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To solve the class imbalance problem in classification of pre-miRNAs with ab initio method, a novel sample selection method is proposed according to the characteristics of pre-miRNAs. Real/pseudo pre-miRNAs are clustered based on their stem similarity and their distribution in high dimensional sample space respectively. The training samples are selected according to the sample density of each cluster...
The investigation of community structures in networks is an important issue in many domains and disciplines. However, Most of the present algorithms consider only structure of the network, ignoring some additional conditions such as direction, weight, semantic, etc. In this paper the behaviors of each vertex are focus. Based on the previous work, two limitations of swarm similarity in closely community...
System anomaly detection is very important for development, maintenance and performance refinement in large scale distributed systems. It's a good way to obtain the troubleshooting and problem diagnosis by analyzing system logs produced by distributed systems. However, due to the increasing scale and complexity of distributed systems, the size of logs must be very large. Thus, it's inefficient for...
Emails play an important role in our daily life. It has been recognized that clustering emails into meaningful groups can greatly save cognitive load to process emails. Mailbox user becomes more and more concerned about how to organize and manage the emails as well as how to mine the meaningful data conveniently and effectively. This paper proposes a novel personal topics detection approach using...
The investigation of community structures in networks is an important issue in many domains and disciplines.Closely communicating community is different from the traditional community which emphasize particularly on structure or context. The definition of closely communicating community and measuring method are introduced firstly. Based on the previous work, the closely communicating community detection...
Rare category detection is the task of identifying examples from rare classes in an unlabeled data set. It is an open challenge in machine learning and plays key roles in real applications such as financial fraud detection, network intrusion detection, astronomy, spam image detection, etc. In this paper, we develop a new graph-based method for rare category detection named GRADE. It makes use of the...
Rushes editing, which enables the computer to edit the film like a professional film cutter based on the noisy and redundant footage, is an active topic in multimedia semantic analysis. The most critical problem of rushes editing is how to generate an effective, efficient, and robust descriptor for the footage content analysis. This paper proposes a novel non-linear dimensionality reduction algorithm...
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