The COVID-19 pandemic has hit the world hard. reaction to related issues been pouring into social platforms, such as Twitter. Many public officials and governments use Twitter make policy announcements. People keep close track of information express their concerns about policies on It is beneficial yet challenging derive important or knowledge out data. In this paper, we propose a Tripartite Gr...

This abstract presents a collection of clustering and decomposition techniques enabling the construction of sparse and locality preserving representations for arbitrary networks. These new clustering techniques have already found several powerful applications in the area of distributed network algorithms. Two of these applications are described in this abstract, namely, routing with polynomial ...

A clique clustering of a graph is a partitioning of its vertices into disjoint cliques. The quality of a clique clustering is measured by the total number of edges in its cliques. We consider the online variant of the clique clustering problem, where the vertices of the input graph arrive one at a time. At each step, the newly arrived vertex forms a singleton clique, and the algorithm can merge...

A join-index is a data structure used for processing join queries in databases. Join-indices use precomputation techniques to speed up online query processing and are useful for data sets which are updated infrequently. The I/O cost of join computation using a join-index with limited buffer space depends primarily on the page-access sequence used to fetch the pages of the base relations. Given ...

In this paper, we have proposed, developed and experimentally validated our novel subspace data stream clustering, termed PreDeConStream. The technique is based on the two phase mode of mining streaming data, in which the first phase represents the process of the online maintenance of a data structure, that is then passed to an offline phase of generating the final clustering model. The techniq...

A Join Index is a data structure used for processing join queries in databases. Join indices use pre-computation techniques to speed up online query processing and are useful for data-sets which are updated infrequently. The cost of join computation using a join-index with limited buuer space depends primarily on the page-access sequence used to fetch the pages of the base relations. Given the ...

To facilitate front-line teachers to provide more efficient cases for classroom teaching activities in limited time, it is necessary conduct clustering analysis of online cases. The existing study on text-based resources focuses the representation and fusion different views texts discovery consistent allocation, ignores high-dimensional sparsity text data. this end, paper studies evaluation res...

As the adoption of service-oriented paradigms in the IoT (Internet of Things) environment, real-world devices will open their capabilities through service interfaces, which enable other functional entities to interact with them. In an IoT application, it is indispensable to find suitable services for satisfying users' requirements or replacing the unavailable services. However, from the perspec...

We present an online video segmentation algorithm based on a novel nonparametric Bayesian clustering method called Bayesian Split-Merge Clustering (BSMC). BSMC can efficiently cluster dynamically changing data through split and merge processes at each time step, where the decision for splitting and merging is made by approximate posterior distributions over partitions with Dirichlet Process (DP...