Computer Engineering / Bilgisayar Mühendisliği
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Article Gender Bias in Occupation Classification From the New York Times Obituaries(Dokuz Eylül Üniversitesi, 2022) Atik, Ceren; Tekir, SelmaTechnological developments such as artificial intelligence can strengthen social prejudices prevailing in society, regardless of the developer's intention. Therefore, researchers should be aware of the ethical issues that may arise from a developed product/solution. In this study, we investigate the effect of gender bias on occupational classification. For this purpose, a new dataset was created by collecting obituaries from the New York Times website and is provided in two different versions: With and without gender indicators. Category distributions from this dataset show that gender and occupation variables have dependence. Thus, gender affects occupation classification. To test the effect, we perform occupation classification using SVM (Support Vector Machine), HAN (Hierarchical Attention Network), and DistilBERT-based classifiers. Moreover, to get further insights into the relationship of gender and occupation in classification problems, a multi-tasking model in which occupation and gender are learned together is evaluated. Experimental results reveal that there is a gender bias in job classification.Article Sales History-Based Demand Prediction Using Generalized Linear Models(Süleyman Demirel Üniversitesi, 2019) Özenboy, Başar; Tekir, SelmaIt’s vital for commercial enterprises to accurately predict demand by utilizing the existing sales data. Such predictive analytics is a crucial part of their decision support systems to increase the profitability of the company.In predictive data analytics, the branch of regression modeling is used to predict a numerical response variable like sale amount. In this category, linear models are simple and easy to interpret yet they permit generalization to very powerful and flexible families of models which are called Generalized linear models (GLM). The generalization potential over simple linear regression can be explained twofold: First, GLM relax the assumption of normally distributed error terms. Moreover, the relationship of the set of predictor variables and the response variable could be represented by a set of link functions rather than the sole choice of the identity function. This work models the sales amount prediction problem through the use of GLM. Unique company sales data are explored and the response variable, sale amount is fitted to the Gamma distribution. Then, inverse link function, which is the canonical one in the case of gamma-distributed response variable is used. The experimental results are compared with the other regression models and the classification algorithms. The model selection is performed via the use of MSE and AIC metrics respectively. The results show that GLM is better than the linear regression. As for the classification algorithms, Random Forest and GLM are the top performers. Moreover, categorization on the predictor variables improves model fitting results significantly.Conference Object 13. Ulusal Yazılım Mühendisliği Sempozyumu(Izmir Institute of Technology, 2019) Ayav, Tolga; Tekir, Selma; Erten, MuratThe 13th National Software Engineering Symposium (UYMS) of Turkey was held Izmir Institute of Technology on 23-25 September 2019. There has been a great interest in this year’s symposium, as in previous years. UYMS is a platform which helps bring together the software industry and the academicians working in this area. It is being organized since 2003 and it plays an important role in shaping the future of the software industry in Turkey. We would like to thank all the participants whose contributions led to the successful realization of this symposium. We would also like to express our belief that these contributions will lead to a better and more productive efforts in the field of software engineering. Along with the main area of UYMS, in the thematic areas of Software Test Engineering, Software Engineering for Health, Software Modeling, and Graduate Theses, a total of 77 papers were accepted this year. At least three referees reviewed each paper and the papers were evaluated based on these reviews. We thank all the program committee members who served as referees.Article Gender Prediction From Tweets: Improving Neural Representations With Hand-Crafted Features(Cornell University, 2019) Tekir, Selma; Sezerer, Erhan; Polatbilek, OzanAuthor profiling is the characterization of an author through some key attributes such as gender, age, and language. In this paper, a RNN model with Attention (RNNwA) is proposed to predict the gender of a twitter user using their tweets. Both word level and tweet level attentions are utilized to learn ’where to look’. This model1 is improved by concatenating LSA-reduced n-gram features with the learned neural representation of a user. Both models are tested on three languages: English, Spanish, Arabic. The improved version of the proposed model (RNNwA + n-gram) achieves state-of-the-art performance on English and has competitive results on Spanish and Arabic.Conference Object Doğruluk Problemi için Veri Kümesi Hazırlanması(CEUR Workshop Proceedings, 2018) Karabayır, Arif Kürşat; Tek, Ozan Onur; Çınar, Özgür Fırat; Tekir, SelmaInternet has become one of the most important information sources. With the advent of Internet, the ease of access and sharing of information have caused the emergence of conflicting information. The increase in conflicting information makes it a challenge to find the truth out of it. This problem is named as the veracity problem. The algorithms that were developed in response to this problem accept structured data as in¬ put. Thus, to be able to use these algorithms on Internet, there is a need to transform the unstructured data on the Internet into a structured form. This need is hard to fulfill in a domain-independent and automatic way considering the variety on Internet. In this work; structured data preparation to test the effectiveness of the truth-finder algorithms is experienced. The process of transforming the unstructured data on the Internet into a structured form is described in steps to contribute its generalization in a domain-independent way. As a result of this process, a new quotes data set is constructed and a truth-finder algorithm is tested on this dataset by giving some comments on it.Conference Object Citation - WoS: 1Citation - Scopus: 1A Relativistic Opinion Mining Approach To Detect Factual or Opinionated News Sources(Springer Verlag, 2017) Sezerer, Erhan; Tekir, SelmaThe credibility of news cannot be isolated from that of its source. Further, it is mainly associated with a news source’s trustworthiness and expertise. In an effort to measure the trustworthiness of a news source, the factor of “is factual or opinionated” must be considered among others. In this work, we propose an unsupervised probabilistic lexicon-based opinion mining approach to describe a news source as “being factual or opinionated”. We get words’ positive, negative, and objective scores from a sentiment lexicon and normalize these scores through the use of their cumulative distribution. The idea behind the use of such a statistical approach is inspired from the relativism that each word is evaluated with its difference from the average word. In order to test the effectiveness of the approach, three different news sources are chosen. They are editorials, New York Times articles, and Reuters articles, which differ in their characteristic of being opinionated. Thus, the experimental validation is done by the analysis of variance on these different groups of news. The results prove that our technique can distinguish the news articles from these groups with respect to “being factual or opinionated” in a statistically significant way.Conference Object Sosyal Çizgeler için Arama Motoru Geliştirilmesi(CEUR Workshop Proceedings, 2016) Yafay, Erman; Tekir, SelmaSosyal ağlara giderek artan ilgi, beraberinde büyük ölçeklerde bağlantılı veri açığa çıkarmıştır. Bu büyük veriler üzerinde arama yapabilmek için özelleştirilmiş sistemlere gereksinim duyulmaktadır. Bu gereksinimi karşılamak üzere Facebook, 2013 yılında kendi arama motoru olan Unicorn’u[1] hizmete sunmuştur. Bu çalışmada, Unicorn’un asgari fakat temel özellikleri tasarlanıp gerçekleştirilmiştir. Yaklaşımımızda sosyal ağ bir çizge olarak modellenmiştir ve çizgedeki düğümler ve kenarlar farklı türlere sahip olabilecek şekilde genel olarak tanımlanmıştır. Düğümler, kişi veya sayfa gibi varlıkları ifade ederken; kenarlar, düğümler arasındaki arkadaşlık veya beğenme ilişkisini ortaya koyar. Verimlilik sorununu çözebilmek için tamamen bellek üzerinde çalışan bir indisleme sistemi geliştirilmiştir. Bu sistem geniş ölçekte veri işlenmesini sağlamak üzere geliştirilen dağıtık motor Spark[2] üzerinde gerçekleştirilmiştir. Son olarak, sosyal ağ yapısına uygun işleçler (ve, veya, zayıf- ve, güçlü-veya, uygula) tasarlanmıştır. Bu işleçler sayesinde kolayca kişilerin ortak arkadaşları veya arkadaşlarının arkadaşları gibi sorgular ifade edilip çalıştırılabilmektedir. Çalışmanın son bölümünde bu tip bir sistemin gerçekleştirilmesinde dikkate alınması gereken nitelikler, bu niteliklere ilişkin ödünleşimler ve karar mekanizmaları ele alınıp değerlendirilmiştir.Conference Object Bir Platform Oyununa Kullanıcı Performansı Temelinde Yapay Zeka Uyarlaması(CEUR Workshop Proceedings, 2015) Türkmen, Sercan; Mungan, Hilmi Yalın; Tekir, SelmaOyun programlama, video oyunlarının yazılım geliştirme bölümüdür. Diğer yazılımlardan farklı olarak oyun içindeki nesnelerin sürekli güncellenmesini gerektirmektedir. Güncelleme işlevinde, nesnenin dünya içinde bulunduğu yer, hız, ivme gibi fiziksel özellikleri, çarpışma işlemleri, animasyon güncellemeleri ve kullanıcı girdisinin ele alınması gibi çok çeşitli işlemler kapsanmaktadır. Yüksek güncelleme frekansı gereksinimi de dikkate alındığında yazılan kodun performansı ve kalitesi ön plana çıkmaktadır. Oyun alanı, yazılım karakteristiklerinden kullanılabilirliğin ötesinde kullanıcının eğlenmesini sağlamayı hedeflemektedir. Yapay zekanın uygulama alanlarının ve tekniklerinin gelişmesi oyunların eğlendirici yönünü arttırmaktadır. Bu çalışmada, bir platform oyunu (Dawn) geliştirilerek oyun içerisindeki kurguyu, geçerli kullanıcıya göre uyarlayan bir yapay zeka entegre edilmesi amacıyla platform oyununu karakterize edebilecek öznitelikler çıkarılmış ve ölçülmüştür. Genel olarak, çıkarılan öznitelikler girdi ve çıktı öznitelikleri olarak gruplandırılarak girdi özniteliklerinin çıktı öznitelikleri ile ilişkisi ortaya konmaya çalışılmıştır. Belirlenen en temel çıktı özniteliği, kullanıcı performansıdır. Kullanıcı performansının ölçümünde bölüm tamamlanma zamanı, kahramanın ölüm nedeni ve bölümlerde uğradığı zarar öznitelikleri baz alınmıştır. Sistem, bu sayede bölüm içerisindeki düşman seçimini ve bir sonraki bölüm önerisini kullanıcının performansına göre belirlemektedir.Conference Object Overt information operations during peacetime(Curran Associates, 2012) Tekir, SelmaInformation superiority is the most critical asset in war making. It directly addresses the perception of the opponent and in the long term the will of him to act. Sun Tzu's classical text states this fact by the concept of deception as the basis of all warfare. The success in warfare then is dependent on being aware of what's happening, accurately realizing the context. This is the intelligence function in broad terms and mostly open source intelligence as it provides the context. Competitive intelligence is based mainly on open sources and day by day the open source share in the intelligence product is increasing. Present diversified open sources & services represent a methodology shift in war. The two preceding ways have been overt physical acts against military targets in wartime and covert information operations conducted throughout peacetime against even nonmilitary targets respectively. The present methodology must be overt (open) information operations during peacetime. This coincides with a metaphor change as well. It proposes a transformation from a war metaphor into a game metaphor in which there are some playing rules. In fact, the existence of such rules helps in drawing the boundary of the field of competitive intelligence and thus making it a profession. Game metaphor is safer to adopt than war as it's easier to take responsibility in public disclosure scenarios in this case. By following this metaphor, you continue to stay in the boundary of legitimate competition. In other terms, you make a conscious preference in terms of war intensities by choosing to avoid the more intense war forms limited conflict, and actual warfare respectively. Finally, this preference is in accordance with the fundamental point of the Sun Tzu's entire argument: The vision of victory without fighting. To summarize, open source domination in the competitive intelligence lays the ground for the game metaphor that represents a transformation in warfare. The apparent outcome is overt information operations during peacetime. It emerges as the most important tool to fight against deception, thus success in information warfare in the contemporary world.Conference Object Citation - WoS: 3Citation - Scopus: 4Recent Cyberwar Spectrum and Its Analysis(Curran Associates, 2012) Aslanoğlu, Rabia; Tekir, SelmaWar is an organized, armed, and often prolonged conflict that is carried on between states, nations or other parties. Every war instance includes some basic components like rising conditions, battlespace, weapons, strategy, tactics, and consequences. Recent developments in the information and communication technologies have brought about changes on the nature of war. As a consequence of this change, cyberwar became the new form of war. In this new form, the new battlespace is cyber space and the contemporary weapons are constantly being renovated viruses, worms, trojans, denial-of-service, botnets, and advanced persistent threat. In this work, we present recent cyberwar spectrum along with its analysis. The spectrum is composed of the Estonia Attack, Georgia Attack, Operation Aurora, and Stuxnet Worm cases. The methodology for analysis is to identify reasons, timeline, effects, responses, and evaluation of each individual case. Moreover, we try to enumerate the fundamental war components for each incident. The analysis results put evidences to the evolution of the weapons into some new forms such as advanced persistent threat. Another outcome of the analysis is that when approaching to the end, confidentiality and integrity attributes of information are being compromised in addition to the availability. Another important observation is that in the last two cases, the responsive actions were not possible due to the lack of the identities of the offending parties. Thus, attribution appears as a significant concern for the modern warfare. The current sophistication level of the cyber weapons poses critical threats to society. Particularly developed countries that have high dependence on information and communication technologies are potential targets since the safety of the critical infrastructures like; healthcare, oil and gas production, water supply, transportation and telecommunication count on the safety of the computer networks. Being aware of this fact, every nation should attach high priorities to cyber security in his agenda and thus behave proactively.