0% Complete
Home
/
13th International Conference on Computer and Knowledge Engineering
A Novel Hybrid Method for Clustering Text Documents using Evolutionary Optimization
Authors :
Muhammad Naderi
1
Maryam Amiri
2
1- Computer Engineering Group, Faculty of Engineering, Arak University
2- Assistant Professor, Department of Computer Engineering Faculty of Engineering, Arak University
Keywords :
Evolutionary computation،Clustering methods،Text clustering،Multi-objective Evolution
Abstract :
Unstructured text documents generated daily by millions of internet users have allocated a considerable volume of data in this digital age. Text document clustering is widely regarded as a highly effective method for analyzing text documents, particularly in response to the growing prevalence of big data. This technique is employed to group documents based on their content. Many text clustering algorithms commonly employ a single-criterion optimization strategy, which frequently falls short of generating effective clustering solutions across diverse datasets exhibiting various clustering characteristics. To address this challenge, the multi-objective meta-heuristic approach is employed to achieve optimal clustering outcomes by maximizing or minimizing multiple objective functions. Balancing exploitation and exploration is a crucial aspect of the metaheuristic approaches. To enhance this balance, we propose a Multi-objective Firefly Differential Jaya (MFDJ) evolutionary algorithm. MFDJ enhances the quest for optimal clustering by improving the equilibrium between exploitation and exploration. We evaluate MFDJ on some text datasets. As the experimental results show, the MFDJ algorithm outperforms new document clustering algorithms.
Papers List
List of archived papers
Multi Model CNN Based Gas Meter Characters Recognition
Sanaz Tarhib - Jafar Tanha - Soodabeh Imanzadeh - Sahar Hassanzadeh Mostafaei
EfficientNetB0’s Hybrid Approach for Brain Tumor Classification from MRI Images Using Deep Learning and Bagging Trees
Yeganeh Modaresnia - Farhad Abedinzadeh Torghabeh - Seyyed Abed Hosseini
Innovative Customer Segmentation based on Multi-Step Sequential Deep Clustering in the Telecommunication Industry
Fatemeh Jalali Farahani - Shima Tabibian
LPCNet: Lane detection by lane points correction network in challenging environments based on deep learning
Sina BaniasadAzad - Seyed Mohammadreza Mousavi mirkolaei
Islamic Geometric algorithms: A survey
Elham Akbari - Azam Bastanfard
The process of multi class fake news dataset generation
Sajjad Rezaei - Mohsen Kahani - Behshid Behkamal
Real-Time Gender Recognition with a Deep Neural Network
Samad Azimi Abriz - Majid Meghdadi
Investigating the Behavior of Generation Z Customers in Online Banking Services (Case Study of a Bank of Iran)
Elham Mahmoudabadi - Esmaeil Mollaahmadi
BERT transformers Multitask learning Sarcasm and Sentiment classification (BMSS)
Fatemeh Molavi - Jamshid Bagherzadeh Mohasefi
Weakly Supervised Convolutional Neural Network for Automatic Gleason Grading of Prostate Cancer
Maryam Kamareh - Mohammad Sadegh Helfroush - Kamran Kazemi
more
Samin Hamayesh - Version 41.7.6