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» Approximate data mining in very large relational data
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WSDM
2009
ACM
198views Data Mining» more  WSDM 2009»
15 years 8 months ago
Measuring the similarity between implicit semantic relations using web search engines
Measuring the similarity between implicit semantic relations is an important task in information retrieval and natural language processing. For example, consider the situation whe...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...
PPOPP
2010
ACM
15 years 11 months ago
A distributed placement service for graph-structured and tree-structured data
Effective data placement strategies can enhance the performance of data-intensive applications implemented on high end computing clusters. Such strategies can have a significant i...
Gregory Buehrer, Srinivasan Parthasarathy, Shirish...
CIKM
2005
Springer
15 years 7 months ago
Opportunity map: a visualization framework for fast identification of actionable knowledge
Data mining techniques frequently find a large number of patterns or rules, which make it very difficult for a human analyst to interpret the results and to find the truly interes...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Weimin Xia...
SIGCOMM
2006
ACM
15 years 7 months ago
Beyond bloom filters: from approximate membership checks to approximate state machines
Many networking applications require fast state lookups in a concurrent state machine, which tracks the state of a large number of flows simultaneously. We consider the question ...
Flavio Bonomi, Michael Mitzenmacher, Rina Panigrah...
SDM
2011
SIAM
269views Data Mining» more  SDM 2011»
14 years 4 months ago
Semi-Supervised Convolution Graph Kernels for Relation Extraction
Extracting semantic relations between entities is an important step towards automatic text understanding. In this paper, we propose a novel Semi-supervised Convolution Graph Kerne...
Xia Ning, Yanjun Qi