PPT-1 Online Feature Selection for Information Retrieval

Author : briana-ranney | Published Date : 2016-04-13

Niranjan Balasubramanian University of Massachusetts Amherst Joint work with Giridhar Kumaran and Vitor Carvalho Microsoft Corporation James Allan University

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1 Online Feature Selection for Information Retrieval: Transcript


Niranjan Balasubramanian University of Massachusetts Amherst Joint work with Giridhar Kumaran and Vitor Carvalho Microsoft Corporation James Allan University of Massachusetts Amherst. kiritchenkonrccnrcgcca Institute for Information Technology National Research Council Canada Ottawa Canada Mikhail Jiline mzhilinepiphancom Epiphan Systems Inc Ottawa Canada Editor Saeys et al Abstract Sponsored search is a new application domain for CSC . 575. Intelligent Information Retrieval. 2. Source: . Intel. How much information?. Google: . ~100 . PB a . day; 3+ million servers (15 . Exabytes. stored). Wayback Machine has . ~9 . PB + . 100 . . lecture 2. history. Thomas . Krichel. 2011-09-19 . contents . based on a very fine paper by Michael Lesk “The Seven Ages of Information Retrieval”. . That paper was written in 1997, so it does not cover recent advances.. applications. Alan Jović, Karla Brkić, Nikola Bogunović. E-mail: {alan.jovic, karla.brkic, nikola.bogunovic}@fer.hr. Faculty of Electrical Engineering and Computing, University of Zagreb. Department of Electronics, Microelectronics, Computer and Intelligent Systems. Hang Xiao. Background. Feature. a . feature. is an individual . measurable heuristic property of a phenomenon being observed. In character recognition: . horizontal and vertical . profiles, . number of internal holes, stroke . ChengXiang. (“Cheng”) . . Zhai. Department of Computer Science. University of Illinois at Urbana-Champaign. http://www.cs.uiuc.edu/homes/czhai. . Email: czhai@illinois.edu. 1. Yahoo!-DAIS Seminar, UIUC. and R Packages. Houtao Deng. houtao_deng@intuit.com. 1. Data Mining with R. 12/13/2011. Agenda. Concept of feature selection. Feature selection methods. The R packages for feature selection. 12/13/2011. Hongning. Wang. CS@UVa. What is information retrieval?. CS6501: Information Retrieval. CS@UVa. 2. Why information retrieval . Information overload. “. It refers to the . difficulty. a person can have understanding an issue and making decisions that can be caused by the presence of . All slides ©Addison Wesley, 2008. How Much Data is Created Every . Minute?. Source: . https. ://www.domo.com/blog/2012/06/how-much-data-is-created-every-minute/. The Search Problem. Search and Information Retrieval. What is IR?. Sit down before fact as a little child, . be prepared to give up every conceived notion, . follow humbly wherever and whatever abysses nature leads, . or you will learn nothing. . . -- Thomas Huxley --. Fatemeh. Azimzadeh. Books. (Manning et al., 2008). Christopher D. Manning, . Prabhakar. . Raghavan. , and . Hinrich. . Schütze. . Introduction to Information Retrieval. Cambridge University Press, 2008. . Objects from Satellite Imagery Using Genetic Algorithm By: Eyad A. Alashqar ( 120110378 ) Supervised by: Prof. Nabil M. Hewahi A Thesis Submitted in Partial Fulfillment of the Requirements for the Objects from Satellite Imagery Using Genetic AlgorithmByEyad A Alashqar120110378Supervised byProf Nabil M HewahiA Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master i Session 10 – Information Retrieval and Dissemination. Lecturer: Dr. . Perpetua. S. . Dadzie. , Dept. of Information Studies. Contact Information: psdadzie@ug.edu.gh. Session Overview . At the end of the session, the student will be able to.

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