Journals
J.1 Ayşenur Deniz, Muhammed Mehdi Elömer, and Ahmet Arif Aydin (2023). A comparison of Apache Solr and Elasticsearch technologies in support of large-scale data analysis. Gümüşhane Üniversitesi Fen Bilimleri Dergisi. doi: https://doi.org/10.17714/gumusfenbil.1213317
Datasets
D.1 Aysenur Deniz and Ahmet Arif Aydin (2022). Web of Science Dataset (Engineering, Computing & Technology Journals). Mendeley Data, V2 . doi: 10.17632/syzcbykjw3.2
Projects
P.5 Journal Recommendation System (2023) is a web project developed in graduate school. A recommendation system has been created to help authors find appropriate journals to publish their articles. (Environments: Back-end: Python, Flask / Database Systems: MongoDB, Apache Solr, Elasticsearch / Front-end: HTML, CSS, Bootstrap)
P.4 Education Portal (2021) is a web application that aims to provide an effective educational environment for students, and teachers. (Environments: Back-end: Java / Database System: PostgreSQL / Front-end: JPA EclipseLink Framework, JSF, CSS, JS, Bootstrap, HTML)
P.3 English Words (2020) is a mobile application that can be used as an English vocabulary book. (Environments: Back-end: Kotlin / Front-end: XML)
P.2 Lab Material Control (2018) is a desktop application where laboratory materials are followed. (Environments: Java, JavaFX)
P.1 Internship Tracking System (2018) is a web project that serves as a bridge between student and company. (Environments: Back-end: Java / Database System: MySQL / Front-end: JDBC, JSF, CSS, JS, Bootstrap, HTML)
M.Sc. Thesis
Title:
Application and Comparison of Full-text Search Technologies for Big Data Processing
Abstract:
Today, the size of the data continues to increase at a serious pace. Operations performed on large datasets cause some difficulties as the size of the data increases. For example, searching within a dataset is one of the basic operations, and as the amount of data increases, it reveals various difficulties. In this thesis, a research is accomplished on the full-text search method based on the difficulties in the search processes. Full-text search is a method in which the search is performed on indexed data. This method provides an advantage in terms of faster access to data and effective search in a large dataset. In this study, a comparison of indexing and search performance was made for Apache Solr and Elasticsearch, which are popular full-text search technologies. First, indexing times for each technology were taken and compared using three different datasets and three different machines. Then, search times for both technologies were examined using 10 queries on the machine with the best indexing performance. Considering the results, Apache Solr performed better in both indexing and searching. Therefore, the web application developed for this study is built on Apache Solr. In the application part, a unique dataset was created and used, in which various information was collected from 1,655 journals in the Engineering, Computing & Technology collection on the Web of Science platform. Thanks to this application, researchers could list the journals suitable for their purpose to publish their work.