Zeynep Hilal Kilimci
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View article: Forecasting Customer Churn using Machine Learning and Deep Learning Approaches
Forecasting Customer Churn using Machine Learning and Deep Learning Approaches Open
Customer churn forecasting is a challenging task recommended for churn prevention for companies operating in various industries such as banking, telecommunications, and insurance. Forecasting customer churn is very important for many compa…
View article: Evaluating raw waveforms with deep learning frameworks for speech emotion recognition
Evaluating raw waveforms with deep learning frameworks for speech emotion recognition Open
Speech emotion recognition is a challenging task in speech processing field. For this reason, feature extraction process has a crucial importance to demonstrate and process the speech signals. In this work, we represent a model, which feed…
View article: Migrating birds optimization-based feature selection for text classification
Migrating birds optimization-based feature selection for text classification Open
Text classification tasks, particularly those involving a large number of features, pose significant challenges in effective feature selection. This research introduces a novel methodology, MBO-NB, which integrates Migrating Birds Optimiza…
View article: Görme engelliler için nesne tanıma ve resim altyazısını derin öğrenme teknikleriyle entegre eden verimli bir aktivite tanıma modeli
Görme engelliler için nesne tanıma ve resim altyazısını derin öğrenme teknikleriyle entegre eden verimli bir aktivite tanıma modeli Open
Bir görüntünün içeriğini otomatik olarak tanımlamak, bilgisayarla görmeyi ve doğal dil işlemeyi birbirine bağlayan yapay zekadaki temel bir görevdir. Bu çalışmada, bilgisayarla görü ve makine çevirisindeki son gelişmeleri birleştiren ve bi…
View article: A Review of Metaheuristic Optimization Techniques in Text Classification
A Review of Metaheuristic Optimization Techniques in Text Classification Open
Metaheuristic algorithms, inspired by natural phenomena and human-based strategies, offer versatile approaches to navigate diverse search spaces and adapt to dynamic environments. These algorithms, including evolutionary algorithms, swarm …
View article: An efficient consolidation of word embedding and deep learning techniques for classifying anticancer peptides: FastText+BiLSTM
An efficient consolidation of word embedding and deep learning techniques for classifying anticancer peptides: FastText+BiLSTM Open
Anticancer peptides (ACPs) are a group of peptides that exhibit antineoplastic properties. The utilization of ACPs in cancer prevention can present a viable substitute for conventional cancer therapeutics, as they possess a higher degree o…
View article: Special issue on computing, intelligence and data analytics for wisdom (<scp>CIDA4Wisdom</scp>)
Special issue on computing, intelligence and data analytics for wisdom (<span>CIDA4Wisdom</span>) Open
Data wisdom is the ability to think critically about data and create data-based judgments by combining domain, mathematical, and methodological expertise with experience, comprehension, common sense, insight, and sound judgment. This speci…
View article: ACP-ESM: A novel framework for classification of anticancer peptides using protein-oriented transformer approach
ACP-ESM: A novel framework for classification of anticancer peptides using protein-oriented transformer approach Open
Anticancer peptides (ACPs) are a class of molecules that have gained significant attention in the field of cancer research and therapy. ACPs are short chains of amino acids, the building blocks of proteins, and they possess the ability to …
View article: Migrating Birds Optimization-Based Feature Selection for Text Classification
Migrating Birds Optimization-Based Feature Selection for Text Classification Open
This research introduces a novel approach, MBO-NB, that leverages Migrating Birds Optimization (MBO) coupled with Naive Bayes as an internal classifier to address feature selection challenges in text classification having large number of f…
View article: A novel transformer-based approach for soil temperature prediction
A novel transformer-based approach for soil temperature prediction Open
Soil temperature is one of the most significant parameters that plays a crucial role in glacier energy, dynamics of mass balance, processes of surface hydrological, coaction of glacier-atmosphere, nutrient cycling, ecological stability, th…
View article: Heart Disease Prediction with Machine Learning-Based Approaches
Heart Disease Prediction with Machine Learning-Based Approaches Open
Heart disease, a global ailment with substantial mortality rates, poses a significant health concern. The prevalence of heart disease has escalated due to the demanding nature of contemporary occupations and inherent genetic predisposition…
View article: Heart Disease Detection using Vision-Based Transformer Models from ECG Images
Heart Disease Detection using Vision-Based Transformer Models from ECG Images Open
Heart disease, also known as cardiovascular disease, is a prevalent and critical medical condition characterized by the impairment of the heart and blood vessels, leading to various complications such as coronary artery disease, heart fail…
View article: Detection of Fault from Acoustic Signals in Automobile Engines using Deep Learning Techniques
Detection of Fault from Acoustic Signals in Automobile Engines using Deep Learning Techniques Open
Detecting faults in automobile engines from sound signals is a challenging task in the production phase of automobiles. That is why it attracts engineers and researchers to handle this issue thereby applying various solutions. In this work…
View article: An Efficient Consolidation of Word Embedding and Deep Learning Techniques for Classifying Anticancer Peptides: FastText+BiLSTM
An Efficient Consolidation of Word Embedding and Deep Learning Techniques for Classifying Anticancer Peptides: FastText+BiLSTM Open
Anticancer peptides (ACPs) are a group of peptides that exhibite antineoplastic properties. The utilization of ACPs in cancer prevention can present a viable substitute for conventional cancer therapeutics, as they possess a higher degree …
View article: Evaluating raw waveforms with deep learning frameworks for speech emotion recognition
Evaluating raw waveforms with deep learning frameworks for speech emotion recognition Open
Speech emotion recognition is a challenging task in speech processing field. For this reason, feature extraction process has a crucial importance to demonstrate and process the speech signals. In this work, we represent a model, which feed…
View article: An ensemble-based framework for mispronunciation detection of Arabic phonemes
An ensemble-based framework for mispronunciation detection of Arabic phonemes Open
Determination of mispronunciations and ensuring feedback to users are maintained by computer-assisted language learning (CALL) systems. In this work, we introduce an ensemble model that defines the mispronunciation of Arabic phonemes and a…
View article: The Effectiveness of Homogeneous Classifier Ensembles on Customer Churn Prediction in Banking, Insurance, and Telecommunication Sectors
The Effectiveness of Homogeneous Classifier Ensembles on Customer Churn Prediction in Banking, Insurance, and Telecommunication Sectors Open
The prediction of customer churn is a big challenging problem for companies in different sectors such as banking, telecommunication, and insurance. It is a crucial estimation for many businesses since obtaining new customers frequently cos…
View article: Derin öğrenme temelli hibrid altın endeksi (XAU/USD) yön tahmin modeli
Derin öğrenme temelli hibrid altın endeksi (XAU/USD) yön tahmin modeli Open
Borsa, döviz kuru, kripto para yön tahminlerinin yanı sıra 1 ons altının dolar cinsinden değerini belirleyen altın endeksinin (XAU/USD) yönünün tahminlenmesi de yatırımcılar, araştırmacılar ve analistler için cezbedici bir araştırma konusu…
View article: Consolidation of Time Series Models for the Prediction of XUTEK Index and Technology Stocks in Istanbul Stock Exchange during Pandemic Period
Consolidation of Time Series Models for the Prediction of XUTEK Index and Technology Stocks in Istanbul Stock Exchange during Pandemic Period Open
Due to the closure experienced during the pandemic, many investors divert their investments to different exchanges. In this sense, it has been observed that while sectors such as transportation, banking, and services have seriously lost va…
View article: Ensemble Regression-Based Gold Price (XAU/USD) Prediction
Ensemble Regression-Based Gold Price (XAU/USD) Prediction Open
The prediction of any commodities such as cryptocurrency, stocks, silver, gold is a challenging task for the investors, researchers, and analysts. In this work, we propose a model that forecasts the value of 1 ounce of gold in dollars by u…
View article: The Prediction of Chiral Metamaterial Resonance using Convolutional Neural Networks and Conventional Machine Learning Algorithms
The Prediction of Chiral Metamaterial Resonance using Convolutional Neural Networks and Conventional Machine Learning Algorithms Open
Electromagnetic resonance is the most important distinguishing property of metamaterials to examine many unusual phenomena. The resonant response of metamaterials can depend many parameters such as geometry, incident wave polarization. The…
View article: Evaluation of Society Response to Violence against Women in Turkey via Twitter using Topic Modeling
Evaluation of Society Response to Violence against Women in Turkey via Twitter using Topic Modeling Open
In recent times, people's reactions to violence against women, harassment and murder have been shared more and more, thanks to social media. This, in turn, led to the organization of people and increased awareness of violence against women…
View article: Consolidation of Time Series Models for the Prediction of XUTEK Index and Technology Stocks in Istanbul Stock Exchange (BIST) during Pandemic Period
Consolidation of Time Series Models for the Prediction of XUTEK Index and Technology Stocks in Istanbul Stock Exchange (BIST) during Pandemic Period Open
Due to the closure experienced during the pandemic, many investors divert their investments to different exchanges. In this sense, it has been observed that while sectors such as transportation, banking, and services have seriously lost va…
View article: Prediction of user loyalty in mobile applications using deep contextualized word representations
Prediction of user loyalty in mobile applications using deep contextualized word representations Open
Customer loyalty is important for many industries, including banking, telecommunications, gaming, and shopping, in terms of sustainability. In mobile applications, it is observed that the demand rises with the usage of mobile devices such …
View article: Comprehensive Analysis of Forest Fire Detection using Deep Learning Models and Conventional Machine Learning Algorithms
Comprehensive Analysis of Forest Fire Detection using Deep Learning Models and Conventional Machine Learning Algorithms Open
Forest fire detection is a very challenging problem in the field of object detection. Fire detection-based image analysis have advantages such as usage on wide open areas, the possibility for operator to visually confirm presence, intensit…
View article: A Novel Deep Reinforcement Learning Based Stock Direction Prediction using Knowledge Graph and Community Aware Sentiments
A Novel Deep Reinforcement Learning Based Stock Direction Prediction using Knowledge Graph and Community Aware Sentiments Open
Stock market prediction has been an important topic for investors, researchers, and analysts. Because it is affected by too many factors, stock market prediction is a difficult task to handle. In this study, we propose a novel method that …
View article: A Novel Deep Reinforcement Learning Based Stock Direction Prediction\n using Knowledge Graph and Community Aware Sentiments
A Novel Deep Reinforcement Learning Based Stock Direction Prediction\n using Knowledge Graph and Community Aware Sentiments Open
Stock market prediction has been an important topic for investors,\nresearchers, and analysts. Because it is affected by too many factors, stock\nmarket prediction is a difficult task to handle. In this study, we propose a\nnovel method th…
View article: Derin öğrenme yöntemleri ve kelime yerleştirme modelleri kullanılarak Parkinson hastalığının duygu analiziyle değerlendirilmesi
Derin öğrenme yöntemleri ve kelime yerleştirme modelleri kullanılarak Parkinson hastalığının duygu analiziyle değerlendirilmesi Open
Parkinson hastalığı, hastanın yaşam kalitesini etkileyen, önemli sosyal ve ekonomik etkileri olan ve semptomların aşamalı görünümü nedeniyle erken teşhis edilmesi güç olan yaygın bir nörolojik hastalıktır. Parkinson hastalığının Twitter gi…
View article: The evaluation of Parkinson's disease with sentiment analysis using deep learning methods and word embedding models
The evaluation of Parkinson's disease with sentiment analysis using deep learning methods and word embedding models Open
Parkinson's disease is a common neurodegenerative neurological disorder, which affects the patient's quality of life, has significant social and economic effects, and is difficult to diagnose early due to the gradual appearance o…
View article: Stock Pattern Classification from Charts using Deep Learning Algorithms
Stock Pattern Classification from Charts using Deep Learning Algorithms Open
Pattern classification is related with the automatic finding of regularities in dataset through the utilization of various learning techniques. Thus, the classification of the objects into a set of categories or classes is provided. This s…