Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object A Semantic Search Engine for Turkish and English Research Resources(Institute of Electrical and Electronics Engineers Inc., 2025) Karabacak, O.; Inan, E.Research resources are growing in volume at an exponential rate across disciplines and languages. This exponential increase has created a pressing need for intelligent search systems that can help researchers efficiently access relevant academic material. To overcome this issue, this study introduces a bilingual semantic search engine designed to retrieve academic articles written in both Turkish and English. The primary goal is to improve the accuracy and relevance of academic information retrieval by using modern Natural Language Processing techniques. Instead of relying on traditional keyword-based search methods, the system leverages transformer-based sentence embedding models. To capture semantic meaning more effectively, MiniLM-L6v2, paraphrase-multilingual-MiniLM-L12-v2 and multilingual-e5-base models were chosen for their multilingual capabilities and sentence-level embedding performance. To assess the quality of search results, Mean Average Precision (MAP) and Normalized Discounted Cumulative Gain (nDCG) were used. These metrics were calculated for each model across both language groups. Evaluation results show that the multilingual-e5-base model consistently outperformed the other models in both MAP and nDCG scores, demonstrating superior semantic understanding and multilingual alignment. The system also features a simple and responsive Streamlit-based interface that allows for real-time querying and result display. © 2025 IEEE.Book Part Urban Information Systems in Turkish Local Governments(IGI Global, 2008) Velibeyoǧlu, KoraySince the end of 1980s, different sectors have implemented geographical information systems (GIS) in Turkey. A study on GIS market in Turkey indicates that municipalities are the primary customers (Gülersoy & Yigiter, 1999). One of the earliest GIS projects in Turkey began with the production of digital maps covering the boundaries of Istanbul Metropolitan Municipality in 1987. Since 1994, a rapid development process has occurred with the widespread diffusion of GIS especially in universities and large public sector organizations respectively. However, the early city-wide municipal GIS projects were initiated only after 1996 (Ucuzal, 1999). © 2025 Elsevier B.V., All rights reserved.Article Recognition of Counterfactual Statements in Turkish(Assoc Computing Machinery, 2025) Acar, Ali; Tekir, SelmaCounterfactual statements are examples of causal reasoning as they describe events that did not happen and, optionally, those events' consequences if they happened. SemEval-2020 introduces the counterfactual detection (CFD) task and shares an English dataset. Since then, a set of datasets has been released in English, German, and Japanese as part of Amazon product reviews. This work releases the first Turkish corpus of counterfactuals (TRCD). The data collection process is driven by a clue phrase list of counterfactuals, mainly in the form of verb inflections in Turkish. We use clue phrase-based filtering to collect sentences from the Turkish National Corpus (TNC). On the other hand, half of the collection is subject to random word filtering to avoid selection bias due to clue phrases. After the human annotation process with an Inter Annotator Agreement of 0.65, we have 5000 sentences, of which 12.8% contain counterfactual statements. Furthermore, we provide a comprehensive baseline of transformer-based models by testing the effect of clue phrases, cross-lingual performance comparisons using the available CFD datasets, and zero-shot cross-lingual classification experiments using fine-tuning on the different combinations of the existing datasets. The results confirm that TRCD is compatible with the other CFD datasets. Moreover, fine-tuning a Turkish-specific model (BERTurk) performs better than the multilingual alternatives (mBERT and XLM-R). BERTurk is more robust to clue phrase masking. This result emphasizes the importance of a language-specific tokenizer for contextual understanding, especially for low-resource languages. Finally, our qualitative analysis gives insights into errors by different models.Conference Object Citation - Scopus: 1Applying Weighted Graph Embeddings To Turkish Metaphor Detection(Institute of Electrical and Electronics Engineers Inc., 2024) İnan, EmrahMetaphor is a common literary mechanism that allows abstract concepts to be conceptualised using more concrete terminology. Existing methods rely on either end-to-end models or hand-crafted pre-processing steps. Generating well-defined training datasets for supervised models is a time-consuming operation for this type of problem. There is also a lack of pre-processing steps for resource-poor natural languages. In this study, we propose an approach for detecting Turkish metaphorical concepts. Initially, we collect non-literal concepts including their meaning and reference sentences by employing a Turkish dictionary. Secondly, we generate a graph by discovering super-sense relations between sample texts including target metaphorical expressions in Turkish WordNet. We also compute weights for relations based on the path closeness and word occurrences. Finally, we classify the texts by leveraging a weighted graph embedding model. The evaluation setup indicates that the proposed approach reaches the best F1 and Gmean scores of 0.83 and 0.68 for the generated test sets when we use feature vector representations of the Node2Vec model as the input of the logistic regression for detecting metaphors in Turkish texts. © 2024 IEEE.Article Citation - Scopus: 4Analysis of Design-Driven Innovation Practices in Turkish and Swedish Furniture Firms: an Exploratory Approach(Common Ground Research Networks, 2019) Aydın, Mahmut Ferit; Erkarslan, ÖnderThis study explores and analyzes recent design-driven innovation (DDI) practices in the furniture industries in Turkey and Sweden.2 The study was conducted in three phases: an in-depth literature review; the identification and selection of furniture companies; and analysis of the selected companies based on the strategic, operational, market-entry and organizational dimensions. We used case-study methods and conducted semi-structured interviews with designers and design managers of leading furniture companies from Turkey (Nurus, Ersa, Burotime, and Tuna Ofis) and Sweden (Offecct and Skandiform). Through cross-case analysis of national outcomes, we propose additional drivers to DDI theory, such as product segmentation, activity research, culture research and concept/designer research. The results of this study are crucial for all parties involved, as they suggest ways to achieve incremental and radical design-driven innovations. © Common Ground Research Networks, M. Ferit Aydin, Onder Erkarslan, All Rights Reserved.