PPT-Topic 2

Perception Outline of course Perception Theories of perceptual organisation Gregorys top downindirect theory of perception Gibsons bottom updirect theory of perception Development of perception . 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 . David Kauchak. cs160. Fall . 2009. Administrative. Hw5/paper review. what . would be useful for the . authors. technical. , refers to not only the results, but the rest of the . paper. give . as many specific examples as . 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. Siddharth Gupta. 1. , Casey Hanson. 2. , Carl A Gunter. 3. , Mario Frank. 4. , David Liebovitz. 4. , Bradley . Malin. 6. 1,2,3,4. Department of Computer Science, . 3,5. Department of Medicine, . 6. Department of Biomedical Informatics. Mini-Lesson. What is the . thesis statement. ?. What is the formula?. Thesis Statement Examples. Topic 1: Bradbury uses imagery to reveal a society that uses government censorship as a way to control its people, and warns that this could be any society’s fate if people refuse to speak up.. 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. Liangjie Hong. and Brian D. Davison. Computer Science and Engineering. Lehigh University. Bethlehem, PA USA. SOMA 2010 . Why. . we care about text modeling in Twitter ?. SOMA 2010 . Why. . we care about text modeling in Twitter ?. 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 . 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. 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 . . ..