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There has been a surge in research interest in learning feature representation of networks in recent times. Researchers, motivated by the recent successes of embeddings in natural language processing and advances in deep learning, have explored various means for network embedding. Network embedding is useful as it can exploit off-the-shelf machine learning algorithms for network mining tasks like...
Recommender systems have attracted much attention in last decades, which can help the users explore new items in many applications. As a popular technique in recommender systems, item recommendation works by recommending items to users based on their historical interactions. Conventional item recommendation methods usually assume that users and items are stationary, which is not always the case in...
Mining activities has caused long-term change in land surface and hydrological cycle. Accurate information of vegetation structure is important for assessing how mining activities affect ecosystem in mining areas. A remote sensing method based on vegetation cover monitoring and assessment by using Landsat data sets with the temporal coverage from 1989 to 2015 was presented and applied to the Pingshuo...
Classification of high frequency micro logs has been completed. A model is proposed in which the direct influence is based on some factors: the micro logger's aggregation, the activity, the amount of microblog comments and the number of fans, and the indirect influence is based on the forward depth and repost time. Official microblog "Chongqing Mobile" and grassroots microblog "Hong...
Mining closed frequent item set(CFI) plays a fundamental role in many real-world data mining applications. However, memory requirement and computational cost have become the bottleneck of CFI mining algorithms, particularly when confronting with large scale datasets, which herewith makes mining closed frequent item set from large scale datasets a significant and challenging issue. To address the above...
Mining closed frequent itemset (CFI) plays an essential role in many real-world data mining applications. With the emergence of abundant large-scale data sets, it now turns to be a significant and challenging issue to mine CFI concurrently. This paper proposes a parallel balanced mining algorithm for CFI based on the MapReduce platform. The proposed algorithm adopts Greedy strategy to group items...
This is a article of research which bases on the classical granular computing and the Association Rules, focus on the association rules and decision-making rules of the information system. Firstly, defines a association-rule characteristic Information Granule, which can be treated as a sub-definition of the Information Granule, and a association-rule characteristic Information Granularity matirx is...
The analysis on codon usage bias of UL26.5 gene of duck enteritis virus (DEV) may provide a basis for understanding the evolution and pathogenesis of DEV and for selecting appropriate host expression systems to improve the expression of target genes in vivo and in vitro. In this study, the synonymous codon usage in the UL26.5 gene of DEV and 27 reference herpesviruses have been investigated . The...
This article introduces the research on composite insulator of various degrees by using Fourier transform infrared spectroscopy (FTIR). The results show there is a close relationship between absorption areas of the functional group of Si-CH3 and Si-O-Si of silicone rubber shed and housing aging. Along with the severity of ageing in the appearance of composite insulator, the absorption areas of the...
This paper presents the development and application of an active disturbance rejection controller (ADRC) to regulate the frequency error for a three-area interconnected power system. As the interconnected power system transmits the power from one area to another, the system frequency will inevitably deviate from a scheduled frequency, resulting in a frequency error. A control system is essential to...
Botnets have been recognized as one of the most important threats to the Internet security. They are engaged in DDOS attacks, email spamming and other malicious activities likewise. Traditional botnets usually organized themselves in a hierarchy architecture, which offers professionals opportunities to detect or defend the botnets in their servers. However, newly-appeared P2P botnet such as Storm...
In this paper, a novel data driven knowledge extraction scheme is proposed and applied to realize power system stability estimation since power system stability assessment can be treated as a typical classification problem (stable/unstable). The strategy is composed of three cascading layers, including the feature selection for choosing an optimal subset from candidate inputs, pattern discovery layer...
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