Pamalla Veena

According to our database, Pamalla Veena authored at least 16 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Efficient Discovery of Fuzzy Partial Periodic Frequent Patterns Within Quantitative Temporal Databases.

Pamalla Veena, Vanitha Kattumuri, Yutaka Watanobe, Deepika Saxena

IEEE Trans. Fuzzy Syst., August, 2025

A Novel Depth-First Search Algorithm for Partial Periodic-Frequent Pattern Mining in Temporal Databases.

Pamalla Veena, Vanitha Kattumuri, Yutaka Watanobe, Rage Uday Kiran, So Nakamura, Palla Likhitha, Koji Zettsu

IEEE Access, 2025

2024

3P-ECLAT: mining partial periodic patterns in columnar temporal databases.

Pamalla Veena, Rage Uday Kiran, Penugonda Ravikumar, Likhitha Palla, Yutaka Watanobe, Sadanori Ito, Koji Zettsu, Masashi Toyoda, Bathala Venus Vikranth Raj

Appl. Intell., January, 2024

PAMI: An Open-Source Python Library for Pattern Mining.

Rage Uday Kiran, Pamalla Veena, Masashi Toyoda, Masaru Kitsuregawa

J. Mach. Learn. Res., 2024

Fuzzy Partial Periodic Frequent Pattern Mining in Quantitative Temporal Databases.

Pamalla Veena, Vanitha Kattumuri, Yutaka Watanobe, Deepika Saxena

Proceedings of the Neural Information Processing - 31st International Conference, 2024

2023

A fundamental approach to discover closed periodic-frequent patterns in very large temporal databases.

Pamalla Veena, Rage Uday Kiran, Penugonda Ravikumar, Likhitha Palla, Yuto Hayamizu, Kazuo Goda, Masashi Toyoda, Koji Zettsu, Sourabh Shrivastava

Appl. Intell., November, 2023

HDSHUI-miner: a novel algorithm for discovering spatial high-utility itemsets in high-dimensional spatiotemporal databases.

Rage Uday Kiran, Pamalla Veena, Penugonda Ravikumar, Bathala Venus Vikranth Raj, Minh-Son Dao, Koji Zettsu, Sai Chithra Bommisetti

Appl. Intell., April, 2023

Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set Complements.

Pamalla Veena, Sreepada Tarun, Rage Uday Kiran, Minh-Son Dao, Koji Zettsu, Yutaka Watanobe, Ji Zhang

IEEE Access, 2023

Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases.

Palla Likhitha, Pamalla Veena, Rage Uday Kiran, Koji Zettsu

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Discovering Fuzzy Partial Periodic Patterns in Quantitative Irregular Multiple Time Series.

Pamalla Veena, Palla Likhitha, R. Uday Kiran, José María Luna, Philippe Fournier-Viger, Koji Zettsu

Proceedings of the IEEE International Conference on Fuzzy Systems, 2023

2022

Discovering Fuzzy Geo-referenced Periodic-Frequent Patterns in Geo-referenced Time Series Databases.

Pamalla Veena, Penugonda Ravikumar, Kundai Kwangwari, R. Uday Kiran, Kazuo Goda, Yutaka Watanobe, Koji Zettsu

Proceedings of the IEEE International Conference on Fuzzy Systems, 2022

Towards Efficient Discovery of Periodic-Frequent Patterns in Dense Temporal Databases Using Complements.

Pamalla Veena, Sreepada Tarun, R. Uday Kiran, Minh-Son Dao, Koji Zettsu, Yutaka Watanobe, Ji Zhang

Proceedings of the Database and Expert Systems Applications, 2022

2021

A Unified Framework to Discover Partial Periodic-Frequent Patterns in Row and Columnar Temporal Databases.

Pamalla Veena, So Nakamura, Palla Likhitha, R. Uday Kiran, Yutaka Watanobe, Koji Zettsu

Proceedings of the 2021 International Conference on Data Mining, 2021

Discovering Fuzzy Frequent Spatial Patterns in Large Quantitative Spatiotemporal databases.

Pamalla Veena, Sai Chithra Bommisetty, R. Uday Kiran, Sonali Agarwal, Koji Zettsu

Proceedings of the 30th IEEE International Conference on Fuzzy Systems, 2021

Discovering Top-k Spatial High Utility Itemsets in Very Large Quantitative Spatiotemporal databases.

Pradeep Pallikila, Pamalla Veena, R. Uday Kiran, Ram Avatar, Sadanori Ito, Koji Zettsu, P. Krishna Reddy

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Discovering Maximal Partial Periodic Patterns in Very Large Temporal Databases.

Palla Likhitha, Pamalla Veena, R. Uday Kiran, Yutaka Watanobe, Koji Zettsu

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021