PPT-Beyond Search: Statistical Topic Models for Text Analysis

ChengXiang Zhai Department of Computer Science University of Illinois at UrbanaChampaign httpwwwcsuiuceduhomesczhai 1 Search is a means to the end of finishing a task Decision Making. Rochelle Terman. Social Computing Working Group. Feb 27, 2015. https://github.com/rochelleterman/worlds-women. Lifecycle. Frame research question. Acquire text data. Preprocess. Analyze. Visualize + Interpret. 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. Lesson . 8.01. After completing this lesson, you will be able to say. :. I . can. recognize and write a statistical question. .. I . can. recognize that data can have variability as a result of the question. Machine Learning @ CU. Intro courses. CSCI 5622: Machine Learning. CSCI 5352: Network Analysis and Modeling. CSCI 7222: Probabilistic Models. Other courses. cs.colorado.edu/~mozer/Teaching/Machine_Learning_Courses. Class 1. Tony Cox. tcoxdenver@aol.com. . University of Colorado at Denver. January 17, 2017. Proposed agenda. Introduction: Views on statistical consulting. Learning objectives. Course administration, grading, policies. 2011/2012. M. de Gunst. Lecture. 7. Statistical Data Analysis. 2. Statistical Data Analysis: Introduction. Topics. Summarizing data. Exploring . distributions . Bootstrap . Robust methods. Nonparametric tests (continued). for Computer Experiments. Habilitation . à. . Diriger. des . Recherches. Olivier ROUSTANT. Ecole des Mines de St-Etienne. 8. th. November 2011. Outline. Foreword. Computer . Experiments. : . Industrial. HEADLINE. Body. text,. body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text, body text. THOMAS FUNKHOUSER, PATRICK MIN, MICHAEL KAZHDAN, JOYCE CHEN,. ALEX HALDERMAN, and DAVID DOBKIN. Princeton University. and. DAVID JACOBS. NEC Research Institute. ACM Transactions on Graphics, Vol. 22, No. 1, January 2003, Pages 83–105.. Topic. A topic is a subject within a text. It is typically one word, or a short phrase . Topics are what the text is “about” . For example…. The Avengers . is about “heroes” and “friendship” . Main Title Here. Topic 1. Topic 1 title goes here. Your text here. Your text here. Your text here. Your text here. Your text here. Your text here. Your text . here. Your text here. Your text here. Your text here. . SYFTET. Göteborgs universitet ska skapa en modern, lättanvänd och . effektiv webbmiljö med fokus på användarnas förväntningar.. 1. ETT UNIVERSITET – EN GEMENSAM WEBB. Innehåll som är intressant för de prioriterade målgrupperna samlas på ett ställe till exempel:. Text 2. Text 3. Text 4. Text 5. Text 6. Text 7. Text 8. Text 9. Text 10. Text 11. Text 12. Text 13. Text 14. Text 15. Text 16. Text 17. Erbauer: . Max Mustermann (Ort). Bauzeit: xx Wochen. Steine: ca. 10.000. Designing GNN for Text-rich Graphs. Yanbang Wang, Jul 27, 2020 at UIUC DMG. Collaborated work with Carl Yang, Pan Li and Prof. Jiawei Han. Text-rich Graphs. Usually come with two things:. Node attributes.