Browsing by Author "Özacar, T"

Now showing 1 - 6 of 6
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    A tool for producing structured interoperable data from product features on the web
    (PERGAMON-ELSEVIER SCIENCE LTD) Özacar, T
    This paper introduces a tool that produces structured interoperable data from product features, i.e., attribute name-value pairs, on the web. The tool extracts the product features using a web site-specific template created by the user. The value of the extracted data is maximized by using GoodRelations, which is the standard vocabulary for modeling product types and their features. The final output of the tool is GoodRelations snippets, which contain product features encoded in RDFa or Microdata. These snippets can be embedded into existing static and dynamic web pages in a way accessible to major search engines like Google and Yahoo, mobile applications, and browser extensions. This increases the visibility of your products and services in the latest generation of search engines, recommender systems, and other novel applications. (C) 2015 Elsevier Ltd. All rights reserved.
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    Extending ontology pitfalls for better ontology evaluation
    (SAGE PUBLICATIONS LTD) Özacar, T
    This article presents a framework that detects potential ontology building errors to improve the ontology quality. These potential errors are called ontology pitfalls in the literature. This work extends the existing ontology pitfall set in the literature and suggests new solutions for ontology repair. We have also developed a Java implementation for detection of the proposed pitfalls. These pitfalls were evaluated with well-known ontologies using this implementation.
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    Hermos: An annotated image dataset for visual detection of grape leaf diseases
    (SAGE PUBLICATIONS LTD) Özacar, T; Öztürk, Ö; Savas, NG
    Powdery mildew, dead arm and vineyard downy mildew diseases are frequently seen in the vineyards in the Gediz River Basin, West Anatolia of Turkey. These diseases can be detected early using artificial intelligence (AI)-based systems that can contribute to crop yields and also reduce the labour of the farmer and the amount of pesticides used. This article presents a dataset - namely, Hermos - for use in such AI-based systems. Hermos contains four classes of grape leaf images: leaves with powdery mildew, leaves with dead arm, leaves with downy mildew and healthy leaves. We have currently 492 images and 13,913 labels in the dataset. We have published Hermos in the Linked Open Data (LOD) cloud in order to make it easier for consumers to access, process and manipulate the data.
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    A case study for block-based linked data generation: Recipes as jigsaw puzzles
    (SAGE PUBLICATIONS LTD) Öztürk, Ö; Özacar, T
    This article is a proof-of-concept case study to evaluate the functionality of a block metaphor-based linked data generator. In this work, we chose to produce linked data repository of recipes, which provide a medium for people to share their regional and healthy recipes with the masses. However, the same approach can also be adapted easily to other domains. Therefore, the applicability of our approach extends well beyond the food domain that we are considering in this article. As a medium for information sharing and understanding between heterogeneous systems, ontologies will play an important role in the realisation of the Internet of things (IoT) vision. Therefore, an ontology-based recipe repository would also be one of the basic blocks of a smart kitchen environment. However, building ontologies is a challenging task, especially for users who are not conversant in the ontology building languages. This article proposes an approach that can be used even by non-experts and facilitates the sharing and searching of recipe data. In our case, we exploit the features of the block paradigm to publish recipes in Linked Data format. In this way, users do not have to know the OWL (Web Ontology Language) syntax and the text input is kept minimal. As far as we know, this article is the first study that produces linked data using Blockly in the literature. We also conducted a user-based evaluation of the proposed approach using the System Usability Scale (SUS) questionnaire.
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    The extension-based inference algorithm for pD*
    (ELSEVIER) Öztürk, Ö; Özacar, T; Ünalir, MO
    In this work, we present a scalable rule-based reasoning algorithm for the OWL pD* language. This algorithm uses partial materialization and a syntactic ontology transformation (the extension-based knowledge model) to provide a fast inference. Because the materialized part of the ontology does not contain assertional data, the time consumed by the process, and the number of inferred triples, remain fixed with varying amounts of assertional data. The algorithm uses database reasoning and a query rewriting technique to handle the remaining inference. The extension-based knowledge model and the database reasoning prevent the expected decreases in query performances, which are the natural result of online reasoning during query time. This work also evaluates the efficiency of the proposed method by conducting experiments using LUBM and UOBM benchmarks. (C) 2011 Published by Elsevier B.V.
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    The Comparison of Parasitological and Bacteriological Stool Examinations in Patients with Gastrointestinal Symptoms
    (KAFKAS UNIV, VETERINER FAKULTESI DERGISI) Bayram, A; Oyur, T; Ünver, A; Aydemir, S; Özacar, T; Töz, SÖ; Turgay, N
    Stool samples of 236 patients with acute and chronic gastrointestinal symptoms admitted to Ege University Medical Faculty Parasitology Outpatient Clinic Laboratory between July 2009 to June 2010 were examined. One hundred eleven out of 236(47%) patients admitted to the laboratory during summer and autumn period with acute gastrointestinal symptoms while other 125 patients (53%) admitted during winter and spring with chronic symptoms. At least one parasite was determined in 112 out of 236 (47.45%) patients. In retrospective analysis, it has determined that the bacteriological examination of stool samples were also performed in 121 out of 236(51.7%) patients. Seven out of 121 (5.78%) patients admitted both bacteriological and parasitological laboratories together had at least one bacterial agent in their stool examination. Five out of 7 patients were found to be having bacteriological and parasitological mixed infection. Our findings showed that it is important to perform both bacteriological and parasitological examinations together in patients admitting to hospital with intestinal symptoms due to these mixed infections. Performing both diagnostic techniques together will improve accurate diagnosis, treatment and understanding possible etiological reasons of these mixed infections.