Automatic Subspace Clustering of High Dimensional Data

By Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan. Data mining and knowledge discovery, 2005

404 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/22b1ca1ccfa94e247b357544772fbf18aedcfb49

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Vipin Kumar
2. Aleksandar Lazarevic
3. Kevin Fu
4. David E. Irwin
5. Charu C. Aggarwal
6. Arthur Zimek
7. Longin Jan Latecki
8. Dragoljub Pokrajac

In Information Systems

1. Aleksandar Lazarevic
2. Vipin Kumar
3. Bamshad Mobasher
4. David Sculley

In Signal Processing

1. Kevin Fu
2. David E. Irwin
3. Aleksandar Lazarevic
4. Vipin Kumar

Citations in the corpus

• Private memoirs of a smart meter (2010, background): “Entities that gather large amounts of data would potentially be able to predict even more detailed facts, such as residents genders and ages.”
• Feature bagging for outlier detection (2005, background): “It has been shown recently that by examining the behavior of the data in subspaces, it is possible to develop more effective algorithms for cluster discovery [28] and similarity search in high dimensional spaces [1, 2, 4].”