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We consider the problem of discovering association rules between items in a large database of sales transactions. We present t wo new algorithms for solving this problem that are fundamentally diierent from the known algorithms. Empirical evaluation shows that these algorithms outperform the known algorithms by factors ranging from three for small problems… (More)

- Rakesh Agrawal, Ramakrishnan Srikant
- VLDB
- 1994

- Rakesh Agrawal, Ramakrishnan Srikant
- ICDE
- 1995

We are given a large database of customer transactions , where each transaction consists of customer-id, transaction time, and the items bought in the transaction. We i n troduce the problem of mining sequential patterns over such databases. We present three algorithms to solve this problem, and empirically evaluate their performance using synthetic data.… (More)

- Ramakrishnan Srikant, Rakesh Agrawal
- EDBT
- 1996

The problem of mining sequential patterns was recently introduced in 3]. We are given a database of sequences, where each sequence is a list of transactions ordered by transaction-time, and each transaction is a set of items. The problem is to discover all sequential patterns with a user-speciied minimum support, where the support of a pattern is the number… (More)

- Rakesh Agrawal, Heikki Mannila, Ramakrishnan Srikant, Hannu Toivonen, A. Inkeri Verkamo
- Advances in Knowledge Discovery and Data Mining
- 1996

- Rakesh Agrawal, Ramakrishnan Srikant
- SIGMOD Conference
- 2000

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 aggregated data, can we develop accurate models without access to precise information in individual data… (More)

Given a large collection of sparse vector data in a high dimensional space, we investigate the problem of finding all pairs of vectors whose similarity score (as determined by a function such as cosine distance) is above a given threshold. We propose a simple algorithm based on novel indexing and optimization strategies that solves this problem without… (More)

- Rakesh Agrawal, Jerry Kiernan, Ramakrishnan Srikant, Yirong Xu
- SIGMOD Conference
- 2004

Encryption is a well established technology for protecting sensitive data. However, once encrypted, data can no longer be easily queried aside from exact matches. We present an order-preserving encryption scheme for numeric data that allows any comparison operation to be directly applied on encrypted data. Query results produced are sound (no false hits)… (More)

- Usama M. Fayyad, Padhraic Smyth, +22 authors Martin L. Kersten
- 1996

- Ramakrishnan Srikant, Rakesh Agrawal
- SIGMOD Conference
- 1996

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 cars". We deal with quantitative attributes by fine-partitioning the values of the attribute and then combining… (More)