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This paper studies the problem of top-k structural diversity search, which is to compute k users with the highest structural diversities that is measured by the number of connected components in the neighborhood of a user. As the existing algorithms are not scalable for processing large graphs due to their limits, in this paper we propose a scalable algorithm Div-TriE to improve the e ciency. Div-TriE...
Our group recommender system was targeted at a scenario that requires the adoption of group recommendation techniques to conserve computational resources. The profile aggregation strategy was used in our work to implement this group recommendation system. Key to our work, user clustering is also the first step of our work. The accuracy of user clustering could be improved once we processed the data...
In current days, data tend to become much bigger than before, and the distributed computing system is an prevalent option to deal with them. As one of powerful tools, MapReduce framework provides a cheap and efficient way to write parallel programs to run on distributed computing systems. Chance discovery (CD) is an extension of data mining, where chance refers to rare but important events or situations...
Memory partitioning is widely adopted to efficiently increase the memory bandwidth by using multiple memory banks and reducing data access conflict. Previous methods for memory partitioning mainly focused on one-dimensional arrays. As a consequence, designers must flatten a multidimensional array to fit those methodologies. In this work we propose an automatic memory partitioning scheme for multidimensional...
In this paper, we focus on the interference alignment precoder design for cellular system. Varying from the traditional constrained optimization method, we reformulate the optimization problem on the complex Grassmann manifold and derive a novel steepest descent algorithm to achieve perfect interference alignment. Moreover our proposed algorithm only requires the participation of transmitter. Thus...
The site selection and layout of automatic teller machines (ATMs) are important parts of operation and management system of banks. Different addresses usually lead to different returns. It is difficult for us to decide which place is the best one. In this paper, we investigate on the factors of ATMs planning and location model, and make a judgment and forecast by the application of the model, in which...
In this paper we present a new clustering method based on K-means that have avoided alternative randomness of initial center. This paper focused on K-means algorithm to the initial value of the dependence of K selected from the aspects of the algorithm is improved. First, the initial clustering number is radicN. Second, through the application of the sub-merger strategy the categories were combined...
To efficiently reduce space complexity of a discernibility matrix, a compact structure, the so-called "condensing tree" (denoted by C-Tree for short ), was introduced, and two efficiently heuristic algorithms based on C-Tree for attribute reduction were presented, but the previously proposed algorithms only obtain one attribute subset. Therefore, in this paper, a novel condensing tree based...
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