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Found 7 papers, 1 papers with code
Measuring the Predictability of Recommender Systems using Structural Complexity Metrics
This study introduces data-driven metrics to measure the predictability of RS based on the structural complexity of the user-item rating matrix.
QuickCent: a fast and frugal heuristic for harmonic centrality estimation on scale-free networks
Our experiments show that QuickCent is able to make estimates that are competitive in accuracy with the best alternative methods tested, either on synthetic scale-free networks or empirical networks.
Challenges in Forecasting Malicious Events from Incomplete Data
As we show in this paper, the process of filtering reduces the predictability of cyber-attacks.
Quantifying the Effects of Recommendation Systems
Recommendation systems today exert a strong influence on consumer behavior and individual perceptions of the world.
Learning Behavioral Representations from Wearable Sensors
Continuous collection of physiological data from wearable sensors enables temporal characterization of individual behaviors.
Discovering patterns of online popularity from time series
By clustering the multidimensional time-series of the popularity of contents coupled with other domain-specific dimensions, we uncover two main patterns of popularity: bursty and steady temporal behaviors.
Characterizing Activity on the Deep and Dark Web
The deep and darkweb (d2web) refers to limited access web sites that require registration, authentication, or more complex encryption protocols to access them.
