Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Cost-effective outbreak detection in networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
SCAN: a structural clustering algorithm for networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Node roles and community structure in networks
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Spectral clustering in telephone call graphs
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Exploration of Link Structure and Community-Based Node Roles in Network Analysis
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Mining social networks using heat diffusion processes for marketing candidates selection
Proceedings of the 17th ACM conference on Information and knowledge management
An experimental study of large-scale mobile social network
Proceedings of the 18th international conference on World wide web
Efficient influence maximization in social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting influential nodes for information diffusion on a social network
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Efficient Algorithm for Computing Link-Based Similarity in Real World Networks
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
Tractable models for information diffusion in social networks
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Influential nodes in a diffusion model for social networks
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Finding influential mediators in social networks
Proceedings of the 20th international conference companion on World wide web
CIM: categorical influence maximization
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
Discovering shakers from evolving entities via cascading graph inference
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Active learning of model parameters for influence maximization
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
Data-driven modeling and analysis of online social networks
WAIM'11 Proceedings of the 12th international conference on Web-age information management
Group Profiling for Understanding Social Structures
ACM Transactions on Intelligent Systems and Technology (TIST)
In-time estimation for influence maximization in large-scale social networks
Proceedings of the Fifth Workshop on Social Network Systems
Finding influential seed successors in social networks
Proceedings of the 21st international conference companion on World Wide Web
Influence propagation and maximization for heterogeneous social networks
Proceedings of the 21st international conference companion on World Wide Web
Maximizing influence spread in a new propagation model
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
Proceedings of the 21st ACM international conference on Information and knowledge management
Cascade-based community detection
Proceedings of the sixth ACM international conference on Web search and data mining
CINEMA: conformity-aware greedy algorithm for influence maximization in online social networks
Proceedings of the 16th International Conference on Extending Database Technology
Supporting information spread in a social internetworking scenario
NFMCP'12 Proceedings of the First international conference on New Frontiers in Mining Complex Patterns
StaticGreedy: solving the scalability-accuracy dilemma in influence maximization
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Personalized influence maximization on social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Guide query in social networks
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Exploring celebrity dynamics on Twitter
Proceedings of the 5th IBM Collaborative Academia Research Exchange Workshop
Don't count the number of friends when you are spreading information in social networks
Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication
Preference-based mining of top-K influential nodes in social networks
Future Generation Computer Systems
High quality, scalable and parallel community detection for large real graphs
Proceedings of the 23rd international conference on World wide web
Affinity-driven blog cascade analysis and prediction
Data Mining and Knowledge Discovery
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With the proliferation of mobile devices and wireless technologies, mobile social network systems are increasingly available. A mobile social network plays an essential role as the spread of information and influence in the form of "word-of-mouth". It is a fundamental issue to find a subset of influential individuals in a mobile social network such that targeting them initially (e.g. to adopt a new product) will maximize the spread of the influence (further adoptions of the new product). The problem of finding the most influential nodes is unfortunately NP-hard. It has been shown that a Greedy algorithm with provable approximation guarantees can give good approximation; However, it is computationally expensive, if not prohibitive, to run the greedy algorithm on a large mobile network. In this paper we propose a new algorithm called Community-based Greedy algorithm for mining top-K influential nodes. The proposed algorithm encompasses two components: 1) an algorithm for detecting communities in a social network by taking into account information diffusion; and 2) a dynamic programming algorithm for selecting communities to find influential nodes. We also provide provable approximation guarantees for our algorithm. Empirical studies on a large real-world mobile social network show that our algorithm is more than an order of magnitudes faster than the state-of-the-art Greedy algorithm for finding top-K influential nodes and the error of our approximate algorithm is small.