TR-Dizin İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396
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Article İşbirlikçi Filtreleme temelinde Film Öneri Sistemleri: Netflix üzerinde bir VakaÇalışması(2021) Sütçü, Muhammed; Kaya, Ecem; Erdem, OğuzkanFilmler, şarkılar ve alışveriş ürünleri gibi ögelerin kullanıcı değerlendirmeleriÖneri Sistemleri (ÖS) tarafından henüz değerlendirilmemiş ürünleri tahmin etmekiçin kullanılır. ÖS kullanıcılara çeşitli alanlarda öneri vermek için geliştirilmiştir veÖS uygulama alanlarından birisi de film önerisidir. Bu alanda üç genel algoritmakullanılmaktadır; kullanıcılar arası benzerliğe dayanarak tavsiye veren İşbirlikçiFiltreleme, kullanıcı-eşya eşleştirilmesindeki ilişkiden beslenen İçerik TabanlıFiltreleme ve bu iki algoritmayı birleştiren Hibrit Filtreleme. Bu çalışmamızdaİşbirlikçi Filtreleme çerçevesinde hangi metotların daha etkili çalıştığı incelenmiştir.Analizimizde Netflix Ödül veri seti kullanılmış ve iyi bilinen İşbirlikçi Filtrelememetotları olan Tekil Değer Ayrışımı, Tekil Değer Ayrışımı++, K En Yakın Komşu veEş Kümeleme kıyaslanmıştır. Her metodun hatası Ortalama Hata Kare Kökükullanılarak ölçülmüştür. Son olarak, K En Yakın Komşu metodunun veri setimizdedaha başarılı olduğu sonuçlanmıştır.Article Movie Recommendation Systems Based on Collaborative Filtering: A Case Study on Netflix(Erciyes Üniversitesi, 2021) Sütçü, Muhammed; Erdem, Oğuzkan; Kaya, EcemUser ratings on items like movies, songs, and shopping products are used_x000D_ by Recommendation Systems (RS) to predict user preferences for items that have_x000D_ not been rated. RS has been utilized to give suggestions to users in various domains_x000D_ and one of the applications of RS is movie recommendation. In this domain, three_x000D_ general algorithms are applied; Collaborative Filtering that provides prediction_x000D_ based on similarities among users, Content-Based Filtering that is fed from the_x000D_ relation between item-user pairs and Hybrid Filtering one which combines these_x000D_ two algorithms. In this paper, we discuss which methods are more efficient in movie_x000D_ recommendation in the framework of Collaborative Filtering. In our analysis, we use_x000D_ Netflix Prize dataset and compare well-known Collaborative Filtering methods_x000D_ which are Singular Value Decomposition, Singular Value Decomposition++, KNearest Neighbour and Co-Clustering. The error of each method is calculated by_x000D_ using Root Mean Square Error (RMSE). Finally, we conclude that K-Nearest_x000D_ Neighbour method is more successful in our dataset.Article Optimal Location Determination of Electric Vehicle Charging Stations: A Case Study on Turkey's Most Preferred Highway(2022-06-30) Gülbahar, İbrahim Tümay; Sütçü, MuhammedToday, electric vehicles are seen as one of the most suitable and environmentally friendly alternatives to internal combustion engine vehicles. An important issue related to the dissemination of electric vehicles is the location of the vehicle charging network and specifically the optimum location selection of the charging stations. Generally, most of the studies focus on popular destinations such as city centers, shopping areas, bus stations, and airports. Although these places are often used in normal life, they can usually provide an adequate solution for daily charging needs due to the number of alternative charging stations. However, finding adequate charging stations is not possible in intercity travels especially in highways. In this paper, we proposed a decision model to determine the location of electric car charging stations in highways. We create an optimization model to decide the optimum locations for the charging stations that can meet the customer demands on the Istanbul-Ankara highway. The proposed model determines optimum charging stations that enable passengers traveling with their electric vehicles to travel in Istanbul-Ankara highway in the shortest time.Article Analysis of Under-Five Mortality by Diseases in Countries With Different Levels of Development: a Comparative Analysis(2023-07-03) Ersöz, Nur Şebnem; Sütçü, Muhammed; Şahan, Pınar GünerObjectives: The right to health is critical for children because they are sensitive beings who are more susceptible to disease and health problems. It would be beneficial to compare child mortality rates in countries with different levels of development and to conduct studies to address them by taking into account their causes. This study aims to analyze the situation of developed, developing and least developed countries in terms of causes under-5 child mortality (U5CM) determined by World Health Organization and to identify the similarities or differences of under-five mortality. Methods: Child mortality rates per 1,000 live births between 2000 and 2017 years in between different age groups (0-27 days and 1-59 months) by causes (disease-specific) were obtained from World Health Organization for a total 15 countries including developed, developing and least developed countries. Regression analysis was performed to identify which causes have more impact on child mortality. In addition, the relationship between diseases was calculated using Euclidean distance, and diseases were clustered using k-means clustering algorithm for each country. Results: As a result of mathematical and statistical analysis, it was seen that causes of child mortality have a significant relation with the development level of country where a child was born. Conclusions: It has been observed that the causes of child mortality in countries with different levels of development vary depending on different factors such as geographical conditions, air quality population and access to medicine.