Maryam Khanian Najafabadi

According to our database, Maryam Khanian Najafabadi authored at least 18 papers between 2016 and 2026.

Collaborative distances:

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

2026

SensePoints: a deep learning approach based on multi-modal data fusion via multiple parallel convolutions to classify points in smart buildings.

Mashud Rana, Ashfaqur Rahman, John McCulloch, Eila Erfani, Maryam Khanian Najafabadi

Internet Things, 2026

A survey and illustrative example of hybrid semantic and contextual models for improving diversity and accuracy in personalized tag recommendation.

Maryam Khanian Najafabadi, Jiayi Chen, Saman Shojae Chaeikar, Javad Rezazadeh

Comput. Sci. Rev., 2026

2025

Q2HO-MFTV: A binary hippopotamus optimization algorithm for feature selection with a brief review of binary optimization.

Nastaran Mehrabi Hashjin, Mohammad Hussein Amiri, Amin Beheshti, Maryam Khanian Najafabadi

Knowl. Based Syst., 2025

From theory to practice: The evolution and comparative analysis of homogeneous vs. heterogeneous Graph Neural Networks in recommender systems.

Maryam Khanian Najafabadi, Rei-An Chen, Javad Rezazadeh, Amin Beheshti, Nasrin Shabani

Neurocomputing, 2025

An innovative data-driven AI approach for detecting and isolating faults in gas turbines at power plants.

Mohammad Hussein Amiri, Nastaran Mehrabi Hashjin, Maryam Khanian Najafabadi, Amin Beheshti, Nima Khodadadi

Expert Syst. Appl., 2025

Enhancing Facial Recognition and Expression Analysis With Unified Zero-Shot and Deep Learning Techniques.

Sasan Karamizadeh, Saman Shojae Chaeikar, Maryam Khanian Najafabadi

IEEE Access, 2025

Learning from Uncertainty: A Cloud-Based Active Learning for Detecting Bone Union in Mandibular Reconstruction.

MohammadHossein Ahmadi, Amin Beheshti, Yuankai Qi, Sam Mokhtari, Maryam Khanian Najafabadi, Masako Dunn, Jonathan R. Clark

Proceedings of the IEEE International Conference on Data Mining, 2025

2024

Attention-Based Graph Summarization for Large-Scale Information Retrieval.

Nasrin Shabani, Amin Beheshti, Alireza Jolfaei, Jia Wu, Venus Haghighi, Maryam Khanian Najafabadi, Jin Foo

IEEE Trans. Consumer Electron., August, 2024

Sentiment analysis incorporating convolutional neural network into hidden Markov model.

Maryam Khanian Najafabadi

Comput. Intell., April, 2024

GraphSUM: Scalable Graph Summarization for Efficient Question Answering.

Nasrin Shabani, Amin Beheshti, Jia Wu, Maryam Khanian Najafabadi, Jin Foo, Alireza Jolfaei

Proceedings of the Proceedings 27th International Conference on Extending Database Technology, 2024

2023

Aspect Level Sentiment Analysis with CNN Bi-LSTM and Attention Mechanism.

Jionghui Lin, Maryam Khanian Najafabadi

Proceedings of the 8th IEEE/ACIS International Conference on Big Data, 2023

2021

An Effective Collaborative User Model Using Hybrid Clustering Recommendation Methods.

Maryam Khanian Najafabadi, Azlinah Mohamed, Madhavan A/l Balan Nair, Sayed Mojtaba Tabibian

Ingénierie des Systèmes d Inf., 2021

2020

The state of the art and taxonomy of big data analytics: view from new big data framework.

Azlinah Mohamed, Maryam Khanian Najafabadi, Bee Wah Yap, Ezzatul Akmal Kamaru-Zaman, Ruhaila Maskat

Artif. Intell. Rev., 2020

2019

A survey on data mining techniques in recommender systems.

Maryam Khanian Najafabadi, Azlinah Hj. Mohamed, Mohd Naz'ri Mahrin

Soft Comput., 2019

An impact of time and item influencer in collaborative filtering recommendations using graph-based model.

Maryam Khanian Najafabadi, Azlinah Hj. Mohamed, Wou Onn Choo

Inf. Process. Manag., 2019

2018

Incremental Software Development Model for Solving Exam Scheduling Problems.

Maryam Khanian Najafabadi, Azlinah Mohamed

Proceedings of the Soft Computing in Data Science - 4th International Conference, 2018

2017

Improving the accuracy of collaborative filtering recommendations using clustering and association rules mining on implicit data.

Maryam Khanian Najafabadi, Mohd Naz'ri Mahrin, Suriayati Chuprat, Haslina Md Sarkan

Comput. Hum. Behav., 2017

2016

A systematic literature review on the state of research and practice of collaborative filtering technique and implicit feedback.

Maryam Khanian Najafabadi, Mohd Naz'ri Mahrin

Artif. Intell. Rev., 2016