Kuldeep Singh

Orcid: 0000-0001-5289-362X

Affiliations:
  • University of Delhi, Department of Computer Science, India
  • Indian Institute of Technology, BHU, Department of Computer Science and Engineering, Varanasi, India


According to our database1, Kuldeep Singh authored at least 15 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2023
High utility itemsets mining from transactional databases: a survey.
Appl. Intell., November, 2023

Prediction of Age and Gender from Masked Face Images using Convolution Neural Network.
Proceedings of the OITS International Conference on Information Technology, 2023

2022
A survey on soft computing-based high-utility itemsets mining.
Soft Comput., 2022

High average-utility itemsets mining: a survey.
Appl. Intell., 2022

2020
ACO-IM: maximizing influence in social networks using ant colony optimization.
Soft Comput., 2020

IM-SSO: Maximizing influence in social networks using social spider optimization.
Concurr. Comput. Pract. Exp., 2020

2019
Efficient Algorithm for Mining High Utility Pattern Considering Length Constraints.
Int. J. Data Warehous. Min., 2019

EHNL: An efficient algorithm for mining high utility itemsets with negative utility value and length constraints.
Inf. Sci., 2019

LAPSO-IM: A learning-based influence maximization approach for social networks.
Appl. Soft Comput., 2019

TKEH: an efficient algorithm for mining top-k high utility itemsets.
Appl. Intell., 2019

Level-2 node clustering coefficient-based link prediction.
Appl. Intell., 2019

2018
High utility itemsets mining with negative utility value: A survey.
J. Intell. Fuzzy Syst., 2018

Mining of high-utility itemsets with negative utility.
Expert Syst. J. Knowl. Eng., 2018

2015
An Efficient Approach to Discovering Frequent Patterns from Data Cube using Aggregation and Directed Graph.
Proceedings of the Sixth International Conference on Computer and Communication Technology 2015, 2015

Frequent Patterns Mining from Data Cube Using Aggregation and Directed Graph.
Proceedings of the 4th International Conference on Frontiers in Intelligent Computing: Theory and Applications, 2015


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