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You are viewing titles for ARIZONA STATE UNIVERSITY in the Information science available through the UMI Dissertations & Thesis Gradwoorks site
 
Query Expansion For Handling Exploratory And Ambiguous Keyword Queries
 The Impact of Working Memory, Tags and, Tag Clouds on Search of Websites
 
An Information Diffusion Approach for Detecting Emotional Contagion in Online Social Networks
 Topic Sensitive SourceRank: Extending SourceRank for Performing Context-Sensitive Search over Deep Web
 
Volatile Perceptions: The Power of the Public Sphere to Reshape Science
 Advancing Access to Biodiversity Data Using the SALIX Method and Digital Field Guides
 
Analysis of an Information Sharing System Model Within the Community of Navajo County, Arizona
 Multimodal Data Fusion As a Predictior of Missing Information in Social Networks
 
Bridging the digital divide: Homeless women participate in Internet life
 Online usability among Arizona local governments
 
Towards dynamic, real time Informative Warning Systems
 An assessment of the economic, political, and cultural impacts of ICT investments in emerging societies
 
Building decision support for dynamic decision making: A design science approach
 Using online learning modules to promote students' ability to identify and locate empirical research articles
 
Methods for visualization and analysis of geo-spatial data
 Web question answering technology: An empirical test of the task-technology fit model
 
Modular process and service design in situ
 Understanding the virtualization of the backpacker culture and the emergence of the flashpacker: A mixed-method
 
Community discovery in dynamic, rich-context social networks
 Conformal predictions in multimedia pattern recognition
 
An Effective Approach to Biomedical Information Extraction with Limited Training Data
 Finding Provenance Data in Social Media
 
The Impact of Subject Indexes on Semantic Indeterminacy in Enterprise Document Retrieval
 Modeling Time Series Data for Supervised Learning
 
Factors Affecting Behavioral Change through the Use of Computer-Mediated Technology
 Learning from Asymmetric Models and Matched Pairs