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Kazem Taghandiki
Kazem Taghandiki
Department of Computer Engineering, Technical and Vocational University (TVU), Tehran, Iran
Verified email at tvu.ac.ir - Homepage
Title
Cited by
Cited by
Year
A supervised approach for automatic web documents topic extraction using well-known web design features
K Taghandiki, A Zaeri, A Shirani
International Journal of Modern Education and Computer Science 8 (11), 20, 2016
132016
Applying an innovative semantic sensor network model in internet of things
M Rezvan, M Barekatain, A Zaeri, K Taghandiki
2015 International conference on information and communication technology …, 2015
62015
Topic modeling: Exploring the processes, tools, challenges and applications
K Taghandiki, M Mohammadi
Authorea Preprints, 2023
42023
Building an Effective Email Spam Classification Model with spaCy
K Taghandiki
arXiv preprint arXiv:2303.08792, 2023
42023
Minimizing the repair cost of the air pressure system of scania trucks using a deep learning algorithm
K Taghandiki, M DallakehNejad
Authorea Preprints, 2023
32023
Implementation of a noisy hyperlink removal system: A semantic and relatedness approach
K Taghandiki, ER Ehsan
arXiv preprint arXiv:2303.03321, 2023
32023
Automatic summarisation of Instagram social network posts Combining semantic and statistical approaches
K Taghandiki, MH Ahmadi, ER Ehsan
arXiv preprint arXiv:2303.07957, 2023
22023
Types of Approaches, Applications and Challenges in the Development of Sentiment Analysis Systems
K Taghandiki, ER Ehsan
arXiv preprint arXiv:2303.11176, 2023
22023
Implementation of a Noisy Hyperlink Removal System: Using the Semantic and Relational Approach of the DBpedia Ontology
K Taghandiki
12023
A Review on the Application of Machine Learning in Gamma Spectroscopy: Challenges and Opportunities
M Zehtabvar, K Taghandiki, N Madani, D Sardari, B Bashiri
Spectroscopy Journal 2 (3), 123-144, 2024
2024
Large Language Models Training, Challenges, Applications, and Development
K Taghandiki, M Mohammadi
Authorea Preprints, 2024
2024
Reducing Air Pressure System Repair Costs in Scania Trucks through Deep Learning
K Taghandiki, M Dallakehnejad, H Rahimi Asiabaraki
Journal of Engineering and Applied Research 1 (1), 183-196, 2024
2024
Reduce the cost of repairing heavy machinery by enhancing the decision tree algorithm with information gain, correlation and SVM feature selection algorithms.
K Taghandiki, A Kalantari
The First National Conference on New Achievements in Electrical, Computer …, 2023
2023
Thematic modelling of web pages using MALT tools and supervised learning methods
K Taghandiki
The First National Conference on New Achievements in Electrical, Computer …, 2023
2023
An overview of approaches to solving matching problems and extracting textual elements from different images
K taghandiki
3rd International Conference on Electrical, Computer and Mechanical …, 2020
2020
Predicting and analyzing the behavioral patterns of acceptors in the electronic payment industry using machine learning
K Taghandiki
Fourth National Conference on Development of New Technologies in Management …, 2020
2020
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