PPT-1 Multi-Application User Interest Modeling

Sampath Jayarathna Center for the Study of Digital Libraries Computer Science amp Engineering Texas AampM University Motivation 2 Personalized Information Delivery Customize search results based on the . Department of Computer Science, KAIST. Dabi Ahn, Taehun Kim, . Soon J. Hyun, Dongman Lee. IEEE 2012 . Web Intelligence and Intelligent Agent Technology. System Workflow. Inferring User Interest Using Topic Structure. Web . System E. ngineering. 02. Modeling Web Applications. Anca Ion. Introduction. Models . represent . a solid starting point for the implementation of a Web application taking into . account. . static . Normally, users perform search tasks using multiple applications in concert: a search engine interface presents lists of potentially relevant documents; a document reader displays their contents; and a third tool—a text editor or personal information management application—is used to record notes and assessments (MS Word and MS PowerPoint). . Prasun Dewan. Department of Computer Science. University of North Carolina at Chapel Hill. dewan@cs.unc.edu. COLLABORATIVE APPLICATION. U1. U2. U3. Application. User inputs “draw red circle”. Coupling. heat exchangers. Modeling, optimization and heat integration. Candidate: Axel Holene ; . Supervisors: . Sigurd. . Skogestad. , Johannes . J. äschke. ;. Modeling. Mass and energy balances. Pinch concept. . Athabasca University. Sima Shabani. October 2012. What is QuizMASter? . Online game show and a knowledge assessment tool. G. ame-based learning environment can provide:. Excitement. Competition. Purpose of QuizMASter is for students to increase their . Presented by: . Mohammad Sajib Al . Seraj. Supervised by:. Prof. Robert Pastel. User Modeling. R. epresentation . of the knowledge and preferences of users . Customization and adaptation systems.  to the user's specific . Grades P-2. Session Objectives. 2. Understand the . application component . of . rigor called . for in the Standards, . as defined by guiding documents. Examine . various activities in . A Story of . Grades 3-5. Session Objectives. 2. Understand the . application component . of . rigor called . for in the Standards, . as defined by guiding documents. Examine . various activities in . A Story of . Hongning Wang. 1. , ChengXiang Zhai. 1. , Feng Liang. 2. . 1. Department of Computer Science . 2. Department of Statistics University of Illinois at Urbana-Champaign Urbana, IL 61801 USA {wang296,czhai,liangf}@Illinois.edu. Acknowledgements : This research is supported by NSF grant 0938074 INTRODUCTION MULTI LAYER PERCEPTRONS (MLP) DATA SET FOR TRAINING Learning weights using multi-layer perceptron in User Interest Modeling INTRODUCTION TO NUMERICAL MODELING IN GEOTECHNICAL ENGINEERING WITH EMPHASIS ON FLAC MODELING www.zamiran.net By Siavash Zamiran, Ph.D., P.E. Geotechnical Engineer, Marino Engineering Associates, Inc. Data Assimilation and Inverse Modeling. Benjamin Gaubert & Daven Henze. MUSICA Kick-off Meeting 22 May 2019. MUSICA Kick-off Meeting 22 May 2019. Ability to model systems that couple the atmospheric chemistry to other earth system model components including ocean, land, ionosphere.. (for ISVs). Sarah Vaughan. Windows Business Group Lead. . sarahv@microsoft.com. . Dave Glover. Microsoft Australia, Developer Platform Group. 0403809914. dglover@microsoft.com. http://blogs.msdn.com/dglover.