Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 1Citation - Scopus: 1Author Reputation Measurement on Question and Answer Sites by the Classification of Author-Generated Content(World Scientific Publishing, 2021) Sezerer, Erhan; Tenekeci, Samet; Acar, Ali; Baloğlu, Bora; Tekir, SelmaIn the field of software engineering, practitioners' share in the constructed knowledge cannot be underestimated and is mostly in the form of grey literature (GL). GL is a valuable resource though it is subjective and lacks an objective quality assurance methodology. In this paper, a quality assessment scheme is proposed for question and answer (Q&A) sites. In particular, we target stack overflow (SO) and stack exchange (SE) sites. We model the problem of author reputation measurement as a classification task on the author-provided answers. The authors' mean, median, and total answer scores are used as inputs for class labeling. State-of-the-art language models (BERT and DistilBERT) with a softmax layer on top are utilized as classifiers and compared to SVM and random baselines. Our best model achieves 63.8% accuracy in binary classification in SO design patterns tag and 71.6% accuracy in SE software engineering category. Superior performance in SE software engineering can be explained by its larger dataset size. In addition to quantitative evaluation, we provide qualitative evidence, which supports that the system's predicted reputation labels match the quality of provided answers.Article Estimating Spatiotemporal Focus of Documents Using Entropy With Pmi(Türkiye Klinikleri Journal of Medical Sciences, 2020) Yaşar, Damla; Tekir, SelmaMany text documents are spatiotemporal in nature, i.e. contents of a document can be mapped to a specific time period or location. For example, a news article about the French Revolution can be mapped to year 1789 as time and France as place. Identifying this time period and location associated with the document can be useful for various downstream applications such as document reasoning or spatiotemporal information retrieval. In this paper, temporal entropy with pointwise mutual information (PMI) is proposed to estimate the temporal focus of a document. PMI is used to measure the association of words with time expressions. Moreover, a word’s temporal entropy is considered as a weight to its association with a time point and a single time point with the highest overall score is chosen as the focus time of a document. The proposed method is generic in the sense that it can also be applied for spatial focus estimation of documents. In the case of spatial entropy with PMI, PMI is used to calculate the association between words and place entities. The effectiveness of our proposed methods for spatiotemporal focus estimation is evaluated on diverse datasets of text documents. The experimental evaluation confirms the superiority of our proposed temporal and spatial focus estimation methods.Article Citation - WoS: 9Citation - Scopus: 14Rule-Based Automatic Question Generation Using Semantic Role Labeling(Institute of Electronics, Information and Communication Engineers, 2019) Keklik, Onur; Tuğlular, Tuğkan; Tekir, SelmaThis paper proposes a new rule-based approach to automatic question generation. The proposed approach focuses on analysis of both syntactic and semantic structure of a sentence. Although the primary objective of the designed system is question generation from sentences, automatic evaluation results shows that, it also achieves great performance on reading comprehension datasets, which focus on question generation from paragraphs. Especially, with respect to METEOR metric, the designed system significantly outperforms all other systems in automatic evaluation. As for human evaluation, the designed system exhibits similar performance by generating the most natural (human-like) questions.Conference Object Citation - Scopus: 1Türkçe Tweetler Üzerinden Yapay Sinir Ağları ile Cinsiyet Tahminlemesi(Institute of Electrical and Electronics Engineers Inc., 2019) Sezerer, Erhan; Polatbilek, Ozan; Tekir, SelmaYazar ayrımlaması, yazarı bilinmeyen bir metin üzerinden yazarına dair cinsiyet, yaş ve dil gibi bazı anahtar özniteliklerin belirlenmesidir. Özellikle güvenlik ve pazarlama alanında önem arz etmektedir. Bu çalışmada, kullanıcıların tweetleri kullanılarak cinsiyetleri tahminlenmektedir. Yinelemeli Sinir Ağı (YSA) ve ilgi mekanizmasının birleşiminden oluşan bir model önerilmiştir. Bildiğimiz kadarıyla bu çalışma Twitter veri kümesi ile Türkçe’de ilk defa yapılmıştır. Önerilen model Türkçe, İngilizce, İspanyolca ve Arapça dillerinde sınanmış ve sırasıyla 80.63, 81.73, 78.22, 78.5 doğruluk değerlerine ulaşılmıştır. Elde edilen doğruluk değerleri Türkçe’de en gelişkin, diğer dillerde ise rekabetçi bir başarım ortaya koymaktadır.Conference Object Citation - Scopus: 6Gender Prediction From Tweets With Convolutional Neural Networks: Notebook for Pan at Clef 2018(CEUR Workshop Proceedings, 2018) Sezerer, Erhan; Polatbilek, Ozan; Sevgili, Özge; Tekir, SelmaThis paper presents a system1 developed for the author profiling task of PAN at CLEF 2018. The system utilizes style-based features to predict the gender information from the given tweets of each user. These features are automatically extracted by Convolutional Neural Networks (CNN). The system mainly depends on the idea that the informativeness of each tweet is not the same in terms of the gender of a user. Thus, the attention mechanism is included to the CNN outputs in order to discriminate the tweets carrying more information. Our architecture was able to obtain competitive results on three languages provided by the PAN 2018 author profiling challenge with an average accuracy of 75.1% on local runs and 70.23% on the submission run.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.