PPT-Topic 12

Author : trish-goza | Published Date : 2016-09-07

Graphs 1 Graphs Definition Two types Undirected Directed ExamplesApplications Transportation Networks Source pagescswiscedu Shortest path Vacuum World from AI Source

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Topic 12: Transcript


Graphs 1 Graphs Definition Two types Undirected Directed ExamplesApplications Transportation Networks Source pagescswiscedu Shortest path Vacuum World from AI Source centurion2com. The speci c topic you select may arise from a number of different triggers If you are a nursing student your interest in a topic may result from a lecture or module on a medical condition that was covered in your undergraduate classes or a medical p TOPIC SENTENCE. A . topic sentence tells the reader what the paragraph is all about.. TOPIC AND MAIN POINT. Every good topic sentence has two parts:. 1. Topic . 2. Main . Point. TOPIC. A topic is WHO the paragraph or story is about.. Paul N. Bennett, Microsoft Research. Joint with. Ece Kamar, Microsoft Research. Gabriella Kazai, Microsoft Research Cambridge. Motivation for Consensus Task. Recover actual . relevance of . a topic-document . Authors: Rosen-. Zvi. , Griffiths, . Steyvers. , Smyth . Venue: the 20th Conference on Uncertainty in Artificial Intelligence. Year: 2004. Presenter: Peter Wu. Date: Apr 7, 2015. Title: The Author-Topic Model for Authors and Documents. Language Model Adaptation. Ekapol. . Chuangsuwanich. 1. , . Shinji . Watanabe. 2. ,. Takaaki. Hori. 2. , . Tomoharu. . Iwata. 2. , . James . Glass. 1. 報告者:郝柏翰. 2013/03/05. ICASSP 2012. 0. Pre-industrial economies in transition. Topics:. Advanced Organic Economies . A characterisation of pre-industrial economies . Demographic forces and economic development. Causes and effects of population change in pre-industrial economies. Source: “Topic models”, David . Blei. , MLSS ‘09. Topic modeling - Motivation. Discover topics from a corpus . Model connections between topics . Model the evolution of topics over time . Image annotation. part 1. Andrea Tagarelli. Univ. of Calabria, Italy. Statistical topic modeling. . (1/3). Key assumption: . text . data represented as a mixture . of . topics. , i.e., probability distributions . over . 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?. Padhraic Smyth. Department of Computer Science. University of California, Irvine . . Progress Report. New deadline. In class, Thursday February 18. th. (not Tuesday). Outline. 3 to 5 pages maximum. in an HDP-Based Rating Regression Model for Online Reviews. Zheng Chen. 1. , Yong Zhang. 1,. 2. , Yue Shang. 1. , Xiaohua Hu. 1. 1. Drexel University, USA. 2. China Central Normal University, China. Paul N. Bennett, Microsoft Research. Joint with. Ece Kamar, Microsoft Research. Gabriella Kazai, Microsoft Research Cambridge. Motivation for Consensus Task. Recover actual . relevance of . a topic-document . Illustrations, descriptions or procedures. (with prompting). K. Compare & Contrast. The most important points presented by two texts on the same topic. 2. nd. . Integrate. Information from two texts on the same topic in order to write or speak about the subject knowledgably. Choosing a Good Topic. What Happens After Brainstorming Topics?. Strategies for Brainstorming an EDD Topic. Brainstorming Review. What Do You Know?. What Do You Love?. Don’t You Hate It When . . ..

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