Diversifying Top-K Results

Top-k query processing finds a list of k results that have largest scores w.r.t the user given query, with the assumption that all the k results are independent to each other. In practice, some of the top-k results returned can be very similar to each other. As a result some of the top-k results returned are redundant. In the literature, diversified top-k search has been studied to return k results that take both score and diversity into consideration. Most existing solutions on diversified top-k search assume that scores of all the search results are given, and some works solve the diversity problem on a specific problem and can hardly be extended to general cases. In this paper, we study the diversified top-k search problem. We define a general diversified top-k search problem that only considers the similarity of the search results themselves. We propose a framework, such that most existing solutions for top-k query processing can be extended easily to handle diversified top-k search, by simply applying three new functions, a sufficient stop condition sufficient(), a necessary stop condition necessary(), and an algorithm for diversified top-k search on the current set of generated results, div-search-current(). We propose three new algorithms, namely, div-astar, div-dp, and div-cut to solve the div-search-current() problem. div-astar is an A* based algorithm, div-dp is an algorithm that decomposes the results into components which are searched using div-astar independently and combined using dynamic programming. div-cut further decomposes the current set of generated results using cut points and combines the results using sophisticated operations. We conducted extensive performance studies using two real datasets, enwiki and reuters. Our div-cut algorithm finds the optimal solution for diversified top-k search problem in seconds even for k as large as 2,000.Comment: VLDB201

Traffic Danger Recognition With Surveillance Cameras Without Training Data

We propose a traffic danger recognition model that works with arbitrary traffic surveillance cameras to identify and predict car crashes. There are too many cameras to monitor manually. Therefore, we developed a model to predict and identify car crashes from surveillance cameras based on a 3D reconstruction of the road plane and prediction of trajectories. For normal traffic, it supports real-time proactive safety checks of speeds and distances between vehicles to provide insights about possible high-risk areas. We achieve good prediction and recognition of car crashes without using any labeled training data of crashes. Experiments on the BrnoCompSpeed dataset show that our model can accurately monitor the road, with mean errors of 1.80% for distance measurement, 2.77 km/h for speed measurement, 0.24 m for car position prediction, and 2.53 km/h for speed prediction.Comment: To be published in proceedings of Advanced Video and Signal-based Surveillance (AVSS), 2018 15th IEEE International Conference on, pp. 378-383, IEE

More is simpler : effectively and efficiently assessing node-pair similarities based on hyperlinks

Similarity assessment is one of the core tasks in hyperlink analysis. Recently, with the proliferation of applications, e.g., web search and collaborative filtering, SimRank has been a well-studied measure of similarity between two nodes in a graph. It recursively follows the philosophy that "two nodes are similar if they are referenced (have incoming edges) from similar nodes", which can be viewed as an aggregation of similarities based on incoming paths. Despite its popularity, SimRank has an undesirable property, i.e., "zero-similarity": It only accommodates paths with equal length from a common "center" node. Thus, a large portion of other paths are fully ignored. This paper attempts to remedy this issue. (1) We propose and rigorously justify SimRank*, a revised version of SimRank, which resolves such counter-intuitive "zero-similarity" issues while inheriting merits of the basic SimRank philosophy. (2) We show that the series form of SimRank* can be reduced to a fairly succinct and elegant closed form, which looks even simpler than SimRank, yet enriches semantics without suffering from increased computational cost. This leads to a fixed-point iterative paradigm of SimRank* in O(Knm) time on a graph of n nodes and m edges for K iterations, which is comparable to SimRank. (3) To further optimize SimRank* computation, we leverage a novel clustering strategy via edge concentration. Due to its NP-hardness, we devise an efficient and effective heuristic to speed up SimRank* computation to O(Knm) time, where m is generally much smaller than m. (4) Using real and synthetic data, we empirically verify the rich semantics of SimRank*, and demonstrate its high computation efficiency

An alternating direction and projection algorithm for structure-enforced matrix factorization

Structure-enforced matrix factorization (SeMF) represents a large class of mathematical models appearing in various forms of principal component analysis, sparse coding, dictionary learning and other machine learning techniques useful in many applications including neuroscience and signal processing. In this paper, we present a unified algorithm framework, based on the classic alternating direction method of multipliers (ADMM), for solving a wide range of SeMF problems whose constraint sets permit low-complexity projections. We propose a strategy to adaptively adjust the penalty parameters which is the key to achieving good performance for ADMM. We conduct extensive numerical experiments to compare the proposed algorithm with a number of state-of-the-art special-purpose algorithms on test problems including dictionary learning for sparse representation and sparse nonnegative matrix factorization. Results show that our unified SeMF algorithm can solve different types of factorization problems as reliably and as efficiently as special-purpose algorithms. In particular, our SeMF algorithm provides the ability to explicitly enforce various combinatorial sparsity patterns that, to our knowledge, has not been considered in existing approaches

The antioxidant effect of Asparagus cochinchinensis (Lour.) Merr. shoot in d-galactose induced mice aging model and in vitro

AbstractBackgroundAn increasing number of plant components and their extracts have been shown to have beneficial health effects in humans. We aimed to explore the antioxidant effects of the aqueous extract of Asparagus cochinchinensis (Lour.) Merr. shoot in vivo and in vitro.MethodsA total of 80 Kun Ming mice were randomly divided into four groups (20/group). The mice in the control group received a daily subcutaneous injection of saline. A daily injection of D-galactose was administered to the aging model group, the vitamin C (Vc) group (positive control group), and the extract treatment group. Regular measurement of blood cells, nitric oxide synthase (NOS), catalase (CAT) activities, superoxide dismutase (SOD) activities, nitric oxide (NO), and malondialdehyde (MDA) concentration, and the expressions of NOS, SOD, and glutathione peroxidase (GPX) in serum levels were obtained. Furthermore, the microstructure of mice viscera was observed using hematoxylin and eosin staining.ResultsThe aqueous extract of A. cochinchinensis (Lour.) Merr. had similar 1,1-diphenyl-2-picrylhydrazyl radical 2,2-diphenyl-1-(2,4,6-trinitrophenyl) hydrazyl (DPPH·) [or 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS+)] and higher hydroxyl radicals (or superoxide anion; p < 0.05) radical scavenging capabilities to Vc. Moreover, compared with the aging model group, the aqueous extract of A. cochinchinensis (Lour.) Merr. shoot could obviously increase NOS, CAT, and SOD activities and the NO content, and reduce the MDA content (p < 0.05). Additionally, the microstructure of mice viscera was obviously improved and the expressions of NOS, SOD and GPX were also manifestly increased in the treatment group (p < 0.05).ConclusionThe aqueous extract of A. cochinchinensis (Lour.) Merr. shoot had a strong radical scavenging capability in vivo and in vitro, and might be used to diminish radicals in the body and consequently prevent aging

A stochastic control problem arising from relaxed wealth tracking with a monotone benchmark process

This paper studies a nonstandard stochastic control problem motivated by the optimal consumption in an incomplete market with wealth tracking of a non-decreasing benchmark process. In particular, the monotone benchmark is modelled by the running maximum of a drifted Brownian motion. We consider a relaxed tracking formulation using capital injection such that the wealth compensated by the injected capital dominates the benchmark process at all times. The stochastic control problem is to maximize the expected utility on consumption deducted by the cost of the capital injection under the dynamic floor constraint. By introducing two auxiliary state processes with reflections, an equivalent auxiliary control problem is formulated and studied such that the singular control of capital injection and the floor constraint can be hidden. To tackle the HJB equation with two Neumann boundary conditions, we establish the existence of a unique classical solution to the dual PDE in a separation form using some novel probabilistic representations involving the dual reflected processes and the local time. The proof of the verification theorem on the optimal feedback control can be carried out by some technical stochastic flow analysis of the dual reflected processes and estimations of the optimal control.Comment: Keywords: Non-decreasing benchmark, capital injection, optimal consumption, Neumann boundary conditions, probabilistic representation, reflected diffusion processe

Centralized systemic risk control in the interbank system: Relaxed control and Gamma-convergence

This paper studies a systemic risk control problem by the central bank, which dynamically plans monetary supply for the interbank system with borrowing and lending activities. Facing both heterogeneity among banks and the common noise, the central bank aims to find an optimal strategy to minimize the average distance between log-monetary reserves and some prescribed capital levels for all banks. A relaxed control approach is adopted, and an optimal randomized control can be obtained in the system with finite banks by applying Ekeland's variational principle. As the number of banks grows large, we further prove the convergence of optimal strategies using the Gamma-convergence arguments, which yields an optimal relaxed control in the mean field model. It is shown that the limiting optimal relaxed control is linked to a solution of a stochastic Fokker-Planck-Kolmogorov (FPK) equation. The uniqueness of the solution to the stochastic FPK equation is also established under some mild conditions.Comment: Keywords: Systemic risk; interbank system; relaxed control; mean field model; stochastic FPK equation; Gamma-convergenc

An extended Merton problem with relaxed benchmark tracking

This paper studies a Merton's optimal portfolio and consumption problem in an extended formulation incorporating the tracking of a benchmark process described by a geometric Brownian motion. We consider a relaxed tracking formulation such that that the wealth process compensated by a fictitious capital injection outperforms the external benchmark at all times. The fund manager aims to maximize the expected utility of consumption deducted by the cost of the capital injection, where the latter term can also be regarded as the expected largest shortfall with reference to the benchmark. By introducing an auxiliary state process with reflection, we formulate and tackle an equivalent stochastic control problem by means of the dual transform and probabilistic representation, where the dual PDE can be solved explicitly. On the strength of the closed-form results, we can derive and verify the feedback optimal control in the semi-analytical form for the primal control problem, allowing us to observe and discuss some new and interesting financial implications on portfolio and consumption decision making induced by the additional risk-taking in capital injection and the goal of tracking.Comment: Keywords: Benchmark tracking, capital injection, expected largest shortfall, consumption and portfolio choice, Neumann boundary conditio