Volume 13 (2025)
Volume 12 (2024)
Volume 11 (2023)
Volume 10 (2022)
Volume 9 (2021)
Volume 8 (2020)
Volume 7 (2019)
Volume 6 (2018)
Volume 5 (2017)
Volume 4 (2016)
Volume 3 (2015)
Volume 2 (2014)
Volume 1 (2013)
H.3.8. Natural Language Processing
ConSPro: Context-Aware Stance Detection Using Zero-Shot Prompting

Milad Allahgholi; Hossein Rahmani; Parinaz Soltanzadeh

Volume 13, Issue 2 , April 2025, , Pages 251-260

https://doi.org/10.22044/jadm.2025.15250.2629

Abstract
  Stance detection is the process of identifying and classifying an author's point of view or stance towards a specific target in a given text. Most of previous studies on stance detection neglect the contextual information hidden in the input data and as a result lead to less accurate results. In this ...  Read More

H.3.8. Natural Language Processing
DOSTE: Document Similarity Matching considering Informative Name Entities

Milad Allhgholi; Hossein Rahmani; Amirhossein Derakhshan; Saman Mohammadi Raouf

Volume 13, Issue 1 , January 2025, , Pages 85-94

https://doi.org/10.22044/jadm.2025.15383.2641

Abstract
  Document similarity matching is essential for efficient text retrieval, plagiarism detection, and content analysis. Existing studies in this field can be categorized into three approaches: statistical analysis, deep learning, and hybrid approaches. However, to the best of our knowledge, none have incorporated ...  Read More

H.3. Artificial Intelligence
FinFD-GCN: Using Graph Convolutional Networks for Fraud Detection in Financial Data

Mohamad Mahdi Yadegar; Hossein Rahmani

Volume 12, Issue 4 , November 2024, , Pages 487-495

https://doi.org/10.22044/jadm.2024.14869.2585

Abstract
  In recent years, new technologies have brought new innovations into the financial and commercial world, giving fraudsters many ways to commit fraud and cost companies big time. We can build systems that detect fraudulent patterns and prevent future incidents using advanced technologies. Machine learning ...  Read More

H.3. Artificial Intelligence
X-SHAoLIM: Novel Feature Selection Framework for Credit Card Fraud Detection

Sajjad Alizadeh Fard; Hossein Rahmani

Volume 12, Issue 1 , January 2024, , Pages 57-66

https://doi.org/10.22044/jadm.2024.13630.2480

Abstract
  Fraud in financial data is a significant concern for both businesses and individuals. Credit card transactions involve numerous features, some of which may lack relevance for classifiers and could lead to overfitting. A pivotal step in the fraud detection process is feature selection, which profoundly ...  Read More

Document and Text Processing
DcDiRNeSa, Drug Combination Prediction by Integrating Dimension Reduction and Negative Sampling Techniques

Mina Tabatabaei; Hossein Rahmani; Motahareh Nasiri

Volume 11, Issue 3 , July 2023, , Pages 417-427

https://doi.org/10.22044/jadm.2023.12883.2437

Abstract
  The search for effective treatments for complex diseases, while minimizing toxicity and side effects, has become crucial. However, identifying synergistic combinations of drugs is often a time-consuming and expensive process, relying on trial and error due to the vast search space involved. Addressing ...  Read More

MoGaL: Novel Movie Graph Construction by Applying LDA on Subtitle

Mohammad Nazari; Hossein Rahmani; Dadfar Momeni; Motahare Nasiri

Volume 11, Issue 2 , April 2023, , Pages 221-228

https://doi.org/10.22044/jadm.2023.12481.2396

Abstract
  Graph representation of data can better define relationships among data components and thus provide better and richer analysis. So far, movies have been represented in graphs many times using different features for clustering, genre prediction, and even for use in recommender systems. In constructing ...  Read More

DENOVA: Predicting Five-Factor Model using Deep Learning based on ANOVA

M. Nasiri; H. Rahmani

Volume 9, Issue 4 , November 2021, , Pages 451-463

https://doi.org/10.22044/jadm.2021.10471.2186

Abstract
  Determining the personality dimensions of individuals is very important in psychological research. The most well-known example of personality dimensions is the Five-Factor Model (FFM). There are two approaches 1- Manual and 2- Automatic for determining the personality dimensions. In a manual approach, ...  Read More

DINGA: A Genetic-algorithm-based Method for Finding Important Nodes in Social Networks

H. Rahmani; H. Kamali; H. Shah-Hosseini

Volume 8, Issue 4 , November 2020, , Pages 545-555

https://doi.org/10.22044/jadm.2020.9025.2040

Abstract
  Nowadays, a significant amount of studies are devoted to discovering important nodes in graph data. Social networks as graph data have attracted a lot of attention. There are various purposes for discovering the important nodes in social networks such as finding the leaders in them, i.e. the users who ...  Read More