PPT-Retrieval Effectiveness of an Ontology-based Model for Info

Khan L McLeod D amp Hovy E Presented by Danielle Lee Agenda Study Purpose Target Data Processing Ontology Development Metadata Query Mechanism Experiment Results Discussion. 19. th. July, Loughborough University, UK. Dr. Tom Jackson, Dr. Ann O’Brien and Dr. Martin Sykora. EMOTIVE Work Packages and Milestones. Contents. Previous Work. Technical Considerations. Retrieval of Datasets. . Matthew F. . RUTLEDGE-TAYLOR, . Christian . LEBIERE, Robert THOMSON,. James . STASZEWSKI . and John R. . ANDERSON. Carnegie . Mellon University, Pittsburgh, PA, USA. 19th Annual ACT-R Workshop: . Pittsburgh, PA, USA. Milton J. Dehn, Ed.D. ., NCSP. Schoolhouse Educational Services. Fall, 2012. Notice of Copyright, . 2012. This . PowerPoint . and accompanying materials are copyrighted by Milton J. Dehn and Schoolhouse Educational Services, LLC. All rights reserved. No photocopying, electronic display, or electronic dissemination of these materials is allowed without written permission. the effectiveness of LDA-based retrieval in large collections. Azzopardi et al. (2004) also discussed the applications of LDA models and reported inconclusive results on several small collections. In . Session. 3: . OPM Serializations. Luc Moreau. L.Moreau@ecs.soton.ac.uk. University of Southampton. Session 3: Aims. In this session, you will learn about:. The XML Schema for OPM. The OWL ontology for OPM. . Session. Thursday. Sep. 17. Dr. Paola Grosso. Assistant Professor. SNE . group. - UvA. p.grosso@uva.nl. Dr. . Ilya. . Baldin. . Director. , Networking Research . and. . Infrastructure. . RENCI. 5970.002. Advanced . Atmospheric Radiation. Dave Turner. Lecture 12. Random vs. Systematic Error. Large random error and large bias. Large random error and small bias. Small random error and large bias. OWL 2 QL & OWL 2 EL Ontologies. Dmitriy Zheleznyakov. 28. th. . of . January, 2014, Oslo. 2. Ontology. All popes are clerics. Benedict XVI is a pope. General rules:. Facts:. . To use ontologies in applications,. (for MODIS). Andy Harris. Jonathan . Mittaz. Prabhat. . Koner. (Chris Merchant, Pierre . LeBorgne. ). Satellite data – pros and cons. Main advantages of satellite data. Frequent and regular global coverage (cloud cover permitting for IR). Yongqun. . “Oliver” He. Unit for Laboratory Animal Medicine. Department of Microbiology and Immunology. Center for Computational Medicine and Bioinformatics. University of Michigan Medical School. All slides ©Addison Wesley, 2008. Beyond Bag of Words. “Bag of Words”. a document is considered to be an unordered collection of words with no relationships. Extending representation. feature-based models. Fatemeh. Azimzadeh. Books. (Manning et al., 2008). Christopher D. Manning, . Prabhakar. . Raghavan. , and . Hinrich. . Schütze. . Introduction to Information Retrieval. Cambridge University Press, 2008. . Zan Gao, . Deyu Wang. , Xiangnan He, Hua . Zhang. Tianjin University . of Technology. National University of Singapore. Previous work. Proposed method. Experiments. Conclusion. Outline. Previous work. PART . I: visual data . processing. PART . II. . Audio Search. Liangliang Cao, . Xiaodan. . Zhuang. University of Illinois at Urbana-Champaign. What is Star Challenge?. Competition to Develop World’s Next-Generation Multimedia Search Technology.