Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Resolution principles in possibilistic logic
International Journal of Approximate Reasoning
The design and analysis of algorithms
The design and analysis of algorithms
Theory of generalized annotated logic programming and its applications
Journal of Logic Programming
A theory of nonmonotonic inheritance based on annotated logic
Artificial Intelligence
Probabilistic logic programming
Information and Computation
A logic for reasoning with inconsistency
Journal of Automated Reasoning
The complexity of logic-based abduction
Journal of the ACM (JACM)
On the hardness of approximate reasoning
Artificial Intelligence
A non-ground realization of the stable and well-founded semantics
Theoretical Computer Science
A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Tabling for non-monotonic programming
Annals of Mathematics and Artificial Intelligence
Computing Non-Ground Representations of Stable Models
LPNMR '97 Proceedings of the 4th International Conference on Logic Programming and Nonmonotonic Reasoning
Coherent Well-founded Annotated Logic Programs
LPNMR '99 Proceedings of the 5th International Conference on Logic Programming and Nonmonotonic Reasoning
Annotated Constraint Logic Programming Applied to Temporal Reasoning
PLILP '94 Proceedings of the 6th International Symposium on Programming Language Implementation and Logic Programming
A Brief Overview of Possibilistic Logic
ECSQAU Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Temporal Annotated Constraint Logic Programming with Multiple Theories
DEXA '99 Proceedings of the 10th International Workshop on Database & Expert Systems Applications
First order heterogeneous agent computations
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Optimal Models of Disjunctive Logic Programs: Semantics, Complexity, and Computation
IEEE Transactions on Knowledge and Data Engineering
Combining probabilistic logic programming with the power of maximum entropy
Artificial Intelligence - Special issue on nonmonotonic reasoning
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
The dynamics of viral marketing
ACM Transactions on the Web (TWEB)
Principles of Constraint Programming
Principles of Constraint Programming
On the submodularity of influence in social networks
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Cost-effective outbreak detection in networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Annals of Mathematics and Artificial Intelligence
Characterizing social cascades in flickr
Proceedings of the first workshop on Online social networks
The convergence of social and technological networks
Communications of the ACM - Remembering Jim Gray
AVA: Adjective-Verb-Adverb Combinations for Sentiment Analysis
IEEE Intelligent Systems
Discrete Applied Mathematics
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
ProbLog: a probabilistic prolog and its application in link discovery
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
On the Approximability of Influence in Social Networks
SIAM Journal on Discrete Mathematics
Predicting positive and negative links in online social networks
Proceedings of the 19th international conference on World wide web
The independent choice logic and beyond
Probabilistic inductive logic programming
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Chr(prism)-based probabilistic logic learning
Theory and Practice of Logic Programming
Tabling with answer subsumption: implementation, applications and performance
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
A Scalable Framework for Modeling Competitive Diffusion in Social Networks
SOCIALCOM '10 Proceedings of the 2010 IEEE Second International Conference on Social Computing
Hybrid probabilistic programs: algorithms and complexity
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Generalising the interaction rules in probabilistic logic
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
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There has been extensive work in many different fields on how phenomena of interest (e.g., diseases, innovation, product adoption) “diffuse” through a social network. As social networks increasingly become a fabric of society, there is a need to make “optimal” decisions with respect to an observed model of diffusion. For example, in epidemiology, officials want to find a set of k individuals in a social network which, if treated, would minimize spread of a disease. In marketing, campaign managers try to identify a set of k customers that, if given a free sample, would generate maximal “buzz” about the product. In this article, we first show that the well-known Generalized Annotated Program (GAP) paradigm can be used to express many existing diffusion models. We then define a class of problems called Social Network Diffusion Optimization Problems (SNDOPs). SNDOPs have four parts: (i) a diffusion model expressed as a GAP, (ii) an objective function we want to optimize with respect to a given diffusion model, (iii) an integer k 0 describing resources (e.g., medication) that can be placed at nodes, (iv) a logical condition VC that governs which nodes can have a resource (e.g., only children above the age of 5 can be treated with a given medication). We study the computational complexity of SNDOPs and show both NP-completeness results as well as results on complexity of approximation. We then develop an exact and a heuristic algorithm to solve a large class of SNDOPproblems and show that our GREEDY-SNDOPs algorithm achieves the best possible approximation ratio that a polynomial algorithm can achieve (unless P = NP). We conclude with a prototype experimental implementation to solve SNDOPs that looks at a real-world Wikipedia dataset consisting of over 103,000 edges.