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2020 – today
- 2024
[j28]Vanitha Kattumuri
, Rage Uday Kiran, Shota Suzuki:
Discovering Spatially Interesting Patterns in Big Geo-Referenced Sequential Databases. IEEE Access 12: 169404-169418 (2024)- [j27]Pamalla Veena, Rage Uday Kiran, Penugonda Ravikumar, Likhitha Palla, Yutaka Watanobe, Sadanori Ito, Koji Zettsu, Masashi Toyoda, Bathala Venus Vikranth Raj:
3P-ECLAT: mining partial periodic patterns in columnar temporal databases. Appl. Intell. 54(11-12): 657-679 (2024) - [j26]Rage Uday Kiran, Pamalla Veena, Masashi Toyoda, Masaru Kitsuregawa:
PAMI: An Open-Source Python Library for Pattern Mining. J. Mach. Learn. Res. 25: 209:1-209:6 (2024) - [j25]Ji Zhang, Qiliang Liang, Mohamed Jaward Bah, Hongzhou Li, Liang Chang, Rage Uday Kiran:
Discriminative boundary generation for effective outlier detection. Knowl. Inf. Syst. 66(5): 2987-3004 (2024) - [c100]Zenghui Xu, Mingzhang Li, Ting Yu, Linlin Hou, Peng Zhang, Rage Uday Kiran, Zhao Li, Ji Zhang:
A Novel Multi-scale Spatiotemporal Graph Neural Network for Epidemic Prediction. DEXA (2) 2024: 272-287 - [c99]R. Uday Kiran, Abinash Maharana, Makiko Ohtake, Yoshiko Ogawa:
Towards Addressing an Open Problem in Coupled Matrix Tensor Factorization for Satellite Imagery Data Using Human-in-Loop. IEA/AIE 2024: 265-276 - [c98]Kazuki Tejima, Deepika Saxena, Rage Uday Kiran:
A Novel Multi-task Single-Step Traffic Congestion Forecasting Framework for Large-Scale Road Networks. IEA/AIE 2024: 277-288 - [c97]Minh-Son Dao, Michael Alexander Riegler, Duc-Tien Dang-Nguyen, Hanh-Nhi Tran, Rage Uday Kiran, Takahiro Komamizu:
ICDAR 24: Intelligent Cross-Data Analysis and Retrieval. ICMR 2024: 1332-1333 - [e6]Minh-Son Dao, Michael Alexander Riegler, Duc-Tien Dang-Nguyen, Hanh-Nhi Tran, Rage Uday Kiran, Takahiro Komamizu:
The Fifth Workshop on Intelligent Cross-Data Analysis and Retrieval, ICDAR 2024, Phuket, Thailand, June 10-14, 2024. ACM 2024 [contents] - 2023
- [j24]Hong N. Dao, Penugonda Ravikumar, Palla Likhitha, Rage Uday Kiran, Yutaka Watanobe, Incheon Paik:
Finding Stable Periodic-Frequent Itemsets in Big Columnar Databases. IEEE Access 11: 12504-12524 (2023) - [j23]Juan Xiao, Ashwani Kumar Aggarwal, Rage Uday Kiran, Vaibhav Katiyar, Ram Avtar:
Deep Learning-Based Spatiotemporal Fusion of Unmanned Aerial Vehicle and Satellite Reflectance Images for Crop Monitoring. IEEE Access 11: 85600-85614 (2023) - [j22]Pamalla Veena, Sreepada Tarun, Rage Uday Kiran, Minh-Son Dao, Koji Zettsu, Yutaka Watanobe, Ji Zhang:
Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set Complements. IEEE Access 11: 118676-118688 (2023) - [j21]Palla Likhitha, Penugonda Ravikumar, Deepika Saxena, Rage Uday Kiran, Yutaka Watanobe:
k-PFPMiner: Top-k Periodic Frequent Patterns in Big Temporal Databases. IEEE Access 11: 119033-119044 (2023) - [j20]Phuc-Thinh Nguyen, Minh-Son Dao, Michael A. Riegler, Rage Uday Kiran, Thai-Thinh Dang, Duy-Dong Le, Kieu-Chinh Nguyen-Ly, Thanh-Qui Pham, Van-Luong Nguyen:
Training Performance Indications for Amateur Athletes Based on Nutrition and Activity Lifelogs. Algorithms 16(1): 30 (2023) - [j19]Rage Uday Kiran, Pamalla Veena, Penugonda Ravikumar, Bathala Venus Vikranth Raj, Minh-Son Dao, Koji Zettsu, Sai Chithra Bommisetti:
HDSHUI-miner: a novel algorithm for discovering spatial high-utility itemsets in high-dimensional spatiotemporal databases. Appl. Intell. 53(8): 8536-8561 (2023) - [j18]Pamalla Veena, Rage Uday Kiran, Penugonda Ravikumar, Likhitha Palla, Yuto Hayamizu, Kazuo Goda, Masashi Toyoda, Koji Zettsu, Sourabh Shrivastava:
A fundamental approach to discover closed periodic-frequent patterns in very large temporal databases. Appl. Intell. 53(22): 27344-27373 (2023) - [j17]José María Luna, Rage Uday Kiran, Philippe Fournier-Viger, Sebastián Ventura:
Efficient mining of top-k high utility itemsets through genetic algorithms. Inf. Sci. 624: 529-553 (2023) - [c96]Palla Likhitha, Rage Uday Kiran:
Discovering Top-K Partial Periodic Patterns in Big Temporal Databases. DEXA (1) 2023: 352-357 - [c95]Pamalla Veena, Palla Likhitha, R. Uday Kiran, José María Luna, Philippe Fournier-Viger, Koji Zettsu:
Discovering Fuzzy Partial Periodic Patterns in Quantitative Irregular Multiple Time Series. FUZZ 2023: 1-7 - [c94]Genki Kimura, Yuto Hayamizu, Rage Uday Kiran, Masaru Kitsuregawa, Kazuo Goda:
Efficient Parallel Mining of High-utility Itemsets on Multicore Processors. ICDE 2023: 638-652 - [c93]Genki Kimura, Yuto Hayamizu, Rage Uday Kiran, Masaru Kitsuregawa, Kazuo Goda:
Efficient Parallel Mining of High-utility Itemsets on Multicore Processors. ICDE 2023: 3563-3577 - [c92]Vipul Chhabra, Rage Uday Kiran, Abinash Maharana, Juan Xiao, Krishna Reddy Polepalli, Ram Avtar, Yoshiko Ogawa, Makiko Ohtake:
A Novel Parallel Spatiotemporal Image Fusion Method for Predicting High-Resolution Satellite Images. IEA/AIE (1) 2023: 133-144 - [c91]Palla Likhitha, Pamalla Veena, Rage Uday Kiran, Koji Zettsu:
Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases. PAKDD (3) 2023: 29-41 - [c90]Rage Uday Kiran, Abinash Maharana, Krishna Reddy Polepalli:
A Novel Explainable Link Forecasting Framework for Temporal Knowledge Graphs Using Time-Relaxed Cyclic and Acyclic Rules. PAKDD (1) 2023: 264-275 - [c89]Shota Suzuki, Rage Uday Kiran:
Towards Efficient Discovery of Spatially Interesting Patterns in Geo-referenced Sequential Databases. SSDBM 2023: 9:1-9:11 - 2022
- [j16]Md. Mostafizer Rahman, Yutaka Watanobe, Taku Matsumoto, Rage Uday Kiran, Keita Nakamura:
Educational Data Mining to Support Programming Learning Using Problem-Solving Data. IEEE Access 10: 26186-26202 (2022) - [j15]Philippe Fournier-Viger, Ying Wang, Peng Yang, Jerry Chun-Wei Lin, Unil Yun, Rage Uday Kiran:
TSPIN: mining top-k stable periodic patterns. Appl. Intell. 52(6): 6917-6938 (2022) - [j14]Yutaka Watanobe, Md. Mostafizer Rahman, Taku Matsumoto, Rage Uday Kiran, Penugonda Ravikumar:
Online Judge System: Requirements, Architecture, and Experiences. Int. J. Softw. Eng. Knowl. Eng. 32(6): 917-946 (2022) - [c88]Penugonda Ravikumar, Bathala Venus Vikranth Raj, Palla Likhitha, Rage Uday Kiran, Yutaka Watanobe, Sadanori Ito, Koji Zettsu, Masashi Toyoda:
Towards Efficient Discovery of Partial Periodic Patterns in Columnar Temporal Databases. ACIIDS (2) 2022: 141-154 - [c87]Palla Likhitha, Penugonda Ravikumar, Rage Uday Kiran, Yutaka Watanobe:
Discovering Top-k Periodic-Frequent Patterns in Very Large Temporal Databases. BDA 2022: 200-210 - [c86]Sreepada Tarun, Rage Uday Kiran, Yutaka Watanobe, Kazuo Goda:
A Novel GPU-Accelerated Algorithm to Discover Periodic-Frequent Patterns in Temporal Databases. IEEE Big Data 2022: 121-126 - [c85]R. Uday Kiran, Vipul Chhabra, Saideep Chennupati, P. Krishna Reddy, Minh-Son Dao, Koji Zettsu:
A Novel Null-Invariant Temporal Measure to Discover Partial Periodic Patterns in Non-uniform Temporal Databases. DASFAA (1) 2022: 569-577 - [c84]Qiliang Liang, Ji Zhang, Mohamed Jaward Bah, Hongzhou Li, Liang Chang, Rage Uday Kiran:
Effective and Robust Boundary-Based Outlier Detection Using Generative Adversarial Networks. DEXA (2) 2022: 174-187 - [c83]Pamalla Veena, Sreepada Tarun, R. Uday Kiran, Minh-Son Dao, Koji Zettsu, Yutaka Watanobe, Ji Zhang:
Towards Efficient Discovery of Periodic-Frequent Patterns in Dense Temporal Databases Using Complements. DEXA (2) 2022: 204-215 - [c82]Penugonda Ravikumar, R. Uday Kiran, Palla Likhitha, T. Chandrasekhar, Yutaka Watanobe, Koji Zettsu:
Discovering Geo-referenced Periodic-Frequent Patterns in Geo-referenced Time Series Databases. DSAA 2022: 1-10 - [c81]Pamalla Veena, Penugonda Ravikumar, Kundai Kwangwari, R. Uday Kiran, Kazuo Goda, Yutaka Watanobe, Koji Zettsu:
Discovering Fuzzy Geo-referenced Periodic-Frequent Patterns in Geo-referenced Time Series Databases. FUZZ-IEEE 2022: 1-8 - [c80]Palla Likhitha, Rage Uday Kiran:
Towards developing energy efficient algorithms to discover partial periodic patterns in big temporal databases. SIGSPATIAL/GIS 2022: 110:1-110:2 - [c79]Palla Likhitha, Rage Veena, Rage Uday Kiran, Koji Zettsu, Masashi Toyoda, Philippe Fournier-Viger:
UPFP-growth++: An Efficient Algorithm to Find Periodic-Frequent Patterns in Uncertain Temporal Databases. ICONIP (5) 2022: 182-194 - [c78]Vipul Chhabra, R. Uday Kiran, Juan Xiao, P. Krishna Reddy, Ram Avtar:
A Spatiotemporal Image Fusion Method for Predicting High-Resolution Satellite Images. IEA/AIE 2022: 470-481 - [c77]Hong N. Dao, Penugonda Ravikumar, Palla Likhitha, Bathala Venus Vikranth Raj, R. Uday Kiran, Yutaka Watanobe, Incheon Paik:
Towards Efficient Discovery of Stable Periodic Patterns in Big Columnar Temporal Databases. IEA/AIE 2022: 831-843 - [c76]Truong Cong Thang, Yutaka Watanobe, Rage Uday Kiran, Incheon Paik:
Towards QoE Management for Post-Pandemic Online Learning : Invited Paper. KSE 2022: 1-6 - [e5]Partha Pratim Roy, Arvind Agarwal, Tianrui Li, P. Krishna Reddy, R. Uday Kiran:
Big Data Analytics - 10th International Conference, BDA 2022, Hyderabad, India, December 19-22, 2022, Proceedings. Lecture Notes in Computer Science 13773, Springer 2022, ISBN 978-3-031-24093-5 [contents] - [e4]Arnab Bhattacharya, Janice Lee, Mong Li, Divyakant Agrawal, P. Krishna Reddy, Mukesh K. Mohania, Anirban Mondal, Vikram Goyal, Rage Uday Kiran:
Database Systems for Advanced Applications - 27th International Conference, DASFAA 2022, Virtual Event, April 11-14, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13245, Springer 2022, ISBN 978-3-031-00122-2 [contents] - [e3]Arnab Bhattacharya, Janice Lee, Mong Li, Divyakant Agrawal, P. Krishna Reddy, Mukesh K. Mohania, Anirban Mondal, Vikram Goyal, Rage Uday Kiran:
Database Systems for Advanced Applications - 27th International Conference, DASFAA 2022, Virtual Event, April 11-14, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13246, Springer 2022, ISBN 978-3-031-00125-3 [contents] - [e2]Arnab Bhattacharya, Janice Lee, Mong Li, Divyakant Agrawal, P. Krishna Reddy, Mukesh K. Mohania, Anirban Mondal, Vikram Goyal, Rage Uday Kiran:
Database Systems for Advanced Applications - 27th International Conference, DASFAA 2022, Virtual Event, April 11-14, 2022, Proceedings, Part III. Lecture Notes in Computer Science 13247, Springer 2022, ISBN 978-3-031-00128-4 [contents] - [e1]Rage Uday Kiran, Vikram Goyal, P. Krishna Reddy:
Database Systems for Advanced Applications. DASFAA 2022 International Workshops - BDMS, BDQM, GDMA, IWBT, MAQTDS, and PMBD, Virtual Event, April 11-14, 2022, Proceedings. Lecture Notes in Computer Science 13248, Springer 2022, ISBN 978-3-031-11216-4 [contents] - 2021
- [j13]Md. Mostafizer Rahman, Yutaka Watanobe, Rage Uday Kiran, Truong Cong Thang, Incheon Paik:
Impact of Practical Skills on Academic Performance: A Data-Driven Analysis. IEEE Access 9: 139975-139993 (2021) - [j12]Philippe Fournier-Viger, Peng Yang, Rage Uday Kiran, Sebastián Ventura, José María Luna:
Mining local periodic patterns in a discrete sequence. Inf. Sci. 544: 519-548 (2021) - [c75]R. Uday Kiran, Pradeep Pallikila, José María Luna, Philippe Fournier-Viger, Masashi Toyoda, P. Krishna Reddy:
Discovering Relative High Utility Itemsets in Very Large Transactional Databases Using Null-Invariant Measure. IEEE BigData 2021: 252-262 - [c74]Palla Likhitha, Pamalla Veena, R. Uday Kiran, Yutaka Watanobe, Koji Zettsu:
Discovering Maximal Partial Periodic Patterns in Very Large Temporal Databases. IEEE BigData 2021: 1460-1469 - [c73]Tuan-Vinh La, Minh-Son Dao, Kazuki Tejima, Rage Uday Kiran, Koji Zettsu:
Improving the Awareness of Sustainable Smart Cities by Analyzing Lifelog Images and IoT Air Pollution Data. IEEE BigData 2021: 3589-3594 - [c72]Pradeep Pallikila, Pamalla Veena, R. Uday Kiran, Ram Avatar, Sadanori Ito, Koji Zettsu, P. Krishna Reddy:
Discovering Top-k Spatial High Utility Itemsets in Very Large Quantitative Spatiotemporal databases. IEEE BigData 2021: 4925-4935 - [c71]So Nakamura, R. Uday Kiran, Palla Likhitha, Penugonda Ravikumar, Yutaka Watanobe, Minh-Son Dao, Koji Zettsu, Masashi Toyoda:
Efficient Discovery of Partial Periodic-Frequent Patterns in Temporal Databases. DEXA (1) 2021: 221-227 - [c70]Penugonda Ravikumar, R. Uday Kiran, Narendra Babu Unnam, Yutaka Watanobe, Kazuo Goda, V. Susheela Devi, P. Krishna Reddy:
A Novel Parameter-Free Energy Efficient Fuzzy Nearest Neighbor Classifier for Time Series Data. FUZZ-IEEE 2021: 1-6 - [c69]Pamalla Veena, Sai Chithra Bommisetty, R. Uday Kiran, Sonali Agarwal, Koji Zettsu:
Discovering Fuzzy Frequent Spatial Patterns in Large Quantitative Spatiotemporal databases. FUZZ-IEEE 2021: 1-8 - [c68]R. Uday Kiran, Palla Likhitha, Minh-Son Dao, Koji Zettsu, Ji Zhang:
Discovering Periodic-Frequent Patterns in Uncertain Temporal Databases. ICONIP (5) 2021: 710-718 - [c67]Md. Mostafizer Rahman, Yutaka Watanobe, Rage Uday Kiran, Keita Nakamura:
A Novel Rule-Based Online Judge Recommender System to Promote Computer Programming Education. IEA/AIE (2) 2021: 15-27 - [c66]Penugonda Ravikumar, Likhitha Palla, Rage Uday Kiran, Yutaka Watanobe, Koji Zettsu:
Towards Efficient Discovery of Periodic-Frequent Patterns in Columnar Temporal Databases. IEA/AIE (1) 2021: 28-40 - [c65]Sai Chithra Bommisetty, Penugonda Ravikumar, Rage Uday Kiran, Minh-Son Dao, Koji Zettsu:
Discovering Spatial High Utility Itemsets in High-Dimensional Spatiotemporal Databases. IEA/AIE (1) 2021: 53-65 - [c64]Yutaka Watanobe, Md. Mostafizer Rahman, Rage Uday Kiran, Penugonda Ravikumar:
Online Automatic Assessment System for Program Code: Architecture and Experiences. IEA/AIE (2) 2021: 272-283 - [c63]Minh-Son Dao, Koji Zettsu, Rage Uday Kiran:
IMAGE-2-AQI: Aware of the Surrounding Air Qualification by a Few Images. IEA/AIE (2) 2021: 335-346 - [c62]Mohit Dandekar, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal, Rage Uday Kiran:
Fruit classification using deep feature maps in the presence of deceptive similar classes. IJCNN 2021: 1-6 - [c61]Pamalla Veena, So Nakamura, Palla Likhitha, R. Uday Kiran, Yutaka Watanobe, Koji Zettsu:
A Unified Framework to Discover Partial Periodic-Frequent Patterns in Row and Columnar Temporal Databases. ICDM (Workshops) 2021: 607-614 - [c60]R. Uday Kiran:
Discovering Knowledge Hidden in Raster Images using RasterMiner. ICDAR@ICMR 2021: 1 - [c59]Zhen Wang, Ji Zhang, Yizheng Chen, Chenhao Lu, Jerry Chun-Wei Lin, Jing Xiao, Rage Uday Kiran:
Learning Probabilistic Latent Structure for Outlier Detection from Multi-view Data. PAKDD (1) 2021: 53-65 - [c58]Md. Mostafizer Rahman, Yutaka Watanobe, Rage Uday Kiran, Raihan Kabir:
A Stacked Bidirectional LSTM Model for Classifying Source Codes Built in MPLs. PKDD/ECML Workshops (2) 2021: 75-89 - [c57]Md. Mostafizer Rahman, Yutaka Watanobe, Rage Uday Kiran, Truong Cong Thang, Incheon Paik:
Challenges and Exit Strategies for Adapting Interactive Online Education Amid the Pandemic and its Aftermath. TALE 2021: 595-602 - 2020
- [j11]R. Uday Kiran, P. P. C. Reddy, Koji Zettsu, Masashi Toyoda, Masaru Kitsuregawa, P. Krishna Reddy:
Efficient Discovery of Weighted Frequent Neighborhood Itemsets in Very Large Spatiotemporal Databases. IEEE Access 8: 27584-27596 (2020) - [j10]Philippe Fournier-Viger, Peng Yang, Zhitian Li, Jerry Chun-Wei Lin, Rage Uday Kiran:
Discovering rare correlated periodic patterns in multiple sequences. Data Knowl. Eng. 126: 101733 (2020) - [j9]Philippe Fournier-Viger, Jiaxuan Li, Jerry Chun-Wei Lin, Tin Truong-Chi, R. Uday Kiran:
Mining cost-effective patterns in event logs. Knowl. Based Syst. 191: 105241 (2020) - [c56]Minh-Son Dao, Ngoc-Thanh Nguyen, R. Uday Kiran, Koji Zettsu:
Fusion-3DCNN-max3P: A dynamic system for discovering patterns of predicted congestion. IEEE BigData 2020: 910-915 - [c55]Palla Likhitha, Penugonda Ravikumar, R. Uday Kiran, Yuto Hayamizu, Kazuo Goda, Masashi Toyoda, Koji Zettsu, Sourabh Shrivastava:
Discovering Closed Periodic-Frequent Patterns in Very Large Temporal Databases. IEEE BigData 2020: 4700-4709 - [c54]R. Uday Kiran, Sadanori Ito, Minh-Son Dao, Koji Zettsu, Cheng-Wei Wu, Yutaka Watanobe, Incheon Paik, Truong Cong Thang:
Distributed Mining of Spatial High Utility Itemsets in Very Large Spatiotemporal Databases using Spark In-Memory Computing Architecture. IEEE BigData 2020: 4724-4733 - [c53]R. Uday Kiran, Yutaka Watanobe, Bhaskar Chaudhury, Koji Zettsu, Masashi Toyoda, Masaru Kitsuregawa:
Discovering Maximal Periodic-Frequent Patterns in Very Large Temporal Databases. DSAA 2020: 11-20 - [c52]R. Uday Kiran, C. Saideep, Penugonda Ravikumar, Koji Zettsu, Masashi Toyoda, Masaru Kitsuregawa, P. Krishna Reddy:
Discovering Fuzzy Periodic-Frequent Patterns in Quantitative Temporal Databases. FUZZ-IEEE 2020: 1-8 - [c51]R. Uday Kiran, Sourabh Shrivastava, Philippe Fournier-Viger, Koji Zettsu, Masashi Toyoda, Masaru Kitsuregawa:
Discovering Frequent Spatial Patterns in Very Large Spatiotemporal Databases. SIGSPATIAL/GIS 2020: 445-448 - [c50]Minh-Son Dao, Ngoc-Thanh Nguyen, R. Uday Kiran, Koji Zettsu:
Insights From Urban Sensing Data: From Chaos to Predicted Congestion Patterns. ICDM (Workshops) 2020: 661-668 - [c49]C. Saideep, R. Uday Kiran, Koji Zettsu, Cheng-Wei Wu, P. Krishna Reddy, Masashi Toyoda, Masaru Kitsuregawa:
Parallel Mining of Partial Periodic Itemsets in Big Data. IEA/AIE 2020: 807-819
2010 – 2019
- 2019
- [j8]Philippe Fournier-Viger, Zhitian Li, Jerry Chun-Wei Lin, Rage Uday Kiran, Hamido Fujita:
Efficient algorithms to identify periodic patterns in multiple sequences. Inf. Sci. 489: 205-226 (2019) - [c48]Philippe Fournier-Viger, Chao Cheng, Jerry Chun-Wei Lin, Unil Yun, R. Uday Kiran:
TKG: Efficient Mining of Top-K Frequent Subgraphs. BDA 2019: 209-226 - [c47]P. P. C. Reddy, R. Uday Kiran, Koji Zettsu, Masashi Toyoda, P. Krishna Reddy, Masaru Kitsuregawa:
Discovering Spatial High Utility Frequent Itemsets in Spatiotemporal Databases. BDA 2019: 287-306 - [c46]R. Uday Kiran, C. Saideep, Koji Zettsu, Masashi Toyoda, Masaru Kitsuregawa, P. Krishna Reddy:
Discovering Partial Periodic Spatial Patterns in Spatiotemporal Databases. IEEE BigData 2019: 233-238 - [c45]T. Yashwanth Reddy, R. Uday Kiran, Masashi Toyoda, P. Krishna Reddy, Masaru Kitsuregawa:
Discovering Partial Periodic High Utility Itemsets in Temporal Databases. DEXA (2) 2019: 351-361 - [c44]Rage Uday Kiran, P. P. C. Reddy, Koji Zettsu, Masashi Toyoda, Masaru Kitsuregawa, P. Krishna Reddy:
Discovering Spatial Weighted Frequent Itemsets in Spatiotemporal Databases. ICDM Workshops 2019: 987-996 - [c43]C. Saideep, Rage Uday Kiran, Koji Zettsu, Philippe Fournier-Viger, Masaru Kitsuregawa, P. Krishna Reddy:
Discovering Periodic Patterns in Irregular Time Series. ICDM Workshops 2019: 1020-1028 - [c42]Philippe Fournier-Viger, Peng Yang, Jerry Chun-Wei Lin, Rage Uday Kiran:
Discovering Stable Periodic-Frequent Patterns in Transactional Data. IEA/AIE 2019: 230-244 - [c41]R. Uday Kiran, T. Yashwanth Reddy, Philippe Fournier-Viger, Masashi Toyoda, P. Krishna Reddy, Masaru Kitsuregawa:
Efficiently Finding High Utility-Frequent Itemsets Using Cutoff and Suffix Utility. PAKDD (2) 2019: 191-203 - [c40]R. Uday Kiran, Koji Zettsu, Masashi Toyoda, Philippe Fournier-Viger, P. Krishna Reddy, Masaru Kitsuregawa:
Discovering Spatial High Utility Itemsets in Spatiotemporal Databases. SSDBM 2019: 49-60 - 2018
- [j7]J. N. Venkatesh, R. Uday Kiran, P. Krishna Reddy, Masaru Kitsuregawa:
Discovering Periodic-Correlated Patterns in Temporal Databases. Trans. Large Scale Data Knowl. Centered Syst. 38: 146-172 (2018) - [c39]R. Uday Kiran, Amulya Kotni, P. Krishna Reddy, Masashi Toyoda, Subhash Bhalla, Masaru Kitsuregawa:
Efficient Discovery of Weighted Frequent Itemsets in Very Large Transactional Databases: A Re-visit. IEEE BigData 2018: 723-732 - [c38]Philippe Fournier-Viger, Zhitian Li, Jerry Chun-Wei Lin, Rage Uday Kiran, Hamido Fujita:
Discovering Periodic Patterns Common to Multiple Sequences. DaWaK 2018: 231-246 - [c37]Amulya Kotni, R. Uday Kiran, Masashi Toyoda, P. Krishna Reddy, Masaru Kitsuregawa:
Novel Data Segmentation Techniques for Efficient Discovery of Correlated Patterns Using Parallel Algorithms. DaWaK 2018: 355-370 - [c36]Qian Li, Ziwei Li, Jin-Mao Wei, Zhenglu Yang, Yanhui Gu, R. Uday Kiran:
A Story Coherence based Neural Network Model for Predicting Story Ending. WWW (Companion Volume) 2018: 119-120 - 2017
- [j6]R. Uday Kiran, J. N. Venkatesh, Masashi Toyoda, Masaru Kitsuregawa, P. Krishna Reddy:
Discovering partial periodic-frequent patterns in a transactional database. J. Syst. Softw. 125: 170-182 (2017) - [c35]Alampally Anirudh, R. Uday Kiran, P. Krishna Reddy, Masashi Toyoda, Masaru Kitsuregawa:
An Efficient Map-Reduce Framework to Mine Periodic Frequent Patterns. DaWaK 2017: 120-129 - [c34]R. Uday Kiran, J. N. Venkatesh, Philippe Fournier-Viger, Masashi Toyoda, P. Krishna Reddy, Masaru Kitsuregawa:
Discovering Periodic Patterns in Non-uniform Temporal Databases. PAKDD (2) 2017: 604-617 - [c33]R. Uday Kiran, Haichuan Shang, Masashi Toyoda, Masaru Kitsuregawa:
Discovering Partial Periodic Itemsets in Temporal Databases. SSDBM 2017: 30:1-30:6 - 2016
- [j5]R. Uday Kiran, Masaru Kitsuregawa, P. Krishna Reddy:
Efficient discovery of periodic-frequent patterns in very large databases. J. Syst. Softw. 112: 110-121 (2016) - [c32]J. N. Venkatesh, R. Uday Kiran, P. Krishna Reddy, Masaru Kitsuregawa:
Discovering Periodic-Frequent Patterns in Transactional Databases Using All-Confidence and Periodic-All-Confidence. DEXA (1) 2016: 55-70 - [c31]Alampally Anirudh, R. Uday Kiran, P. Krishna Reddy, Masaru Kitsuregawa:
Memory efficient mining of periodic-frequent patterns in transactional databases. SSCI 2016: 1-8 - 2015
- [j4]Rage Uday Kiran, Masaru Kitsuregawa:
Efficient discovery of correlated patterns using multiple minimum all-confidence thresholds. J. Intell. Inf. Syst. 45(3): 357-377 (2015) - [j3]P. Gowtham Srinivas, P. Krishna Reddy, A. V. Trinath, Bhargav Sripada, R. Uday Kiran:
Mining coverage patterns from transactional databases. J. Intell. Inf. Syst. 45(3): 423-439 (2015) - [c30]R. Uday Kiran, Masaru Kitsuregawa:
Finding Periodic Patterns in Big Data. BDA 2015: 121-133 - [c29]Haichuan Shang, Xiang Zhao, R. Uday Kiran, Masaru Kitsuregawa:
Towards Scale-out Capability on Social Graphs. CIKM 2015: 253-262 - [c28]R. Uday Kiran, Masaru Kitsuregawa:
Discovering Chronic-Frequent Patterns in Transactional Databases. DNIS 2015: 12-26 - [c27]R. Uday Kiran, Haichuan Shang, Masashi Toyoda, Masaru Kitsuregawa:
Discovering Recurring Patterns in Time Series. EDBT 2015: 97-108 - 2014
- [c26]R. Uday Kiran, Masaru Kitsuregawa:
Novel Techniques to Reduce Search Space in Periodic-Frequent Pattern Mining. DASFAA (2) 2014: 377-391 - 2013
- [c25]R. Uday Kiran, Masaru Kitsuregawa:
An Improved Neighborhood-Restricted Association Rule-based Recommender System. ADC 2013: 43-50 - [c24]R. Uday Kiran, Masaru Kitsuregawa:
Discovering Quasi-Periodic-Frequent Patterns in Transactional Databases. BDA 2013: 97-115 - [c23]R. Uday Kiran, Masaru Kitsuregawa:
Towards Addressing the Coverage Problem in Association Rule-Based Recommender Systems. DEXA (2) 2013: 418-425 - [c22]R. Uday Kiran, Masaru Kitsuregawa:
Mining Correlated Patterns with Multiple Minimum All-Confidence Thresholds. PAKDD Workshops 2013: 295-306 - [c21]R. Uday Kiran, Masashi Toyoda, Masaru Kitsuregawa:
Towards efficient discovery of coverage patterns in transactional databases. SSDBM 2013: 38:1-38:4 - 2012
- [j2]Mittapally Kumara Swamy, P. Krishna Reddy, R. Uday Kiran, M. Venugopal Reddy:
Temporality-based user interface design approaches for desktop and small screen environment. Int. J. Comput. Sci. Eng. 7(1): 52-64 (2012) - [c20]R. Uday Kiran, Masaru Kitsuregawa:
Towards Efficient Discovery of Frequent Patterns with Relative Support. COMAD 2012: 92-99 - [c19]M. Venu, R. Uday Kiran, R. Kiranmai:
A robust neural network classifier to model the compressive strength of high performance concrete using feature subset selection. COMPUTE 2012: 1 - [c18]R. Uday Kiran, Masaru Kitsuregawa:
Efficient Discovery of Correlated Patterns in Transactional Databases Using Items' Support Intervals. DEXA (1) 2012: 234-248 - [c17]P. Gowtham Srinivas, P. Krishna Reddy, Bhargav Sripada, R. Uday Kiran, D. Satheesh Kumar:
Discovering Coverage Patterns for Banner Advertisement Placement. PAKDD (2) 2012: 133-144 - 2011
- [c16]Somya Srivastava, R. Uday Kiran, P. Krishna Reddy:
Discovering Diverse-Frequent Patterns in Transactional Databases. COMAD 2011: 69-78 - [c15]R. Uday Kiran, P. Krishna Reddy:
An Alternative Interestingness Measure for Mining Periodic-Frequent Patterns. DASFAA (1) 2011: 183-192 - [c14]Mohak Sharma, P. Krishna Reddy, R. Uday Kiran, Thirumalaisamy Ragunathan:
Improving the Performance of Recommender System by Exploiting the Categories of Products. DNIS 2011: 137-146 - [c13]R. Uday Kiran, P. Krishna Reddy:
Novel techniques to reduce search space in multiple minimum supports-based frequent pattern mining algorithms. EDBT 2011: 11-20 - [c12]Akshat Surana, R. Uday Kiran, P. Krishna Reddy:
An Efficient Approach to Mine Periodic-Frequent Patterns in Transactional Databases. PAKDD Workshops 2011: 254-266 - [c11]Bhargav Sripada, Krishna Reddy Polepalli, Rage Uday Kiran:
Coverage patterns for efficient banner advertisement placement. WWW (Companion Volume) 2011: 131-132 - 2010
- [j1]R. Uday Kiran, P. Krishna Reddy, Mittapally Kumara Swamy, G. Syamasundar Reddy:
Analysing dynamics of crop problems by applying text analysis methods on farm advisory data of eSaguTM. Int. J. Comput. Sci. Eng. 5(2): 154-164 (2010) - [c10]R. Uday Kiran, Krishna Reddy Polepalli:
An Efficient Approach to Mine Rare Association Rules Using Maximum Items' Support Constraints. BNCOD 2010: 84-95 - [c9]Akshat Surana, R. Uday Kiran, P. Krishna Reddy:
Selecting a Right Interestingness Measure for Rare Association Rules. COMAD 2010: 115 - [c8]R. Uday Kiran, P. Krishna Reddy:
Mining periodic-frequent patterns with maximum items' support constraints. Bangalore Compute Conf. 2010: 1:1-1:8 - [c7]R. Uday Kiran, P. Krishna Reddy:
Mining Rare Association Rules in the Datasets with Widely Varying Items' Frequencies. DASFAA (1) 2010: 49-62 - [c6]R. Uday Kiran, P. Krishna Reddy:
Towards Efficient Mining of Periodic-Frequent Patterns in Transactional Databases. DEXA (2) 2010: 194-208 - [c5]Mittapally Kumara Swamy, P. Krishna Reddy, R. Uday Kiran, M. Venugopal Reddy:
Interface Tailoring by Exploiting Temporality of Attributes for Small Screens. DNIS 2010: 284-295
2000 – 2009
- 2009
- [c4]R. Uday Kiran, P. Krishna Reddy:
An improved multiple minimum support based approach to mine rare association rules. CIDM 2009: 340-347 - [c3]R. Uday Kiran, P. Krishna Reddy:
Mining Rare Periodic-Frequent Patterns Using Multiple Minimum Supports. COMAD 2009 - [c2]R. Uday Kiran, P. Krishna Reddy:
An Improved Frequent Pattern-growth Approach to Discover Rare Association Rules. KDIR 2009: 43-52 - 2007
- [c1]R. Uday Kiran, P. Krishna Reddy:
Understanding the Dynamics of Crop Problems by Analyzing Farm Advisory Data in eSagu TM . DNIS 2007: 272-284
Coauthor Index
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