Yağcı, Semih

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14365/7591
Name Variants
Job Title
Email Address
semih.yagci@ieu.edu.tr
Main Affiliation
05.04. Software Engineering
Status
Current Staff
Website
ORCID ID
0009-0002-7754-4148
Scopus Author ID
59491387500
Turkish CoHE Profile ID
42A8201965F569FD
Google Scholar ID
WoS Researcher ID
Files
WhatsApp Image 2025-07-23 at 11.18.34.jpeg (202.71 KB)

Sustainable Development Goals

SDG data is not available
Documents

2

Citations

0

h-index

0

Go to Scopus profile
This researcher does not have a WoS ID.
Scholarly Output

2

Articles

0

Views / Downloads

1/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

0

Scopus Citation Count

0

WoS h-index

0

Scopus h-index

0

Patents

0

Projects

0

WoS Citations per Publication

0.00

Scopus Citations per Publication

0.00

Open Access Source

0

Supervised Theses

0

JournalCount
2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 16 October 2024 through 18 October 2024 -- Ankara -- 2045621
EAI/Springer Innovations in Communication and Computing1
Current Page: 1 / 1

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Filters

2024 - 20252
Reset filters

Settings

Scholarly Output Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Conference Object
    Aspect-Based Sentiment Annotation and Analysis System
    (Springer Science and Business Media Deutschland GmbH, 2025) Terziler, D.E.; Çekirdek, H.; Yağcı, S.; Kumova Metin, S.
    Today, the ever-increasing amount of user-generated content and online activities has increased the transfer of human opinions and feelings through unstructured text (chat, blogs, reviews, etc.) to high levels. This has made emotion/sentiment recognition from unstructured text one of the most popular tasks in the natural language processing field. In current studies, not only the feeling that is conveyed by the whole text is to be recognized but also the sentiment/feeling that is directed to a certain aspect is to be analyzed. In this study, we have built an aspect-based sentiment annotation and analysis system. The system provides an intelligent and user-friendly interface to construct an annotated dataset by highlighting aspect candidates and selecting the sentiment label value for a given aspect. It also gives recommendations to its users with possible aspect candidates and their corresponding sentiment values. The recommendation service in our system is based on existing AI models that have been used for aspect-based sentiment analysis. © 2025 Elsevier B.V., All rights reserved.
  • Thumbnail Image
    Conference Object
    Analyzing Traffic Patterns in Izmir: a Study on Busy Hours and Congestion
    (Institute of Electrical and Electronics Engineers Inc., 2024) Başoğul, Ali Ozan; Çekirdek, Hamza; Nakipoğlu, K.; Yağcı, Semih; Demir, Alper
    Developing strategies for transportation is one of the main tasks for smart cities. With the traffic data on key arteries of Izmir, this project aims to estimate the time intervals and routes where traffic jam may occur in Izmir and uncover relationships between various factors affecting traffic. The study demonstrates that accurate models can be developed to predict the number of passing vehicles and reveals interesting correlations within the data. © 2024 IEEE.