A Hybrid Approach to Three-Way Conversational Recommendation

Conversational recommendation is ubiquitous in e-commerce, while three-way recommendation provides friendly choices for service providers and users. However, their combination has not been studied yet. In this paper, we introduce the three-way conversational recommendation problem, and design the hybrid conversational recommendation (HTCR) algorithm to address it. First, a new recommendation problem is defined by considering the man-machine interaction as well as the misclassification and promotion costs. The optimization objective of the problem is to minimize the total cost. Second, a popularity-based technique is designed for user cold-start recommendation, where the user maturity is responsible for deciding when HTCR turns to the second technique. Third, an incremental matrix factorization technique is designed for regular recommendation. It is efficient since only a few rounds of training are needed for newly acquired user feedback. Experiments were undertaken on three well-known datasets, including Jester, MovieLens 100K, and MovieLens 1M. Results demonstrated that our algorithm outperformed state-of-the-art ones in terms of average cost.

Fractal fluctuations in the cardiovascular dynamical system : from the autonomic control to the central nervous system influence

The fractal component in the complex fluctuations of the human heart rate represents a dynamic feature that is widely observed in diverse fields of natural and artificial systems. It is also of clinical significance as the diminishing of the fractal dynamics appears to correlate with heart disease processes and adverse cardiac events in old age. While the autonomic nervous system directly controls the pacemaker cells of the heart, it does not provide an immediate characterization of the complex heart rate variability (HRV). The central nervous system (CNS) is known to be an important modulator for various cardiac functions. However, its role in the fractal HRV is largely unclear. In this research, human experiments were conducted to study the influence of the central nervous system on fractal dynamics of healthy human HRV. The head up tilt (HUT) maneuver is used to provide a perturbation to the autonomic nervous system. The subsequent fractal effect in the simultaneously recorded electroencephalography and beat-to-beat heart rate data was examined. Using the recently developed multifractal factorization technique, the common multifractality in the data fluctuation was analyzed. An empirical relationship was uncovered which shows the increase (decrease) in HRV multifractality is associated with the increase (decrease) in multifractal correlation between scale-free HRV and the cortical expression of the brain dynamics in 8 out of 11 healthy subjects. This observation is further supported using surrogate analysis. The present findings imply that there is an integrated central-autonomic component underlying the cortical expression of the HRV fractal dynamics. It is proposed that the central element should be incorporated in the fractal HRV analysis to gain a more comprehensive and better characterization of the scale-free HRV dynamics. This study provides the first contribution to the HRV multifractal dynamics analysis in HUT. The multivariate fractal analysis using factorization technique is also new and can be applied in the more general context in complex dynamics research.

Fractal fluctuations in the cardiovascular dynamical system : from the autonomic control to the central nervous system influence

The fractal component in the complex fluctuations of the human heart rate represents a dynamic feature that is widely observed in diverse fields of natural and artificial systems. It is also of clinical significance as the diminishing of the fractal dynamics appears to correlate with heart disease processes and adverse cardiac events in old age. While the autonomic nervous system directly controls the pacemaker cells of the heart, it does not provide an immediate characterization of the complex heart rate variability (HRV). The central nervous system (CNS) is known to be an important modulator for various cardiac functions. However, its role in the fractal HRV is largely unclear. In this research, human experiments were conducted to study the influence of the central nervous system on fractal dynamics of healthy human HRV. The head up tilt (HUT) maneuver is used to provide a perturbation to the autonomic nervous system. The subsequent fractal effect in the simultaneously recorded electroencephalography and beat-to-beat heart rate data was examined. Using the recently developed multifractal factorization technique, the common multifractality in the data fluctuation was analyzed. An empirical relationship was uncovered which shows the increase (decrease) in HRV multifractality is associated with the increase (decrease) in multifractal correlation between scale-free HRV and the cortical expression of the brain dynamics in 8 out of 11 healthy subjects. This observation is further supported using surrogate analysis. The present findings imply that there is an integrated central-autonomic component underlying the cortical expression of the HRV fractal dynamics. It is proposed that the central element should be incorporated in the fractal HRV analysis to gain a more comprehensive and better characterization of the scale-free HRV dynamics. This study provides the first contribution to the HRV multifractal dynamics analysis in HUT. The multivariate fractal analysis using factorization technique is also new and can be applied in the more general context in complex dynamics research.

AMatrix factorization technique using parameter tuning of singular value decomposition for Recommender Systems

In this article we explained the concepts of SVD and algorithm evolution. MF technique and the working of it with computational formulas. PCA withstep-by-step approach with example and A novel approach of Hyper SVD and How to fine tune it and pseudocode of the Hyper SVD with the Experimental setup using SurpriseLib and computing RMSE and MSE for the accuracy purpose and solving with the real time example which solves the cold start hassle also together and it can be seen that comparison of SVD and Hyper SVD and Random algorithm is done and types of Movies they recommended. There is far more difference between the results of the both algorithms and movie recommendations as per the results Hyper SVD is flexible and efficient and superior compared to other algorithms.

Some families of differential equations associated with the Gould-Hopper-Frobenius-Genocchi polynomials

<abstract><p>The basic objective of this paper is to utilize the factorization technique method to derive several properties such as, shift operators, recurrence relation, differential, integro-differential, partial differential expressions for Gould-Hopper-Frobenius-Genocchi polynomials, which can be utilized to tackle some new issues in different areas of science and innovation.</p></abstract>

Exact conditions for preservation of the partial indices of a perturbed triangular 2 × 2 matrix function

The possible instability of partial indices is one of the important constraints in the creation of approximate methods for the factorization of matrix functions. This paper is devoted to a study of a specific class of triangular matrix functions given on the unit circle with a stable and unstable set of partial indices. Exact conditions are derived that guarantee a preservation of the unstable set of partial indices during a perturbation of a matrix within the class. Thus, even in this probably simplest of cases, when the factorization technique is well developed, the structure of the parametric space (guiding the types of matrix perturbations) is non-trivial.