Browsing by Author "Turhan,Ç."

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    Citation - Scopus: 1
    Extractive Text Summarization for Turkish: Implementation of Tf-Idf and Pagerank Algorithms
    (Springer Science and Business Media Deutschland GmbH, 2023) Akülker,E.; Turhan,Ç.
    Due to the massive amount of information available on the web, reaching the desired content has become more and more difficult. Automatic text summarization helps to solve the problem by minimizing the document size while keeping its core information. In this study, two extractive single document automatic text summarization systems for Turkish are presented which implement the statistical-based TF-IDF algorithm as well as the combination of TF-IDF with the graph-based PageRank algorithm. The study aims to reveal the usability and effectiveness of these algorithms for Turkish documents. Moreover, the results of the TF-IDF implementation and the hybrid approach are compared using the co-selection measures, precision, recall, and F-score. In the evaluation phase, the system-generated summaries are categorized and tested based on their word sizes and the predetermined thresholds and compared against the human-generated summaries. The results indicate that the hybrid system performs better than the TF-IDF system even in lower thresholds, and also both systems are inclined to improve average F-scores in higher threshold generated summarization. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Citation - Scopus: 2
    Systematic Mapping Study on Natural Language Processing for Social Robots
    (Prof.Dr. İskender AKKURT, 2024) Adem,A.İ.; Turhan,Ç.; Sezen,A.
    Nowadays, social robots are becoming increasingly sophisticated in terms of their ability to interact with humans and possess social skills, and in this context, natural language processing (NLP) plays a critical role for robots to understand and communicate with human language. Natural Language Processing (NLP) is an interdisciplinary field used to help computers understand, interpret, and generate human language with a wide range of applications. The examination of the datasets, methods/techniques and tools, and usage of speech recognition or generation in the fields of NLP is important in understanding the developments in this field. In this study, 35 out of 92 studies in the literature collected from Web of Science were examined using a systematic mapping approach, and important findings on the use of NLP in social robots were identified. In particular, emphasis was placed on the effective evaluation of the research questions in the context of NLP in social robots. This study creates a starting point that will guide research in the field of NLP use in social robots and guide future studies. © 2024, Prof.Dr. İskender AKKURT. All rights reserved.