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A significant amount of data are significantly available due to the dramatic proliferation of location-based social networks. This has led to the development of location-based recommendation tools that assist users in discovering attractive Points-...

The dramatic proliferation of location-based social networks have resulted in a significant amount of data. This has led to the development of location-based recommendation tools that assist users in discovering attractive Points-of-Interest (POIs)...

Efficient graph partitioning is vital for high-performance graph-parallel systems. Traditional graph partitioning methods attempt to both minimize communication cost and guarantee load balancing in computation. However, the skewed degree distribution of ...

With the rapid development of GPS-enabled mobile devices, huge amounts of user-contributed data with location information can be collected from the Internet. With this kind of data, one promising application is travel recommendation, which has attracted ...

In our increasingly mobile world the ability to access information on demand at any time and place can satisfy people's information needs as well as confer on them a competitive advantage. The emergence of battery-operated, low-cost and portable ...

Social Networking Sites (SNSs) allow users to publish posts to certain user-defined circles (sets of users). However, existing SNS models are limited in several ways. First, it is not practical to predefine all circles a user will ever need for ...

In data publishing, the owner delegates the role of satisfying user queries to a third-party publisher. As the servers of the publisher may be untrusted or susceptible to attacks, we cannot assume that they would always process queries correctly, hence ...

Hadoop, an open-source implementation of Map-Reduce, has been widely used for data-intensive computing. In order to improve performance, multiple jobs operating on a common data file can be processed as a batch to eliminate redundant scanning. However, ...

In this paper, we propose CYBER, a CommunitY Based sEaRch engine, for information retrieval utilizing community feedback information in a DHT network. In CYBER, each user is associated with a set of user profiles that capture his/her interests. Likewise,...

This paper addresses the problem of finding frequent closed patterns (FCPs) from very dense datasets. We introduce two compressed hierarchical FCP mining algorithms C-Miner and B-Miner. The two algorithms compress the original mining space, ...

Peer-to-Peer (P2P) systems have attracted much attention in academic community and industry circles due to their promising applications in various domains. This paper presents the authors' research efforts on introducing complex query capabilities ...