Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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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.Conference Object Citation - WoS: 2Citation - Scopus: 2Türkçe Manzara Metni Veri Kümesi(IEEE, 2017) Erdogmus, NesliScene text localization and recognition keeps attracting an increasing interest from researchers due to its valuable advantage in extracting content from real world images and in image retrieval via text search. Nevertheless, due to the fact that the majority of the image datasets that are commonly used in this field is comprised of text in English, the related studies have mostly been limited to a single language. On that account, in order to apply the technologies developed for scene text detection and recognition to Turkish scene text, analyze their performances and to develop Turkish language specific algorithms, a Turkish scene text database is collected for the first time in the literature. In this paper, the contents of this database, shortly called STRIT (Scene Text Recognition In Turkish), are detailed. Additionally, two baseline methods are tested to detect and recognize scene text in Turkish and the preliminary results are presented.