62,598 research outputs found
Mathematical Modeling of Product Rating: Sufficiency, Misbehavior and Aggregation Rules
Many web services like eBay, Tripadvisor, Epinions, etc, provide historical
product ratings so that users can evaluate the quality of products. Product
ratings are important since they affect how well a product will be adopted by
the market. The challenge is that we only have {\em "partial information"} on
these ratings: Each user provides ratings to only a "{\em small subset of
products}". Under this partial information setting, we explore a number of
fundamental questions: What is the "{\em minimum number of ratings}" a product
needs so one can make a reliable evaluation of its quality? How users' {\em
misbehavior} (such as {\em cheating}) in product rating may affect the
evaluation result? To answer these questions, we present a formal mathematical
model of product evaluation based on partial information. We derive theoretical
bounds on the minimum number of ratings needed to produce a reliable indicator
of a product's quality. We also extend our model to accommodate users'
misbehavior in product rating. We carry out experiments using both synthetic
and real-world data (from TripAdvisor, Amazon and eBay) to validate our model,
and also show that using the "majority rating rule" to aggregate product
ratings, it produces more reliable and robust product evaluation results than
the "average rating rule".Comment: 33 page
Quaternion Electromagnetism and the Relation with 2-Spinor Formalism
By using complex quaternion, which is the system of quaternion representation
extended to complex numbers, we show that the laws of electromagnetism can be
expressed much more simply and concisely. We also derive the quaternion
representation of rotations and boosts from the spinor representation of
Lorentz group. It is suggested that the imaginary 'i' should be attached to the
spatial coordinates, and observe that the complex conjugate of quaternion
representation is exactly equal to parity inversion of all physical quantities
in the quaternion. We also show that using quaternion is directly linked to the
two-spinor formalism. Finally, we discuss meanings of quaternion, octonion and
sedenion in physics as n-fold rotationComment: Version published in journal Universe (2019
Neutron Stars with Bose-Einstein Condensation of Antikaons as MIT Bags
We investigate the properties of an antikaon in medium, regarding itas a MIT
bag. We first construct the MIT bag model for a kaon with and
in order to describe the interaction of-quarks in hyperonic matter in the
framework of the modifiedquark-meson coupling model. The coupling constant
in the density-dependent bag constant is treated
as afree parameter to reproduce the optical potential of a kaon in asymmetric
matter and all other couplings are determined by usingSU(6) symmetry and the
quark counting rule. With various values ofthe kaon potential, we calculate the
effective mass of a kaon inmedium to compare it with that of a point-like kaon.
We thencalculate the population of octet baryons, leptons and and
theequation of state for neutron star matter. The results show thatkaon
condensation in hyperonic matter is sensitive to the -quarkinteraction and
also to the way of treating the kaon. The mass andthe radius of a neutron star
are obtained by solving theTolmann-Oppenheimer-Volkoff equation.Comment: 14 figure
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Radial basis function classifier construction using particle swarm optimisation aided orthogonal forward regression
We develop a particle swarm optimisation (PSO)
aided orthogonal forward regression (OFR) approach for constructing radial basis function (RBF) classifiers with tunable nodes. At each stage of the OFR construction process, the centre vector and diagonal covariance matrix of one RBF node is determined efficiently by minimising the leave-one-out (LOO) misclassification rate (MR) using a PSO algorithm. Compared with the state-of-the-art regularisation assisted orthogonal least square algorithm based on the LOO MR for selecting fixednode RBF classifiers, the proposed PSO aided OFR algorithm for constructing tunable-node RBF classifiers offers significant advantages in terms of better generalisation performance and smaller model size as well as imposes lower computational complexity in classifier construction process. Moreover, the proposed algorithm does not have any hyperparameter that requires costly tuning based on cross validation
Electro-optic scanning of light coupled from a corrugated LiNbO3 waveguide
Light diffracted from a grating output coupler in a Ti-diffused LiNbO3 waveguide is scanned electro-optically. Using a coupling length of 2.5 mm in our arrangement we have demonstrated a scanning capability of one resolved spot per 3 V/Β΅m applied field
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Sparse kernel density estimation technique based on zero-norm constraint
A sparse kernel density estimator is derived based on the zero-norm constraint, in which the zero-norm of the kernel weights is incorporated to enhance model sparsity. The classical Parzen window estimate is adopted as the desired response for density estimation, and an approximate function of the zero-norm is used for achieving mathemtical tractability and algorithmic efficiency. Under the mild condition of the positive definite design matrix, the kernel weights of the proposed density estimator based on the zero-norm approximation can be obtained using the multiplicative nonnegative quadratic programming algorithm. Using the -optimality based selection algorithm as the preprocessing to select a small significant subset design matrix, the proposed zero-norm based approach offers an effective means for constructing very sparse kernel density estimates with excellent generalisation performance
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