Amanote Research

Amanote Research

    RegisterSign In

Efficiently Mining Long Patterns From Databases

SIGMOD Record - United States
doi 10.1145/276305.276313
Full Text
Open PDF
Abstract

Available in full text

Categories
Information SystemsSoftware
Date

June 1, 1998

Authors
Roberto J. Bayardo
Publisher

Association for Computing Machinery (ACM)


Related search

Mining Sequential Patterns More Efficiently by Reducing the Cost of Scanning Sequence Databases

IPSJ Digital Courier
2006English

Mining Topological Relationship Patterns From Spatiotemporal Databases

International Journal of Data Mining & Knowledge Management Process
2012English

Mining Viewpoint Patterns in Image Databases

2003English

Learning Trajectory Patterns by Sequential Pattern Mining From Probabilistic Databases

2018English

Efficiently Finding Arbitrarily Scaled Patterns in Massive Time Series Databases

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2003English

Mining Closed Sequential Patterns in Large Sequence Databases

International Journal of Database Management Systems
2015English

Mining Top-K Closed Sequential Patterns in Sequential Databases

IOSR Journal of Computer Engineering
2013English

Mining Probabilistic Frequent Spatio-Temporal Sequential Patterns With Gap Constraints From Uncertain Databases

2013English

Efficient Mining for Structurally Diverse Subgraph Patterns in Large Molecular Databases

Machine Learning
Artificial IntelligenceSoftware
2010English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy