Browsing by Author "Yeniterzi, R."

Filter results by typing the first few letters
Now showing 1 - 3 of 3
  • Placeholder
    ArticlePublicationMetadata only
    Applying deep learning models to twitter data to detect airport service quality
    (Elsevier, 2021-03) Barakat, Huda Mohammed Mohammed; Yeniterzi, R.; Martin-Domingo, Luis; Aviation Management; DOMINGO, Luıs Martın; Barakat, Huda Mohammed Mohammed
    Measuring airport service quality (ASQ) is an important process for identifying shortages and suggesting improvements that guide management decisions. This research, introduces a general framework for measuring ASQ using passengers’ tweets about airports. The proposed framework considers tweets in any language, not just in English, to support ASQ evaluation in non-speaking English countries where passengers communicate with other languages. Accordingly, this work uses a large dataset that includes tweets in two languages (English and Arabic) and from four airports. Additionally, to extract passenger evaluations from tweets, our framework applies two different deep learning models (CNN and LSTM) and compares their results. The two models are trained with both general data and data from the aviation domain in order to clarify the effect of data type on model performance. Results show that better performance is achieved with the LSTM model when trained with domain specific data. This study has clear implications for researchers and airport managers aiming to use alternative methods to measure ASQ.
  • Placeholder
    Conference paperPublicationMetadata only
    OzU-NLP at TREC NEWS 2019: Entity ranking
    (National Institute of Standards and Technology (NIST), 2019) Fayoumi, Kenan; Yeniterzi, R.; Fayoumi, Kenan
    This paper presents our work and submission for TREC 2019 News Track: Entity Ranking Task. Our approach utilizes Doc2Vec's ability to represent documents as fixed sized numerical vectors. Applied on news articles and wiki-pages of the entities, Doc2Vec provides us with vector representations for these two that we can utilize to perform ranking on entities. We also investigate whether background linked articles can be useful for entity ranking task.
  • Thumbnail Image
    Conference paperPublicationOpen Access
    WordNet and wikipedia connection in Turkish WordNet KeNet
    (European Language Resources Association (ELRA), 2022) Doğan, M.; Oksal, C.; Yenice, A. B.; Beyhan, F.; Yeniterzi, R.; Yıldız, Olcay Taner; Computer Science; YILDIZ, Olcay Taner
    This paper aims to present WordNet and Wikipedia connection by linking synsets from Turkish WordNet KeNet with Wikipedia and thus, provide a better machine-readable dictionary to create an NLP model with rich data. For this purpose, manual mapping between two resources is realized and 11,478 synsets are linked to Wikipedia. In addition to this, automatic linking approaches are utilized to analyze possible connection suggestions. Baseline Approach and ElasticSearch Based Approach help identify the potential human annotation errors and analyze the effectiveness of these approaches in linking. Adopting both manual and automatic mapping provides us with an encompassing resource of WordNet and Wikipedia connections.