Automatic text processing
Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Discover Risky Active Faults by Indexing an Earthquake Sequence
DS '99 Proceedings of the Second International Conference on Discovery Science
KeyGraph: Automatic Indexing by Co-occurrence Graph based on Building Construction Metaphor
ADL '98 Proceedings of the Advances in Digital Libraries Conference
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Experimental study of discovering essential information from customer inquiry
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Approach to Detection of Community's Consensus and Interest
Advanced Web and NetworkTechnologies, and Applications
S-node: A Small-World Navigation System for Exploratory Search
AIRS '09 Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
Query Expansion Based on Query Log and Small World Characteristic
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
Automatic keyphrases extraction from document using neural network
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
iChance: A Web-Based Innovation Support System for Business Intelligence
International Journal of Organizational and Collective Intelligence
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The small world topology is known widespread in biological, social and man-made systems. This paper shows that the small world structure also exists in documents, such as papers. A document is represented by a network; the nodes represent terms, and the edges represent the co-occurrence of terms. This network is shown to have the characteristics of being a small world, i.e., nodes are highly clustered yet the path length between them is small. Based on the topology, we develop an indexing system called KeyWorld, which extracts important terms by measuring their contribution to the graph being small world.