Inverted files versus signature files for text indexing
ACM Transactions on Database Systems (TODS)
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Using Random Walks for Mining Web Document Associations
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Reachability and Distance Queries via 2-Hop Labels
SIAM Journal on Computing
Tracking Information Epidemics in Blogspace
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Dynamic personalized pagerank in entity-relation graphs
Proceedings of the 16th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Fast direction-aware proximity for graph mining
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Objectrank: authority-based keyword search in databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Fast incremental proximity search in large graphs
Proceedings of the 25th international conference on Machine learning
The structure of information pathways in a social communication network
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Query suggestion using hitting time
Proceedings of the 17th ACM conference on Information and knowledge management
Clustering via random walk hitting time on directed graphs
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Scalable proximity estimation and link prediction in online social networks
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
TEDI: efficient shortest path query answering on graphs
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
HyperANF: approximating the neighbourhood function of very large graphs on a budget
Proceedings of the 20th international conference on World wide web
Influential nodes in a diffusion model for social networks
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Hive open research network platform
Proceedings of the 16th International Conference on Extending Database Technology
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A graph neighborhood consists of a set of nodes that are nearby or otherwise related to each other. While existing definitions consider the structure (or topology) of the graph, we note that they fail to take into account the information propagation and diffusion characteristics, such as decay and reinforcement, common in many networks. In this paper, we first define the propagation efficiency of nodes and edges. We use this to introduce the novel concept of zero-erasure (or impact) neighborhood (ZEN) of a given node, n, consisting of the set of nodes that receive information from (or are impacted by) n without any decay. Based on this, we present an impact neighborhood indexing (INI) algorithm that creates data structures to help quickly identify impact neighborhood of any given node. Experiment results confirm the efficiency and effectiveness of the proposed INI algorithms.