Sentiment Classification based on Domain Prediction

Muhammet Yasin Pak

Sentiment classification has received increasing attention in recent years. Supervised learning methods for sentiment classification require considerable amount of labeled data for training purposes. As the number of domains increases, the task of collecting data becomes impractical. Therefore, domain adaptation techniques are employed. However, most of the studies dealing with the domain adaptation problem demand a few amount of labeled data or lots of unlabeled data belonging to the target domain, which may not be always possible. In this work, a novel method for sentiment classification, wh ...Daha fazlası

Assessment of the relationship between executive Nurses’ leadership Self-Efficacy and medical artificial intelligence readiness

Ayşe EMİNOĞLU | Şirin ÇELİKKANAT

Aims This study aims to assess the relationship between management nurses' leadership self-efficacy and medical artificial intelligence readiness. Methods The research was conducted using a descriptive-correlational design. The sample of the study consisted of 196 management nurses working in public, private, and educational research hospitals in Gaziantep, Turkey. The data collection tools included the Personal Information Form, the Leadership Self-Efficacy Scale, and the Medical Artificial Intelligence Readiness Scale. Results The majority of the participants in the research were female (71. ...Daha fazlası

Türkiye'de Atık Üretimini Etkileyen Faktörlerin Logit-Probit Modeller ile Belirlenmesi

Özlem AKAY

Sentiment Classification based on Domain Prediction

Muhammet Yasin Pak

Sentiment classification has received increasing attention in recent years. Supervised learning methods for sentiment classification require considerable amount of labeled data for training purposes. As the number of domains increases, the task of collecting data becomes impractical. Therefore, domain adaptation techniques are employed. However, most of the studies dealing with the domain adaptation problem demand a few amount of labeled data or lots of unlabeled data belonging to the target domain, which may not be always possible. In this work, a novel method for sentiment classification, wh ...Daha fazlası

Multi-Criteria Collaborative Filtering Using Rough Sets Theory

Muhammet Yasin Pak

Recommender systems have recently become a significant part of e-commerce applications. Through the different types of recommender systems, collaborative filtering is the most popular and successful recommender system for providing recommendations. Recent studies have shown that using multi-criteria ratings helps the system to know the customers better. However, bringing multi aspects to collaborative filtering causes new challenges such as scalability and sparsity. Additionally, revealing the relation between criteria is yet another optimization problem. Hence, increasing the accuracy in pred ...Daha fazlası

Antioxidant, cytotoxicity, antimicrobial, wound healing potentials and LC-MS/MS analysis of water extract of Rhus coriaria L.(sumak) leaves

Comparison of exponential smoothing methods in forecasting global prices of main metals

Özlem AKAY

Prediction of Grain Products in Turkey

Özlem AKAY

Şehr-i Ayıntab-ı Cihan Gaziantep

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Segmentation and classification of skin burn images with artificial intelligence: Development of a mobile application

Ayse Elkoca

Aim: This study was conducted to determine the segmentation, classification, object detection, and accuracy of skin burn images using artificial intelligence and a mobile application. With this study, individuals were able to determine the degree of burns and see how to intervene through the mobile application. Methods: This research was conducted between 26.10.2021–01.09.2023. In this study, the dataset was handled in two stages. In the first stage, the open-access dataset was taken from https://universe.roboflow.com/, and the burn images dataset was created. In the second stage, in order to ...Daha fazlası

The impact of text representation and preprocessing on author identification

Muhammet Yasin Pak

Author identification, one of the popular topics in text classification and natural language processing, basically aims to determine the author of a given text through various analyses. In the literature, different text representation approaches and use of preprocessing steps are considered for author identification problem. This paper aims to comprehensively examine the impact of text representation and preprocessing steps on author identification specifically for Turkish language. For this purpose, the contributions of all possible combinations of different text representation approaches, na ...Daha fazlası

A Model for Cross-Domain Opinion Target Extraction in Sentiment Analysis

Muhammet Yasin Pak

Opinion target extraction is one of the core tasks in sentiment analysis on text data. In recent years, dependency parser–based approaches have been commonly studied for opinion target extraction. However, dependency parsers are limited by language and grammatical constraints. Therefore, in this work, a sequential pattern-based rule mining model, which does not have such constraints, is proposed for cross-domain opinion target extraction from product reviews in unknown domains. Thus, knowing the domain of reviews while extracting opinion targets becomes no longer a requirement. The proposed mo ...Daha fazlası