247 search results - page 44 / 50 » Efficient similarity search for market basket data |
KDD
2008
ACM
14 years 7 months ago
2008
ACM
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
KDD
2009
ACM
14 years 7 months ago
2009
ACM
The discovery of biclusters, which denote groups of items that show coherent values across a subset of all the transactions in a data set, is an important type of analysis perform...
KDD
2006
ACM
14 years 7 months ago
2006
ACM
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
ITSL
2008
13 years 8 months ago
2008
Clustering can be defined as a data assignment problem where the goal is to partition the data into nonhierarchical groups of items. In our previous work, we suggested an informati...
ECCV
2010
Springer
14 years 8 days ago
2010
Springer
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...