PPT-An Analysis of Statistical Models and Features for Reading Difficulty Prediction

An Analysis of Statistical Models and Features for Reading Difficulty Prediction Michael Heilman Kevyn CollinsThompson Maxine Eskenazi Language Technologies Institute Carnegie Mellon University 1 The Goal To predict the readability of a page of text. brPage 1br DIFFICULTY LEVEL DIFFICULTY LEVEL DIFFICULTY LEVEL DIFFICULTY LEVEL DIFFICULTY LEVEL DIFFICULTY LEVEL DIFFICULTY LEVEL DIFFICULTY LEVEL DIFFICULTY LEVEL DIFFICULTY LEVEL Christopher . Ré. BigLearn. Collaborators listed throughout. Big data is the future. . Big . data is . great . for . vendors and consulting $$$, but is ‘Big’ the heart of the problem?. How big is `big’?. Saehoon Kim. §. , . Yuxiong He. *. ,. . Seung-won Hwang. §. , . Sameh Elnikety. *. , . Seungjin Choi. §. §. *. Web Search Engine . Requirement. 2. Queries. High quality + Low latency. This talk focuses on how to achieve low latency without compromising the quality. Yongin. Kwon, . Sangmin. Lee, . Hayoon. Yi, . Donghyun. Kwon, . Seungjun. Yang, . Byung. -. Gon. Chun,. Ling Huang, . Petros. . Maniatis. , . Mayur. . Naik. , . Yunheung. . Paek. USENIX ATC’13. Logical and Verbal . Reasoning . Tests. Kuan Xing. 1. and Kirk Becker. 2. 1 . University of Illinois – Chicago; . 2. Pearson VUE, Chicago IL. Acknowledgement: This pilot study was done during first author’s internship at Pearson VUE. The first author wants to thank Pearson VUE, and especially Dr. Kirk Becker for his great support and mentoring.. Presented at EDAMBA summer school, . Soréze. (France) . 23 July – 27 July 2009. An . Example from Research into Hedge Fund Investments . Presenter:. Florian. . Boehlandt. University:. University of. sparsity. in web search click data. Qi . Guo. , Dmitry . Lagun. , . Denis Savenkov. , . Qiaoling. Liu. [qguo3. ,dlagun,denis.savenkov,. qiaoling.liu. ]. @. emory.edu. Mathematics . & . Computer . Flow in Games. Difficulty and Reward. Difficulty Modes and DDA. settable difficulty . levels issues:. The player has to decide too early. .. Games usually ask the player to choose a difficulty level right at the beginning, and at that point the player doesn't actually know how hard the game is going to be because he hasn't played it . An Analysis of Statistical Models and Features for Reading Difficulty Prediction Michael Heilman, Kevyn Collins-Thompson, Maxine Eskenazi Language Technologies Institute Carnegie Mellon University 1 The Goal: To predict the readability of a page of text. . 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:. Saehoon Kim. §. , . Yuxiong He. *. ,. . Seung-won Hwang. §. , . Sameh Elnikety. *. , . Seungjin Choi. §. §. *. Web Search Engine . Requirement. 2. Queries. High quality + Low latency. This talk focuses on how to achieve low latency without compromising the quality. UNC Collaborative Core Center for Clinical Research Speaker Series. August 14, 2020. Jamie E. Collins, PhD. Orthopaedic. and Arthritis Center for Outcomes Research, Brigham and Women’s Hospital. Department of . Time. Andrey. . Kupavskii. , . Liudmila. . Ostroumova. , Alexey . Umnov. , . Svyatoslav. . Usachev. , . Pavel. . Serdyukov. ,. . . Gleb. . Gusev. , . Andrey. for Algorithm Analysis Topics. Mohammed . Farghally. Information Systems Department, . Assiut. University, Egypt. Kyu. Han . Koh. Department of Computer Science, CSU . Stanislaus. Jeremy V. Ernst. School of Education, Virginia Tech.