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A Point-of-Interest Recommendation Method Based on User Check-in Behaviors in Online Social Networks
On model design for simulation of collective intelligence
Cultural appropriation: information technologies as sites of transnational imagination
Designing an Educational Game Facilitating Children’s Understanding of the Development of Social Relationships Using IVAs with Social Group Dynamics
Personalizing Group Recommendation to Social Network Users
Automatic Fine-Grained Localization Of Utility Pole Landmarks On Distributed Acoustic Sensing Traces Based On Bilinear Resnets
Model of Community Emergence in Weighted Social Networks
Emotive media: a review of emotional interfaces and media in human-computer-interaction
KNOWLEDGE‐BASED SYSTEMS
Modeling influence on posting engagement in online social networks: Beyond neighborhood effects
Reconstructing Environmental Variables with Missing Field Data via End-to-End Machine Learning
A Pre-training Oracle for Predicting Distances in Social Networks
Applying and Understanding an Advanced, Novel Deep Learning Approach: A Covid 19, Text Based, Emotions Analysis Study
Expert Systems With Applications
Person Identification between Different Online Social Networks
Social Network and Genre Emergence in Amateur Flash Multimedia
7870_Strong Social Graph Based Trust-Oriented Graph Pattern Matching With Multiple Constraints.
Linguistic reporting of driver behavior: Summary and event description
Learning From the Crowd: Observational Learning in Crowdsourcing Communities
Social Networks Perspective of Firefighters' Adaptive Behaviour and Coordination among Them
Selective Propagation of Social Data in Decentralized Online Social Network
7875_Reproducible Research for Scientific Computing Tools and Strategies for Changing the Culture.
TO DFT OR NOT TO DFT? The answer depends on who is asking and who is answering. Designers might view DFT as a necessary evil that prevents them from achieving the best possible design-"best" meaning high performance, minimum hardware complexity, and low power. From the test engineer's perspective, "best" may be quite different-controllability, observability, and diagnosability being the desired attributes. From a manager's or marketing perspective, "best" includes both sets of attributes-but in the form of costs incurred versus benefits gained. Likewise, for us "best" means an end product that maximizes the cost-to-benefit ratio, with the decision to use DFT ultimately based on its impact on profit. 1 Decision-makers typically make test tradeoffs using models that mainly represent direct costs such as test generation time and tester use. Analyzing a test strategy's impact on other significant factors such as test quality and yield learning requires an understanding of the dynamic nature of the interdomain dependencies of test, manufacturing, and design. Our research centers on modeling the tradeoffs
FamilyID: A Hybrid Approach to Identify Family Information from Microblogs
Enhancing data exploration with a branching history of user operations
Task assignment in spatial crowdsourcing: challenges and approaches
TapSense: combining self-report patterns and typing characteristics for smartphone based emotion detection
Features Found in Twitter Data and Examination of Retweeting Behavior
Near Optimal Strategies for Targeted Marketing in Social Networks
Designing Children’s New Learning Partner: Collaborative Artificial Intelligence for Learning to Solve the Rubik’s Cube