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The similarity search is one of the fundamental components in time series data mining, e.g. clustering, classification, association rules mining. Many methods have been proposed to measure the similarity between time series, including Euclidean distance, Manhattan distance, and dynamic time warping (DTW). In contrast, DTW has been suggested to allow more robust similarity measure and be able to find...
Social media networks are playing increasingly prominent role in people’s daily life. Community structure is one of the salient features of social media network and has been applied to practical applications, such as recommendation system and network marketing. With the rapid expansion of social media size and surge of tremendous amount of information, how to identify the communities in big data scenarios...
Social networks have been part of people's daily life and plenty of users have registered accounts in multiple social networks. Interconnections among multiple social networks add a multiplier effect to social applications when fully used. With the sharp expansion of network size, traditional standalone algorithms can no longer support computing on large scale networks while alternatively, distributed...
MapReduce is an important programming paradigm on big data-intensive computing using share-nothing cluster containing ten of thousands of nodes, in which computing nodes also acts as storage nodes. Since tasks belonging to different jobs are physical executing entities scattered among the whole cluster, task scheduling plays a crucial role in MapReduce systems. For data consolidation and utilization,...
Scheduling algorithms place a crucial role in MapReduce systems. Several recent scheduling algorithms, however, are all under Job-Task scheduling model which makes task scheduling confined, leading to poor task scheduling preference such as data locality, scan sharing and etc. These characteristics are very important heuristics on data intensive computing and helpful in improving system throughput...
In recent years, MapReduce parallel computing model has gained lots of attentions from industry and academia. In Google, Yahoo, Facebook, etc., it has played a very good effect, which greatly simplifies the design of large-scale data-intensive applications. MapReduce-based systems were originally used to manage massive unstructured and semi-structured data, for example: to generate the inverted index,...
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