Estimating Trust Strength For Supporting Effective Recommendation Services

In the age of information explosion, Internet facilitates product searching and collecting much more convenient for users. However, it is time-consuming and exhausting for users to deal with large amounts of product information. In response, various recommendation approaches have been developed to recommend products that match users’ preferences and requirements. In addition to the well-known collaborative filtering recommendation approach, the trust-based recommendation approach is the emerging one. The reason is that most of online communities allow users to express their trust on other users. Based on the analysis of trust relationships, the trust-based recommendation approach finds out and consults the opinions of more reliable users and therefore makes better recommendations. Existing trust-based recommendation techniques consider all trust relationships in a given trust network equally important and give them the same trust strength. However, in a real-world setting, trust relationships may be of various strengths. In response, in this study, we propose a mechanism for trust strength estimation on the basis of the machine learning approach and estimate the trust strength for each existing trust relationship in a given trust network. To overcome the sparsity of the trust network, we also develop a modified trust propagation method to expand the original trust network. Finally, we perform a series of experiments to demonstrate the performance of our trust-based recommendation approach based on the trust strength estimation mechanism. Our empirical evaluation results show that our proposed approach outperforms our benchmark techniques, i.e., the traditional collaborative filtering approach and the original trust-based one

Atomic ionization by sterile-to-active neutrino conversion and constraints on dark matter sterile neutrinos with germanium detectors

The transition magnetic moment of a sterile-to-active neutrino conversion gives rise to not only radiative decay of a sterile neutrino, but also its non-standard interaction (NSI) with matter. For sterile neutrinos of keV-mass as dark matter candidates, their decay signals are actively searched for in cosmic X-ray spectra. In this work, we consider the NSI that leads to atomic ionization, which can be detected by direct dark matter experiments. It is found that this inelastic scattering process for a nonrelativistic sterile neutrino has a pronounced enhancement in the differential cross section at energy transfer about half of its mass, manifesting experimentally as peaks in the measurable energy spectra. The enhancement effects gradually smear out as the sterile neutrino becomes relativistic. Using data taken with germanium detectors that have fine energy resolution in keV and sub-keV regimes, constraints on sterile neutrino mass and its transition magnetic moment are derived and compared with those from astrophysical observations

THE STUDY OF ENERGY LOSS FROM IMPACT ON A CURVED BALL OF GOLF SWINGS

Practicing and correcting positions and movements without understanding the principles were involved with the ball impact and subsequent flight path. This research was focused on the relationships between energy creation and loss when open and closed clubfaces were used to create a curved flight path of the ball. Based on the results of the experiments, the energy loss from different clubface angles was varied and caused different flight trajectories of the ball