A Faster Algorithm to Build New Users Similarity List in Neighbourhood-based Collaborative Filtering

Neighbourhood-based Collaborative Filtering (CF) has been applied in the industry for several decades, because of the easy implementation and high recommendation accuracy. As the core of neighbourhood-based CF, the task of dynamically maintaining users' similarity list is challenged by cold-start problem and scalability problem. Recently, several methods are presented on solving the two problems. However, these methods applied an $O(n^2)$ algorithm to compute the similarity list in a special case, where the new users, with enough recommendation data, have the same rating list. To address the problem of large computational cost caused by the special case, we design a faster ($O(\frac{1}{125}n^2)$) algorithm, TwinSearch Algorithm, to avoid computing and sorting the similarity list for the new users repeatedly to save the computational resources. Both theoretical and experimental results show that the TwinSearch Algorithm achieves better running time than the traditional method

An Accuracy-Assured Privacy-Preserving Recommender System for Internet Commerce

Recommender systems, tool for predicting users' potential preferences by computing history data and users' interests, show an increasing importance in various Internet applications such as online shopping. As a well-known recommendation method, neighbourhood-based collaborative filtering has attracted considerable attention recently. The risk of revealing users' private information during the process of filtering has attracted noticeable research interests. Among the current solutions, the probabilistic techniques have shown a powerful privacy preserving effect. When facing $k$ Nearest Neighbour attack, all the existing methods provide no data utility guarantee, for the introduction of global randomness. In this paper, to overcome the problem of recommendation accuracy loss, we propose a novel approach, Partitioned Probabilistic Neighbour Selection, to ensure a required prediction accuracy while maintaining high security against $k$NN attack. We define the sum of $k$ neighbours' similarity as the accuracy metric alpha, the number of user partitions, across which we select the $k$ neighbours, as the security metric beta. We generalise the $k$ Nearest Neighbour attack to beta k Nearest Neighbours attack. Differing from the existing approach that selects neighbours across the entire candidate list randomly, our method selects neighbours from each exclusive partition of size $k$ with a decreasing probability. Theoretical and experimental analysis show that to provide an accuracy-assured recommendation, our Partitioned Probabilistic Neighbour Selection method yields a better trade-off between the recommendation accuracy and system security.Comment: replacement for the previous versio

Enhanced current noise correlations in a Coulomb-Majorana device

Majorana bound states (MBSs) nested in a topological nanowire are predicted to manifest nonlocal correlations in the presence of a finite energy splitting between the MBSs. However, the signal of the nonlocal correlations has not yet been detected in experiments. A possible reason is that the energy splitting is too weak and seriously affected by many system parameters. Here we investigate the charging energy induced nonlocal correlations in a hybrid device of MBSs and quantum dots. The nanowire that hosts the MBSs is assumed in proximity to a mesoscopic superconducting island with a finite charging energy. Each end of the nanowire is coupled to one lead via a quantum dot with resonant levels. With a floating superconducting island, the devices shows a negative differential conductance and giant super-Poissonian shot noise, due to the interplay between the nonlocality of the MBSs and dynamical Coulomb blockade effect. When the island is strongly coupled to a bulk superconductor, the current cross correlations at small lead chemical potentials are negative by tuning the dot energy levels. In contrast, the cross correlation is always positive in a non-Majorana setup. This difference may provide a signature for the existence of the MBSs.Comment: 11 pages, 10 figure

Finite-temperature conductivity and magnetoconductivity of topological insulators

The electronic transport experiments on topological insulators exhibit a dilemma. A negative cusp in magnetoconductivity is widely believed as a quantum transport signature of the topological surface states, which are immune from localization and exhibit the weak antilocalization. However, the measured conductivity drops logarithmically when lowering temperature, showing a typical feature of the weak localization as in ordinary disordered metals. Here, we present a conductivity formula for massless and massive Dirac fermions as a function of magnetic field and temperature, by taking into account the electron-electron interaction and quantum interference simultaneously. The formula reconciles the dilemma by explicitly clarifying that the temperature dependence of the conductivity is dominated by the interaction while the magnetoconductivity is mainly contributed by the quantum interference. The theory paves the road to quantitatively study the transport in topological insulators and other two-dimensional Dirac-like systems, such as graphene, transition metal dichalcogenides, and silicene.Comment: 5 pages, 5 figure

Using member galaxy luminosities as halo mass proxies of galaxy groups

Reliable halo mass estimation for a given galaxy system plays an important role both in cosmology and galaxy formation studies. Here we set out to find the way that can improve the halo mass estimation for those galaxy systems with limited brightest member galaxies been observed. Using four mock galaxy samples constructed from semi-analytical formation models, the subhalo abundance matching method and the conditional luminosity functions, respectively, we find that the luminosity gap between the brightest and the subsequent brightest member galaxies in a halo (group) can be used to significantly reduce the scatter in the halo mass estimation based on the luminosity of the brightest galaxy alone. Tests show that these corrections can significantly reduce the scatter in the halo mass estimations by $\sim 50\%$ to $\sim 70\%$ in massive halos depending on which member galaxies are considered. Comparing to the traditional ranking method, we find that this method works better for groups with less than five members, or in observations with very bright magnitude cut.Comment: ApJ accepte

Extrinsic anomalous Hall conductivity of a topologically nontrivial conduction band

A key step towards dissipationless transport devices is the quantum anomalous Hall effect, which is characterized by an integer quantized Hall conductance in a ferromagnetic insulator with strong spin-orbit coupling. In this work, the anomalous Hall effect due to the impurity scattering, namely the extrinsic anomalous Hall effect, is studied when the Fermi energy crosses with the topologically nontrivial conduction band of a quantum anomalous Hall system. Two major extrinsic contributions, the side-jump and skew-scattering Hall conductivities, are calculated using the diagrammatic techniques in which both nonmagnetic and magnetic scattering are taken into account simultaneously. The side-jump Hall conductivity changes its sign at a critical sheet carrier density for the nontrivial phase, while it remains sign unchanged for the trivial phase. The critical sheet carrier densities estimated with realistic parameters lie in an experimentally accessible range. The results imply that a quantum anomalous Hall system could be identified in the good-metal regime.Comment: 5 pages, 4 figure