Outlier Detection from Network Data with Subnetwork Interpretation

Detecting a small number of outliers from a set of data observations is always challenging. This problem is more difficult in the setting of multiple network samples, where computing the anomalous degree of a network sample is generally not sufficient. In fact, explaining why the network is exceptional, expressed in the form of subnetwork, is also equally important. In this paper, we develop a novel algorithm to address these two key problems. We treat each network sample as a potential outlier and identify subnetworks that mostly discriminate it from nearby regular samples. The algorithm is developed in the framework of network regression combined with the constraints on both network topology and L1-norm shrinkage to perform subnetwork discovery. Our method thus goes beyond subspace/subgraph discovery and we show that it converges to a global optimum. Evaluation on various real-world network datasets demonstrates that our algorithm not only outperforms baselines in both network and high dimensional setting, but also discovers highly relevant and interpretable local subnetworks, further enhancing our understanding of anomalous networks

Solutions To Develop Small And Medium-Sized Enterprises In Phu Tho Province In The Present Time

During the renewal process in Vietnam, small and medium-sized enterprises are playing an important role that is to contribute to preserving and developing traditional industries and create numerous jobs. It is also the biggest business school for most entrepreneurs before moving on to expand the scale of their business. Accounting for over 97% of the existing enterprises nationwide, small and medium-sized enterprises are operating in an unfavorable economic environment at both the macro and micro levels. They are facing lots of difficulties in production technology, management models, progress, skills of the leadership team and workers, product marketing methods, especially little access to information and financial services, investment capital, etc. In order to contribute to promoting the establishment and development of small and medium-sized enterprises in Phu Tho province, and maximize the potentials of capital, labor, premises, production, etc. among the public, it is necessary to clarify the current situation of local small and medium-sized enterprises, thereby offering some key solutions to effectively support such establishment and development

Knowledge discovery in data streams

Knowing what to do with the massive amount of data collected has always been an ongoing issue for many organizations. While data mining has been touted to be the solution, it has failed to deliver the impact despite its successes in many areas. One reason is that data mining algorithms were not designed for the real world, i.e., they usually assume a static view of the data and a stable execution environment where resources are abundant. The reality however is that data are constantly changing and the execution environment is dynamic. Hence, it becomes difficult for data mining to truly deliver timely and relevant results. Recently, the processing of stream data has received many attention. What is interesting is that the methodology to design stream-based algorithms may well be the solution to the above problem. In this entry, we discuss this issue and present an overview of recent works

CHANGING ROAD TRAFFIC NOISE IN HANOI OF PREVIOUS 10 YEARS

Joint Research on Environmental Science and Technology for the Eart