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

A Situation of Economic Management in NTU Cooperative Fuzzy Games

In economic management, we often use some (divisible) private resources to cooperative. Fuzzy coalitions always be used to describe this situation in cooperative fuzzy games. In this paper, we proposed two new solution concepts in NTU cooperative fuzzy games, and discussed their properties

Mean almost periodicity and moment exponential stability of discrete-time stochastic shunting inhibitory cellular neural networks with time delays

summary:By using the semi-discrete method of differential equations, a new version of discrete analogue of stochastic shunting inhibitory cellular neural networks (SICNNs) is formulated, which gives a more accurate characterization for continuous-time stochastic SICNNs than that by Euler scheme. Firstly, the existence of the 2th mean almost periodic sequence solution of the discrete-time stochastic SICNNs is investigated with the help of Minkowski inequality, Hölder inequality and Krasnoselskii's fixed point theorem. Secondly, the moment global exponential stability of the discrete-time stochastic SICNNs is also studied by using some analytical skills and the proof of contradiction. Finally, two examples are given to demonstrate that our results are feasible. By numerical simulations, we discuss the effect of stochastic perturbation on the almost periodicity and global exponential stability of the discrete-time stochastic SICNNs

Ontology-Based Semantic Retrieval for Education Management Systems

The traditional information retrieval technologies are based on keywords, and therefore provide limited capabilities to capture the conceptualizations associated with user needs and contents. As a new technology of information retrieval, semantic retrieval can retrieve information resource fully and precisely based on the knowledge understanding and knowledge reasoning. Ontology, which can well represent and reason about the domain knowledge, is proved to be very useful in the semantic retrieval. On this basis, in this paper, we propose a complete ontology-based semantic retrieval approach and framework for education management system. Firstly, we present some rules for constructing domain ontology from the education management system; Then, a semantic annotation method of the constructed ontology is given; Further, the ontologybased semantic retrieval algorithmis proposed; Finally, a complete framework is developed and some experiments are done. Conducted experiments show that our semantic retrieval model obtained comparable and better performance results than the traditional information retrieval technology for education management system

Research on Application of Kansei Image of Culture in Big data of Product Design

In pursuit of internationalization and globalization, the multinational corporations have begun to take into account the cultural differences between different regions for their product design and marketing strategy. This paper further clarifies the difference between the Kansei preferences and tendencies of consumers through the discussion on the relationship between products and the Kansei demand of consumers with different cultural backgrounds. In addition, in this paper, the Kansei demand of consumers will be learned through collecting the Kansei images of customers with different cultural backgrounds and learning about the differences of Kansei image affected by different cultural backgrounds and the Kansei factors such as the thoughts and feeling preferences of consumers under the influences of local cultures. Then, the factors affecting the Kansei demands of consumers with different cultural backgrounds are correctly analyzed, which will be helpful for the designers to master these design elements and apply them into product shape and functions, thereby designing the products that meet the consumers’ expectations and improving the additional values of the products

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

Sn(II)-containing phosphates as optoelectronic materials

We theoretically investigate Sn(II) phosphates as optoelectronic materials using first principles calculations. We focus on known prototype materials Sn$_n$P$_2$O$_{5+n}$ (n=2, 3, 4, 5) and a previously unreported compound, SnP$_2$O$_6$ (n=1), which we find using global optimization structure prediction. The electronic structure calculations indicate that these compounds all have large band gaps above 3.2 eV, meaning their transparency to visible light. Several of these compounds show relatively low hole effective masses ($\sim$2-3 m$_0$), comparable the electron masses. This suggests potential bipolar conductivity depending on doping. The dispersive valence band-edges underlying the low hole masses, originate from the anti-bonding hybridization between the Sn 5s orbitals and the phosphate groups. Analysis of structure-property relationships for the metastable structures generated during structure search shows considerable variation in combinations of band gap and carrier effective masses, implying chemical tunability of these properties. The unusual combinations of relatively high band gap, low carrier masses and high chemical stability suggests possible optoelectronic applications of these Sn(II) phosphates, including p-type transparent conductors. Related to this, calculations for doped material indicate low visible light absorption, combined with high plasma frequencies.Comment: 10 pages, 10 figures, Supplementary informatio