2,439 research outputs found
A New Distribution-Random Limit Normal Distribution
This paper introduces a new distribution to improve tail risk modeling. Based
on the classical normal distribution, we define a new distribution by a series
of heat equations. Then, we use market data to verify our model
Determinants of Job Turnover Intentions: Evidence from Singapore
This paper explores both observable and unobservable variables that would affect employed workersâ decisions on job change. We find that age, job satisfaction, satisfaction with working environment or job security, and firm size are among the major factors determining workersâ intentions of job-to-job mobility. Younger workers and workers in smaller firms are more likely to look for other jobs. We also find that men are more likely to consider a change in job than women, but when âactually looking for another jobâ is concerned, men and women do not differ. Furthermore, monthly income and working sector contribute significantly to looking for other jobs.Voluntary job-to-job mobility; Job satisfaction; Logistic regression model
Collaborative Filtering with Social Exposure: A Modular Approach to Social Recommendation
This paper is concerned with how to make efficient use of social information
to improve recommendations. Most existing social recommender systems assume
people share similar preferences with their social friends. Which, however, may
not hold true due to various motivations of making online friends and dynamics
of online social networks. Inspired by recent causal process based
recommendations that first model user exposures towards items and then use
these exposures to guide rating prediction, we utilize social information to
capture user exposures rather than user preferences. We assume that people get
information of products from their online friends and they do not have to share
similar preferences, which is less restrictive and seems closer to reality.
Under this new assumption, in this paper, we present a novel recommendation
approach (named SERec) to integrate social exposure into collaborative
filtering. We propose two methods to implement SERec, namely social
regularization and social boosting, each with different ways to construct
social exposures. Experiments on four real-world datasets demonstrate that our
methods outperform the state-of-the-art methods on top-N recommendations.
Further study compares the robustness and scalability of the two proposed
methods.Comment: Accepted for publication at the 32nd Conference on Artificial
Intelligence (AAAI 2018), New Orleans, Louisian
Extended Quark Potential Model from Random Phase Approximation
The quark potential model is extended to include the sea quark excitation
using the random phase approximation (RPA). The effective quark interaction
preserves the important Quantum Chromodynamics (QCD) properties -- chiral
symmetry and confinement simultaneously. A primary qualitive analysis shows
that the meson as a well-known typical Goldstone boson and the other
mesons made up of valence quark pair such as the meson can
also be described in this extended quark potential model
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