Computer Engineering / Bilgisayar Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/10

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Now showing 1 - 10 of 28
  • Conference Object
    Citation - Scopus: 3
    Ontology Supported Policy Modeling in Opinion Mining Process
    (Springer Verlag, 2012) Husaini, Mus'ab; Ko, Andrea; Tapucu, Dilek; Saygın, Yücel
    In e-Society the spreading services offered by Social Web has changed the way of communication and cooperation among citizens, policy-makers, governance bodies and civil society actors. One of the main goals of policymakers is to motivate citizens for participation in policy-making processes. UbiPOL ((Ubiquitous Participation Platform for Policy-making, ICT-2009.7.3(ICT for Governance and Policy Modelling), 2009-2011) aimed to develop a ubiquitous solution, which emphasizes citizens' participation in policy-making processes (PMPs) regardless of their current location and time. Ontology-based opinion mining component of Ubipol system has a crucial role in citizens' commitment, because it empowers them to contribute in policy making. This paper presents the ontology-based semi-automatic approach and tool for sentiment analysis in Ubipol system, which include lexicon extraction from a large corpus of documents. Aspect-based opinion summarization of user reviews and its combination with domain ontology development are discussed as well.
  • Conference Object
    Citation - WoS: 11
    Citation - Scopus: 20
    Learning Styles Diagnosis Based on Learner Behaviors in Web Based Learning
    (Springer Verlag, 2009) Atman, Nilüfer; İnceoğlu, Mustafa Murat; Aslan, Burak Galip
    Individuals have different backgrounds, motivation and preferences in their own learning processes. Web-based systems that ignore these differences have difficulty in meeting learners' needs effectively. One of these individual differences is the learning style. For providing adaptively incorporated learning styles, firstly learning styles of learners have to be identified. There are many different learning models in literature. This study is based on Felder and Silverman's Learning Styles Model and investigates only active/reflective and visual/verbal dimensions of this model. Instead of filling out a questionnaire, learner behaviors are analyzed with the help of literature-based approaches so that learning styles of learners can be detected.
  • Conference Object
    Citation - Scopus: 2
    Adaptive Join Operator for Federated Queries Over Linked Data Endpoints
    (Springer Verlag, 2016) Oğuz, Damla; Yin, Shaoyi; Hameurlain, Abdelkader; Ergenç, Belgin; Dikenelli, Oğuz
    Traditional static query optimization is not adequate for query federation over linked data endpoints due to unpredictable data arrival rates and missing statistics. In this paper, we propose an adaptive join operator for federated query processing which can change the join method during the execution. Our approach always begins with symmetric hash join in order to produce the first result tuple as soon as possible and changes the join method as bind join when it estimates that bind join is more efficient than symmetric hash join for the rest of the process. We compare our approach with symmetric hash join and bind join. Performance evaluation shows that our approach provides optimal response time and has the adaptation ability to the different data arrival rates.
  • Conference Object
    Citation - Scopus: 4
    An Aspect-Lexicon Creation and Evaluation Tool for Sentiment Analysis Researchers
    (Springer Verlag, 2012) Husaini, Mus'ab; Koçyiğit, Ahmet; Tapucu, Dilek; Yanıkoğlu, Berrin; Saygın, Yücel
    In this demo paper, we present SARE, a modular and extendable semi-automatic system that 1) assists researchers in building gold-standard lexicons and evaluating their lexicon extraction algorithms; and 2) provides a general and extendable sentiment analysis environment to help researchers analyze the behavior and errors of a core sentiment analysis engine using a particular lexicon.
  • Conference Object
    Citation - WoS: 5
    Citation - Scopus: 8
    The Fuzzy Syllogistic System
    (Springer Verlag, 2010) Kumova, Bora İsmail; Çakır, Hüseyin
    A categorical syllogism is a rule of inference, consisting of two premisses and one conclusion. Every premiss and conclusion consists of dual relationships between the objects M, P, S. Logicians usually use only true syllogisms for deductive reasoning. After predicate logic had superseded syllogisms in the 19th century, interest on the syllogistic system vanished. We have analysed the syllogistic system, which consists of 256 syllogistic moods in total, algorithmically. We have discovered that the symmetric structure of syllogistic figure formation is inherited to the moods and their truth values, making the syllogistic system an inherently symmetric reasoning mechanism, consisting of 25 true, 100 unlikely, 6 uncertain, 100 likely and 25 false moods. In this contribution, we discuss the most significant statistical properties of the syllogistic system and define on top of that the fuzzy syllogistic system. The fuzzy syllogistic system allows for syllogistic approximate reasoning inductively learned M, P, S relationships.
  • Article
    Citation - WoS: 30
    Citation - Scopus: 34
    Gddom: an Online Tool for Calculation of Dominant Marker Gene Diversity
    (Springer Verlag, 2017) Abuzayed, Mazen; El-Dabba, Nourhan; Frary, Anne; Doğanlar, Sami
    Gene diversity (GD), also called polymorphism information content, is a commonly used measure of molecular marker polymorphism. Calculation of GD for dominant markers such as AFLP, RAPD, and multilocus SSRs is valuable for researchers. To meet this need, we developed a free online computer program, GDdom, which provides easy, quick, and accurate calculation of dominant marker GD with a commonly used formula. Results are presented in tabular form for quick interpretation. © 2016, Springer Science+Business Media New York.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    A Relativistic Opinion Mining Approach To Detect Factual or Opinionated News Sources
    (Springer Verlag, 2017) Sezerer, Erhan; Tekir, Selma
    The 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.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 5
    Sentiment Analysis Using Domain-Adaptation and Sentence-Based Analysis
    (Springer Verlag, 2015) Gezici, Gizem; Yanıkoğlu, Berrin; Tapucu, Dilek; Saygın, Yücel
    Sentiment analysis aims to automatically estimate the sentiment in a given text as positive, objective or negative, possibly together with the strength of the sentiment. Polarity lexicons that indicate how positive or negative each term is, are often used as the basis of many sentiment analysis approaches. Domain-specific polarity lexicons are expensive and time-consuming to build; hence, researchers often use a general purpose or domain-independent lexicon as the basis of their analysis. In this work, we address two sub-tasks in sentiment analysis. We apply a simple method to adapt a general purpose polarity lexicon to a specific domain [1]. Subsequently, we propose and evaluate new features to be used in a word polarity based approach to sentiment classification. In particular, we analyze sentences as the first step for estimating the overall review polarity. We consider different aspects of sentences, such as length, purity, irrealis content, subjectivity, and position within the opinionated text. This analysis is then used to find sentences that may convey better information about the overall review polarity.We use a subset of hotel reviews from the TripAdvisor database [2] to evaluate the effect of sentence-level features on sentiment classification. Then, we measure the performance of our sentiment analysis engine using the domain-adapted lexicon on a large subset of theTripAdvisor database.
  • Conference Object
    Citation - Scopus: 3
    Ontology-Based Fuzzy-Syllogistic Reasoning
    (Springer Verlag, 2015) Zarechnev, Mikhail; Kumova, Bora İsmail
    We discuss the Fuzzy-Syllogistic System (FSS) that consists of the well-known 256 categorical syllogisms, namely syllogistic moods, and Fuzzy- Syllogistic Reasoning (FSR), which is an implementation of the FSS as one complex approximate reasoning mechanism, in which the 256 moods are interpreted as fuzzy inferences. Here we introduce a sample application of FSR as ontology reasoner. The reasoner can associate up to 256 possible fuzzyinferences with truth ratios in [0,1] for every triple concept relationship of the ontology. We further discuss a transformation technique, by which the truth ratio of a fuzzy-inference can increase, by adapting the fuzzy-quantifiers of a fuzzy-inference to the syllogistic logic of the sample propositions.
  • Conference Object
    Citation - Scopus: 7
    Orderbased Labeling Scheme for Dynamic Xml Query Processing
    (Springer Verlag, 2012) Assefa, Beakal Gizachew; Ergenç, Belgin
    Need for robust and high performance XML database systems increased due to growing XML data produced by today's applications. Like indexes in relational databases, XML labeling is the key to XML querying. Assigning unique labels to nodes of a dynamic XML tree in which the labels encode all structural relationships between the nodes is a challenging problem. Early labeling schemes designed for static XML document generate short labels; however, their performance degrades in update intensive environments due to the need for relabeling. On the other hand, dynamic labeling schemes achieve dynamicity at the cost of large label size or complexity which results in poor query performance. This paper presents OrderBased labeling scheme which is dynamic, simple and compact yet able to identify structural relationships among nodes. A set of performance tests show promising labeling, querying, update performance and optimum label size. © 2012 IFIP International Federation for Information Processing.