H.6.3.3. Pattern analysis
Hidden Pattern Discovery on Clinical Data: an Approach based on Data Mining Techniques

Meysam Roostaee; Razieh Meidanshahi

Volume 11, Issue 3 , July 2023, , Pages 343-355

https://doi.org/10.22044/jadm.2023.12855.2435

Abstract
  In this study, we sought to minimize the need for redundant blood tests in diagnosing common diseases by leveraging unsupervised data mining techniques on a large-scale dataset of over one million patients' blood test results. We excluded non-numeric and subjective data to ensure precision. To identify ...  Read More

BRTSRDM: Bi-Criteria Regression Test Suite Reduction based on Data Mining

Mohammad Reza Keyvanpour; Zahra Karimi Zandian; Nasrin Mottaghi

Volume 11, Issue 2 , April 2023, , Pages 161-186

https://doi.org/10.22044/jadm.2023.12208.2374

Abstract
  Regression testing reduction is an essential phase in software testing. In this step, the redundant and unnecessary cases are eliminated, whereas software accuracy and performance are not degraded. So far, various researches have been proposed in regression testing reduction field. The main challenge ...  Read More

F.4.18. Time series analysis
Time Series Clustering based on Aggregation and Selection of Extracted Features

Ali Ghorbanian; Hamideh Razavi

Volume 11, Issue 2 , April 2023, , Pages 303-314

https://doi.org/10.22044/jadm.2023.13089.2449

Abstract
  In time series clustering, features are typically extracted from the time series data and used for clustering instead of directly clustering the data. However, using the same set of features for all data sets may not be effective. To overcome this limitation, this study proposes a five-step algorithm ...  Read More

Clustering Methods to Analyze Social Media Posts during Coronavirus Pandemic in Iran

F. Amiri; S. Abbasi; M. Babaie mohamadeh

Volume 10, Issue 2 , April 2022, , Pages 159-169

https://doi.org/10.22044/jadm.2022.11270.2285

Abstract
  During the COVID-19 crisis, we face a wide range of thoughts, feelings, and behaviors on social media that play a significant role in spreading information regarding COVID-19. Trustful information, together with hopeful messages, could be used to control people's emotions and reactions during pandemics. ...  Read More

H.5.7. Segmentation
Image Segmentation using Improved Imperialist Competitive Algorithm and a Simple Post-processing

V. Naghashi; Sh. Lotfi

Volume 7, Issue 4 , November 2019, , Pages 507-519

https://doi.org/10.22044/jadm.2019.3935.1464

Abstract
  Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering ...  Read More

H.5. Image Processing and Computer Vision
Video Abstraction in H.264/AVC Compressed Domain

A. R. Yamghani; F. Zargari

Volume 7, Issue 4 , November 2019, , Pages 521-535

https://doi.org/10.22044/jadm.2019.7850.1928

Abstract
  Video abstraction allows searching, browsing and evaluating videos only by accessing the useful contents. Most of the studies are using pixel domain, which requires the decoding process and needs more time and process consuming than compressed domain video abstraction. In this paper, we present a new ...  Read More

H.6.2.2. Fuzzy set
Developing a Course Recommender by Combining Clustering and Fuzzy Association Rules

Sh. Asadi; Seyed M. b. Jafari; Z. Shokrollahi

Volume 7, Issue 2 , April 2019, , Pages 249-262

https://doi.org/10.22044/jadm.2018.6260.1739

Abstract
  Each semester, students go through the process of selecting appropriate courses. It is difficult to find information about each course and ultimately make decisions. The objective of this paper is to design a course recommender model which takes student characteristics into account to recommend appropriate ...  Read More

G.3.9. Database Applications
Using Combined Descriptive and Predictive Methods of Data Mining for Coronary Artery Disease Prediction: a Case Study Approach

M. Shamsollahi; A. Badiee; M. Ghazanfari

Volume 7, Issue 1 , January 2019, , Pages 47-58

https://doi.org/10.22044/jadm.2017.4992.1599

Abstract
  Heart disease is one of the major causes of morbidity in the world. Currently, large proportions of healthcare data are not processed properly, thus, failing to be effectively used for decision making purposes. The risk of heart disease may be predicted via investigation of heart disease risk factors ...  Read More

H.3. Artificial Intelligence
Extracting Prior Knowledge from Data Distribution to Migrate from Blind to Semi-Supervised Clustering

Z. Sedighi; R. Boostani

Volume 6, Issue 2 , July 2018, , Pages 287-295

https://doi.org/10.22044/jadm.2017.5064.1611

Abstract
  Although many studies have been conducted to improve the clustering efficiency, most of the state-of-art schemes suffer from the lack of robustness and stability. This paper is aimed at proposing an efficient approach to elicit prior knowledge in terms of must-link and cannot-link from the estimated ...  Read More

B. Computer Systems Organization
Target Tracking Based on Virtual Grid in Wireless Sensor Networks

F. Hoseini; A. Shahbahrami; A. Yaghoobi Notash

Volume 6, Issue 2 , July 2018, , Pages 313-319

https://doi.org/10.22044/jadm.2017.1057

Abstract
  One of the most important and typical application of wireless sensor networks (WSNs) is target tracking. Although target tracking, can provide benefits for large-scale WSNs and organize them into clusters but tracking a moving target in cluster-based WSNs suffers a boundary problem. The main goal of ...  Read More

H.6.4. Clustering
Grouping Objects to Homogeneous Classes Satisfying Requisite Mass

M. Manteqipour; A.R. Ghaffari Hadigheh; R. Mahmoodvand; A. Safari

Volume 6, Issue 1 , March 2018, , Pages 163-175

https://doi.org/10.22044/jadm.2017.988

Abstract
  Grouping datasets plays an important role in many scientific researches. Depending on data features and applications, different constrains are imposed on groups, while having groups with similar members is always a main criterion. In this paper, we propose an algorithm for grouping the objects with random ...  Read More

H.6.4. Clustering
Improved COA with Chaotic Initialization and Intelligent Migration for Data Clustering

M. Lashkari; M. Moattar

Volume 5, Issue 2 , July 2017, , Pages 293-305

https://doi.org/10.22044/jadm.2016.783

Abstract
  A well-known clustering algorithm is K-means. This algorithm, besides advantages such as high speed and ease of employment, suffers from the problem of local optima. In order to overcome this problem, a lot of studies have been done in clustering. This paper presents a hybrid Extended Cuckoo Optimization ...  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

Timing analysis
Fuzzy clustering of time series data: A particle swarm optimization approach

Z. Izakian; M. Mesgari

Volume 3, Issue 1 , March 2015, , Pages 39-46

https://doi.org/10.5829/idosi.JAIDM.2015.03.01.05

Abstract
  With rapid development in information gathering technologies and access to large amounts of data, we always require methods for data analyzing and extracting useful information from large raw dataset and data mining is an important method for solving this problem. Clustering analysis as the most commonly ...  Read More