarchical. . Structures. 3. .. . Random. . Graph Model of Hierarchical Organization. Lei Shi, Sibai Sun, . Yuan Xuan. , Yue Su, . Hanghang . Tong, Shuai Ma, Yang . Chen. Influence Graph. Initial. Tweet. Re-tweeting Graph. Re-tweets. Citing papers. Source. Paper. Paper Citation Graph. 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. Sushmita Roy. sroy@biostat.wisc.edu. Computational Network Biology. Biostatistics & Medical Informatics 826. Computer Sciences 838. https://compnetbiocourse.discovery.wisc.edu. Nov 3. rd. 2016. RECAP. (Combined Method). 1. Tatsuro. . Oya. Extractive Summarization DA Recognition. . Locate . important sentences . in email and model . dialogue . acts . simultaneously. .. 2. Outline. 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. 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 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. 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. Graph Traversals. Spring 2015. Yanling He. Graphs. A Graph G = (V, E). Represents relationships among items. Can be directed or undirected. Complexity is O(|E|+|V|) is O(|V|^2). Graph Data Structure. Big Graphs. Arijit Khan. Nanyang Technological University, Singapore. Sourav S. Bhowmick. Nanyang Technological University, Singapore. Francesco Bonchi. ISI Foundation, Italy. Google: > 1 trillion indexed pages. 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 .
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