Browsing by Author "Briman, Mohammed Khalid Hilmi"

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Citation - WoS: 5
Citation - Scopus: 8
Beyond Rouge: a Comprehensive Evaluation Metric for Abstractive Summarization Leveraging Similarity, Entailment, and Acceptability
(World Scientific Publ Co Pte Ltd, 2024) Briman, Mohammed Khalid Hilmi; Yıldız, Beytullah; Yildiz, Beytullah; Yıldız, Beytullah; Software Engineering; 06. School Of Engineering; 01. Atılım University
A vast amount of textual information on the internet has amplified the importance of text summarization models. Abstractive summarization generates original words and sentences that may not exist in the source document to be summarized. Such abstractive models may suffer from shortcomings such as linguistic acceptability and hallucinations. Recall-Oriented Understudy for Gisting Evaluation (ROUGE) is a metric commonly used to evaluate abstractive summarization models. However, due to its n-gram-based approach, it ignores several critical linguistic aspects. In this work, we propose Similarity, Entailment, and Acceptability Score (SEAScore), an automatic evaluation metric for evaluating abstractive text summarization models using the power of state-of-the-art pre-trained language models. SEAScore comprises three language models (LMs) that extract meaningful linguistic features from candidate and reference summaries and a weighted sum aggregator that computes an evaluation score. Experimental results show that our LM-based SEAScore metric correlates better with human judgment than standard evaluation metrics such as ROUGE-N and BERTScore.
A New E-Commerce Model Suggestion of Agricultural Products
(Springer international Publishing Ag, 2024) Eryilmaz, Meltem; Briman, Mohammed Khalid Hilmi; Yakut, Gokce; Computer Engineering; 06. School Of Engineering; 01. Atılım University
This study aims to create an e-commerce application that enables farmers to sell their products directly to their customers without resorting to intermediaries by a smart cargo box. It presents a method by which the agricultural industry can gain momentum in e-commerce. The main contributions of the study are an e-commerce application that enables farmers to sell their products directly to the customer without the need for an intermediary and the design and implementation of a smart cargo box that is tailored to carry agricultural items throughout the delivery process that locks and unlocks only via QR code generated by the application after order. Django FrameworkNext.js, React.js, and Redux are used for the system development. The database is created with PostgreSQL using migrations, and AmazonWeb Services is used for this database. The "ESP32 Cam" is used to read the QR Code.