PPT-TOPIC

ULTRASOUND EVALUATION OF SUPERFICIAL LESIONS WITH THE USE OF HIGH RESOLUTION TRANSDUCER AUTHORS amp CO AUTHORS Dr Ananda Kumar B MBBS Dr PM Venkata Sai MBBS DMRD DNB . Duane Theobald. dtheobal@westga.edu . Topic Sentences???. What do you already know about topic sentences? . Topic Sentences: The Basics. A topic sentence serves to organize an entire paragraph, and you need to make sure to include one in most of your major paragraphs.. 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.. 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. 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. Chenghua. Lin . & . Yulan. He. CIKM09. Main Idea. This . paper . proposes . a novel probabilistic modeling framework based on . Latent . Dirichlet. Allocation (LDA), called joint sentiment/. 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. 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. Information Ordering. Ling 573. Systems and Applications. May 5, 2016. Roadmap . Entity-based cohesion model:. Model entity . based transitions. Topic-based cohesion model:. Models sequence of topic transitions. 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. 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.