Learn More
Community detection is a long-standing yet very difficult task in social network analysis. It becomes more challenging as many online social networking sites are evolving into super-large scales. Numerous methods have been proposed for community detection from massive networks, but how to reconcile the partitioning efficiency and the community quality(More)
Real world Web mining applications usually have different requirements, such as massive data processing, low system latency, and high scalability. In order to meet these different requirements, we proposed a distributed text mining system with a layered architecture that divides the system functions into three layers, namely, the crawling and storage layer,(More)
Probabilistic frequent pattern mining over uncertain data has received a great deal of attention recently due to the wide applications of uncertain data. Similar to its counterpart in deterministic databases, however, prob-abilistic frequent pattern mining suffers from the same problem of generating an exponential number of result patterns. The large number(More)
Mining probabilistic frequent patterns from uncertain data has received a great deal of attention in recent years due to the wide applications. However, probabilistic frequent pattern mining suffers from the problem that an exponential number of result patterns are generated, which seriously hinders further evaluation and analysis. In this paper, we focus(More)
BACKGROUND Cancer cells typically exhibit large-scale aberrant methylation of gene promoters. Some of the genes with promoter methylation alterations play "driver" roles in tumorigenesis, whereas others are only "passengers". RESULTS Based on the assumption that promoter methylation alteration of a driver gene may lead to expression alternation of a set(More)
In this paper, multi-robot map building problem in a complex and unknown environment is investigated, and a map building approach is presented based on particle swarm optimization algorithm for global optimization, as well as Hilbert curve on the target region detection of multi-robot cooperative. Particle Swarm Optimization has characteristics of(More)
While agreement-based joint training has proven to deliver state-of-the-art alignment accuracy, the produced word alignments are usually restricted to one-to-one mappings because of the hard constraint on agreement. We propose a general framework to allow for arbitrary loss functions that measure the disagreement between asymmetric alignments. The loss(More)