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No more endless PDFs. Discover the core value of the latest top-tier research in one article.
Personalized ery Expansion for Web Search Using Social Keywords
Influence Propagation for Social Graph-based Recommendations
Toward microtask crowdsourcing software design work
Small Data: Effective Data Based on Big Communication Research in Social Networks
Comparing Topics of Scholars' Blog Posts in an Academic Social Networking Site and Publication Keywords
Imaging Hidden Objects with Consumer LiDAR via Motion Induced Sampling
Detecting Socially Significant Music Events Using Temporally Noisy Labels
Using Social Interaction Between Friends in Knowledge-Based Personalized Recommendation
A New Family of Divergences Originating From Model Adequacy Tests and Application to Robust Statistical Inference
An empirical study of workers' behavior in spatial crowdsourcing
Creation of Bi-lingual Social Network Dataset Using Classifiers
Layer Zero: An Approach for Deepening Self-reflection on Instagram Shares
How Often Should I Access My Online Social Networks?
moviQuest-MAS: An Intelligent Platform for Ubiquitous Social Networking Business
<i>AsEmo:</i> Automatic Approach for EEG-Based Multiple Emotional State Identification
An ontology-based recommendation system for people with autism and technology apps: Ontology application for helping persons with autism
Exploring Ideation: Knowledge Development in Science through the Lens of Semantic and Social Networks
The end consumers of Smart Grid have NO say in the ecosystem of electricity Grid. The price of electricity and infrastructure of grid have been solely governed by utility companies and government entities. One of the objectives of the smart grid is to bring consumer on board using IoT technologies. Peak demand is a major concern for government and utility. Since different neighborhood would have different consumption pattern and hence load forecasting model at utility level would not predict load at all neighborhood. Socio-economic activities of consumers of a particular neighborhood are coherent. Existing research on this topic considers uniform distribution of assets and uniformity in appliances and pattern of consumption hence they are not good enough for Indian condition. The behavioral pattern of user, other economic activities and different aspect of the weather affect the consumption. In this paper we analyzed the effect of socioeconomic dynamics on demand, developed forecasting mechanism and presented the results. This study reveals that the peak demand is actually growing exponentially. Moreover a unique mechanism of forecasting is presented in this paper which is a two steps process-(i) initially a template pattern of consumption is created using parametric estimation, (ii) then total consumption of the day is created using machine learning technique and (ii) finally total consumption is redistributed to deduce time of the day consumption
A trust-based privacy-preserving friend recommendation scheme for online social networks
Discovering Emerging Topics in Social Streams via Link-Anomaly Detection
Knowledge Extraction from Twitter Towards Infectious Diseases in Spanish
The Method of Analysis of Data from Social Networks Using Rapidminer
A framework for seed user identification across multiple online social networks
Clustering Life Course to Understand the Heterogeneous Effects of Life Events, Gender, and Generation on Habitual Travel Modes
What is the impact of service quality on customers’ satisfaction during COVID-19 outbreak? New findings from online reviews analysis
Do Neighbor Buddies Make a Difference in Reblog Likelihood? An Analysis on SINA Weibo Data
Social and geographic contexts of adolescent substance use: The moderating effects of age and gender
Answering Skyline Queries over Incomplete Data with Crowdsourcing(Extended Abstract)
5642_Machine learning classification methods in hyperspectral data processing for agricultural applications.
Design of viral marketing strategies for product cross-sell through social networks