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.3.8. Natural Language Processing
Multilingual Language Models in Persian NLP Tasks: A Performance ‎Comparison of Fine-Tuning Techniques

Ali Reza Ghasemi; Javad Salimi Sartakhti

Volume 13, Issue 1 , January 2025, , Pages 107-117

https://doi.org/10.22044/jadm.2025.15167.2625

Abstract
  This paper evaluates the performance of various fine-tuning methods in Persian natural language ‎processing (NLP) tasks. In low-resource languages like Persian, ‎which suffer from a lack of rich and sufficient data for training large ‎models, it is crucial to select appropriate fine-tuning ...  Read More

H.3.8. Natural Language Processing
Development of a Persian Mobile Sales Chatbot based on LLMs and Transformer

Nura Esfandiari; Kourosh Kiani; Razieh Rastgoo

Volume 12, Issue 4 , November 2024, , Pages 465-472

https://doi.org/10.22044/jadm.2024.15067.2609

Abstract
  Chatbots are computer programs designed to simulate human conversation. Powered by artificial intelligence (AI), these chatbots are increasingly used to provide customer service, particularly by large language models (LLMs). A process known as fine-tuning LLMs is employed to personalize chatbot answers. ...  Read More

H.3.8. Natural Language Processing
Study on Generative Adversarial Network in Discrete Data: A Survey

Alireza Mohammadi Gohar; Kambiz Rahbar; Behrouz Minaei-Bidgoli; Ziaeddin Beheshtifard

Volume 12, Issue 4 , November 2024, , Pages 567-581

https://doi.org/10.22044/jadm.2025.14978.2595

Abstract
  Generative Adversarial Networks (GANs) have emerged as a pivotal research focus within artificial intelligence due to their exceptional capabilities in data generation. Their ability to produce high-quality synthetic data has garnered significant attention, leading to their application in diverse domains ...  Read More

H.3.8. Natural Language Processing
PTRP: Title Generation Based On Transformer Models

Davud Mohammadpur; Mehdi Nazari

Volume 12, Issue 3 , July 2024, , Pages 325-335

https://doi.org/10.22044/jadm.2024.14633.2565

Abstract
  Text summarization has become one of the favorite subjects of researchers due to the rapid growth of contents. In title generation, a key aspect of text summarization, creating a concise and meaningful title is essential as it reflects the article's content, objectives, methodologies, and findings. Thus, ...  Read More

H.3.8. Natural Language Processing
Transformer-based Generative Chatbot Using Reinforcement Learning

Nura Esfandiari; Kourosh Kiani; Razieh Rastgoo

Volume 12, Issue 3 , July 2024, , Pages 349-358

https://doi.org/10.22044/jadm.2024.14466.2549

Abstract
  A chatbot is a computer program system designed to simulate human-like conversations and interact with users. It is a form of conversational agent that utilizes Natural Language Processing (NLP) and sequential models to understand user input, interpret their intent, and generate appropriate answer. This ...  Read More

H.3.8. Natural Language Processing
A Transformer-based Approach for Persian Text Chunking

P. Kavehzadeh; M. M. Abdollah Pour; S. Momtazi

Volume 10, Issue 3 , July 2022, , Pages 373-383

https://doi.org/10.22044/jadm.2022.11035.2250

Abstract
  Over the last few years, text chunking has taken a significant part in sequence labeling tasks. Although a large variety of methods have been proposed for shallow parsing in English, most proposed approaches for text chunking in Persian language are based on simple and traditional concepts. In this paper, ...  Read More

H.3.8. Natural Language Processing
A Novel Approach to Conditional Random Field-based Named Entity Recognition using Persian Specific Features

L. Jafar Tafreshi; F. Soltanzadeh

Volume 8, Issue 2 , April 2020, , Pages 227-236

https://doi.org/10.22044/jadm.2019.8430.1980

Abstract
  Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance ...  Read More

H.3.8. Natural Language Processing
Feature Engineering in Persian Dependency Parser

S. Lazemi; H. Ebrahimpour-komleh

Volume 7, Issue 3 , July 2019, , Pages 467-474

https://doi.org/10.22044/jadm.2018.6066.1720

Abstract
  Dependency parser is one of the most important fundamental tools in the natural language processing, which extracts structure of sentences and determines the relations between words based on the dependency grammar. The dependency parser is proper for free order languages, such as Persian. In this paper, ...  Read More

H.3.8. Natural Language Processing
Improvement of Chemical Named Entity Recognition through Sentence-based Random Under-sampling and Classifier Combination

A. Akkasi; E. Varoglu

Volume 7, Issue 2 , April 2019, , Pages 311-319

https://doi.org/10.22044/jadm.2018.5929.1700

Abstract
  Chemical Named Entity Recognition (NER) is the basic step for consequent information extraction tasks such as named entity resolution, drug-drug interaction discovery, extraction of the names of the molecules and their properties. Improvement in the performance of such systems may affects the quality ...  Read More

H.3.8. Natural Language Processing
Extraction of Drug-Drug Interaction from Literature through Detecting Linguistic-based Negation and Clause Dependency

B. Bokharaeian; A. Diaz

Volume 4, Issue 2 , July 2016, , Pages 203-212

https://doi.org/10.5829/idosi.JAIDM.2016.04.02.08

Abstract
  Extracting biomedical relations such as drug-drug interaction (DDI) from text is an important task in biomedical NLP. Due to the large number of complex sentences in biomedical literature, researchers have employed some sentence simplification techniques to improve the performance of the relation extraction ...  Read More

H.3.8. Natural Language Processing
An improved joint model: POS tagging and dependency parsing

A. Pakzad; B. Minaei Bidgoli

Volume 4, Issue 1 , March 2016, , Pages 1-8

https://doi.org/10.5829/idosi.JAIDM.2016.04.01.01

Abstract
  Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do ...  Read More

H.3.8. Natural Language Processing
Comparing k-means clusters on parallel Persian-English corpus

A. Khazaei; M. Ghasemzadeh

Volume 3, Issue 2 , July 2015, , Pages 203-208

https://doi.org/10.5829/idosi.JAIDM.2015.03.02.09

Abstract
  This paper compares clusters of aligned Persian and English texts obtained from k-means method. Text clustering has many applications in various fields of natural language processing. So far, much English documents clustering research has been accomplished. Now this question arises, are the results of ...  Read More