2016 IEEE 32nd International Conference on Data Engineering (ICDE)

Influence maximization is a key problem in viral marketing. Given a social network G and a positive integer k, it aims to identify a seed set of k nodes in G that can maximize the expected influence spread in a certain propagation model. With the proliferation of geo-social networks, location-aware product promotion is becoming more necessary in real applications. However, the importance of the di... View full abstract»

Social curation services are emerging social media platforms that enable users to curate their contents according to the topic and express their interests at the topic level by following curated collections of other users' contents rather than the users themselves. The topic-level information revealed through this new feature far exceeds what existing methods solicit from the traditional social ne... View full abstract»

With regard to social network analysis, we concentrate on two widely-accepted building blocks: community detection and graph drawing. Although community detection and graph drawing have been studied separately, they have a great commonality, which means that it is possible to advance one field using the techniques of the other. In this paper, we propose a novel community detection algorithm for un... View full abstract»

We study the novel problem of revenue maximization of a social network host that sells viral marketing campaigns to multiple competing campaigners. Each client campaigner informs the social network host about her target users in the network, as well as how much money she is willing to pay to the host if one of her target users buys her product. The social network host, in turn, assigns a set of se... View full abstract»

With the rapid development of smartphones, spatial crowdsourcing platforms are getting popular. A foundational research of spatial crowdsourcing is to allocate micro-tasks to suitable crowd workers. Most existing studies focus on offline scenarios, where all the spatiotemporal information of micro-tasks and crowd workers is given. However, they are impractical since micro-tasks and crowd workers i... View full abstract»

Identifying the labels of points of interest (POIs), aka POI labelling, provides significant benefits in location-based services. However, the quality of raw labels manually added by users or generated by artificial algorithms cannot be guaranteed. Such low-quality labels decrease the usability and result in bad user experiences. In this paper, by observing that crowdsourcing is a best-fit for com... View full abstract»

As one of the three major steps (question design, task assignment, answer aggregation) in crowdsourcing, task assignment directly affects the quality of the crowdsourcing result. A good assignment will not only improve the answers' quality, but also boost the workers' willingness to participate. Although a lot of works have been made to produce better assignment, most of them neglected one of its ... View full abstract»

The paper studies two fundamental problems in graph analytics: computing Connected Components (CCs) and computing BiConnected Components (BCCs) of a graph. With the recent advent of Big Data, developing effcient distributed algorithms for computing CCs and BCCs of a big graph has received increasing interests. As with the existing research efforts, in this paper we focus on the Pregel programming ... View full abstract»

Graph coloring is a fundamental NP-hard problem in graph theory. It has a wide range of real applications, such as Operations Research, Communication Network, Computational Biology and Compiler Optimization. Notable efforts have been spent on designing its approximation algorithms. Halldrsson proposed the algorithm (denoted as SampleIS) with the current best known approximation ratio. However, its... View full abstract»

We present a new graph compressor that detects repeating substructures and represents them by grammar rules. We show that for a large number of graphs the compressor obtains smaller representations than other approaches. For RDF graphs and version graphs it outperforms the best known previous methods. Specific queries such as reachability between two nodes, can be evaluated in linear time over the... View full abstract»

Graph partitioning is an essential preprocessing step in distributed graph computation and scientific simulations. Existing well-studied graph partitioners are designed for static graphs, but real-world graphs, such as social networks and Web networks, keep changing dynamically. In fact, the communication and computation patterns of some graph algorithms may vary significantly, even across their d... View full abstract»

Core decomposition is a fundamental graph problem with a large number of applications. Most existing approaches for core decomposition assume that the graph is kept in memory of a machine. Nevertheless, many real-world graphs are big and may not reside in memory. In the literature, there is only one work for I/O efficient core decomposition that avoids loading the whole graph in memory. However, t... View full abstract»