Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Citation - WoS: 4Citation - Scopus: 8LGPsolver - Solving Logic Grid Puzzles Automatically(Assoc Computational Linguistics-acl, 2020) Jabrayilzade, Elgun; Tekir, SelmaLogic grid puzzle (LGP) is a type of word problem where the task is to solve a problem in logic. Constraints for the problem are given in the form of textual clues. Once these clues are transformed into formal logic, a deductive reasoning process provides the solution. Solving logic grid puzzles in a fully automatic manner has been a challenge since a precise understanding of clues is necessary to develop the corresponding formal logic representation. To meet this challenge, we propose a solution that uses a DistilBERT-based classifier to classify a clue into one of the predefined predicate types for logic grid puzzles. Another novelty of the proposed solution is the recognition of comparison structures in clues. By collecting comparative adjectives from existing dictionaries and utilizing a semantic framework to catch comparative quantifiers, the semantics of clues concerning comparison structures are better understood, ensuring conversion to correct logic representation. Our approach solves logic grid puzzles in a fully automated manner with 100% accuracy on the given puzzle datasets and outperforms state-of-the-art solutions by a large margin.Conference Object A News Chain Evaluation Methodology Along With a Lattice-Based Approach for News Chain Construction(Association for Computational Linguistics (ACL), 2017) Toprak, Mustafa; Özkahraman,Ö.; Tekir, SelmaChain construction is an important requirement for understanding news and establishing the context. A news chain can be defined as a coherent set of articles that explains an event or a story. There's a lack of well-established methods in this area. In this work, we propose a methodology to evaluate the "goodness" of a given news chain and implement a concept latticebased news chain construction method by Hossain et al. The methodology part is vital as it directly affects the growth of research in this area. Our proposed methodology consists of collected news chains from different studies and two "goodness" metrics, minedge and dispersion coefficient respectively. We assess the utility of the lattice-based news chain construction method by our proposed methodology. © EMNLP 2017.All right reserved.Conference Object Improvements on a Multi-Task Bert Model(Ieee, 2024) Agrali, Mahmut; Tekir, SelmaPre-trained language models have introduced significant performance boosts in natural language processing. Fine-tuning of these models using downstream tasks' supervised data further improves the acquired results. In the fine-tuning process, combining the learning of tasks is an effective approach. This paper proposes a multi-task learning framework based on BERT. To accomplish the tasks of sentiment analysis, paraphrase detection, and semantic text similarity, we include linear layers, a Siamese network with cosine similarity, and convolutional layers to the appropriate places in the architecture. We conducted an ablation study using Stanford Sentiment Treebank (SST), Quora, and SemEval STS datasets for each task to test the framework and its components' effectiveness. The results demonstrate that the proposed multi-task framework improves the performance of BERT. The best results obtained for sentiment analysis, paraphrase detection, and semantic text similarity are accuracies of 0.534 and 0.697 and a Pearson correlation coefficient of 0.345.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.Conference Object Citation - Scopus: 6Geodesic Distances for Web Document Clustering(Institute of Electrical and Electronics Engineers Inc., 2011) Tekir, Selma; Mansmann, Florian; Keim, DanielWhile traditional distance measures are often capable of properly describing similarity between objects, in some application areas there is still potential to fine-tune these measures with additional information provided in the data sets. In this work we combine such traditional distance measures for document analysis with link information between documents to improve clustering results. In particular, we test the effectiveness of geodesic distances as similarity measures under the space assumption of spherical geometry in a 0-sphere. Our proposed distance measure is thus a combination of the cosine distance of the term-document matrix and some curvature values in the geodesic distance formula. To estimate these curvature values, we calculate clustering coefficient values for every document from the link graph of the data set and increase their distinctiveness by means of a heuristic as these clustering coefficient values are rough estimates of the curvatures. To evaluate our work, we perform clustering tests with the k-means algorithm on the English Wikipedia hyperlinked data set with both traditional cosine distance and our proposed geodesic distance. The effectiveness of our approach is measured by computing micro-precision values of the clusters based on the provided categorical information of each article. © 2011 IEEE.