Microsoft Research, Mountain View, CA, USA
Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami
993 ACM SIGMOD International Conference on Management of Data, 1993 – SIGMOD
We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an efficient algorithm that generates all significant association rules between items in the database. The ...
Rakesh Agrawal, Ramakrishnan Srikant
VLDB'94, Proceedings of 20th International Conference on Very Large Data Bases, 1994 – VLDB
We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally different from the known algorithms. Empirical evaluation ...
Rakesh Agrawal, Ramakrishnan Srikant
2000 ACM SIGMOD International Conference on Management of Data, 2000 – SIGMOD
A fruitful direction for future data mining research will be the development of techniques that incorporate privacy concerns. Specifically, we address the following question. Since the primary task in data mining is the development of models about ...
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan
1998 ACM SIGMOD International Conference on Management of Data, 1998 – SIGMOD
Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in subspaces of high dimensional data, scalability, end-user comprehensibility of the results, non-presumption of any ...
Rakesh Agrawal, Christos Faloutsos, Arun N. Swami
Foundations of Data Organization and Algorithms, 4th International Conference, FODO'93, vol. 730,1993 – FODO
. We propose an indexing method for time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT) to map time sequences to the frequency domain, the crucial observation being that, for most sequences of practical ...
Rakesh Agrawal, Ramakrishnan Srikant
ACM SIGMOD International Conference on Management of Data, vol. 29,no. 2,Jun/2000 – SIGMOD
A fruitful direction for future data mining research will be the development of techniques that incorporate privacy concerns. Specifically, we address the following question. Since the primary task in data mining is the development of models about ...
Rakesh Agrawal, Sakti P. Ghosh, Tomasz Imielinski, Balakrishna R. Iyer, Arun N. Swami
18th International Conference on Very Large Data Bases, 1992 – VLDB
We are given a large population database that contains information about population instances. The population is known to comprise of m groups, but the population instances are not labeled with the group identification. Also given is a population ...
Ramakrishnan Srikant, Rakesh Agrawal
1996 ACM SIGMOD International Conference on Management of Data, 1996 – SIGMOD
We introduce the problem of mining association rules in large relational tables containing both quantitative and categorical attributes. An example of such an association might be "10% of married people between age 50 and 60 have at least 2 ...
Ramakrishnan Srikant, Rakesh Agrawal
VLDB'95, Proceedings of 21th International Conference on Very Large Data Bases, 1995 – VLDB
We introduce the problem of mining generalized association rules. Given a large database of transactions, where each transaction consists of a set of items, and a taxonomy (is-a hierarchy) on the items, we find associations between items at any level ...
Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami
IEEE Transactions on Knowledge and Data Engineering, vol. 5,no. 6,1993 – TKDE
The authors' perspective of database mining as the confluence of machine learning techniques and the performance emphasis of database technology is presented. Three classes of database mining problems involving classification, associations, and ...