All Outputs (6)

A systematic review of research on cheating in online exams from 2010 to 2021 (2022)
Journal Article
Noorbehbahani, F., Mohammadi, A., & Aminazadeh, M. (2022). A systematic review of research on cheating in online exams from 2010 to 2021. Education and Information Technologies, 27(6), 8413-8460. https://doi.org/10.1007/s10639-022-10927-7

In recent years, online learning has received more attention than ever before. One of the most challenging aspects of online education is the students' assessment since academic integrity could be violated due to various cheating behaviors in online... Read More about A systematic review of research on cheating in online exams from 2010 to 2021.

Ensemble Deep Learning for Aspect-based Sentiment Analysis (2021)
Journal Article
Mohammadi, A., & Shaverizade, A. (2021). Ensemble Deep Learning for Aspect-based Sentiment Analysis. #Journal not on list, 12, 29-38. https://doi.org/10.22075/ijnaa.2021.4769

Sentiment analysis is a subfield of Natural Language Processing (NLP) which tries to process a text to extract opinions or attitudes towards topics or entities. Recently, the use of deep learning methods for sentiment analysis has received noticeable... Read More about Ensemble Deep Learning for Aspect-based Sentiment Analysis.

Finding influential users for different time bounds in social networks using multi-objective optimization (2018)
Journal Article
Mohammadi, A., & Saraee, M. (2018). Finding influential users for different time bounds in social networks using multi-objective optimization. Swarm and Evolutionary Computation, 40, 158-165. https://doi.org/10.1016/j.swevo.2018.02.003

Online social networks play an important role in marketing services. Influence maximization is a major challenge, in which the goal is to find the most influential users in a social network. Increasing the number of influenced users at the end of a d... Read More about Finding influential users for different time bounds in social networks using multi-objective optimization.

Time-sensitive influence maximization in social networks (2015)
Journal Article
Mohammadi, A., Saraee, M., & Mirzaei, A. (2015). Time-sensitive influence maximization in social networks. Journal of Information Science, 41(6), 765-778. https://doi.org/10.1177/0165551515602808

One of the fundamental issues in social networks is the influence maximization problem, where the goal is to identify a small subset of individuals such that they can trigger the largest number of members in the network. In real-world social networks... Read More about Time-sensitive influence maximization in social networks.

A survey on utilization of data mining approaches for dermatological (skin) diseases prediction (2011)
Journal Article
Barati, E., Saraee, M., Mohammadi, A., & Adibi, N. (2011). A survey on utilization of data mining approaches for dermatological (skin) diseases prediction. #Journal not on list,

Due to recent technology advances, large volumes of medical data is obtained. These data contain valuable information. Therefore data mining techniques can be used to extract useful patterns. This paper is intended to introduce data mining and its va... Read More about A survey on utilization of data mining approaches for dermatological (skin) diseases prediction.

Identification of disease-causing genes using microarray data mining and gene ontology (2011)
Journal Article
Mohammadi, A., Saraee, M., & Salehi, M. (2011). Identification of disease-causing genes using microarray data mining and gene ontology. BMC Medical Genomics, 4(12), 1-9. https://doi.org/10.1186/1755-8794-4-12

Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small... Read More about Identification of disease-causing genes using microarray data mining and gene ontology.