Browsing by Author "Ganiz, Murat Can"
Now showing items 1-20 of 24
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Analysis of preprocessing methods on classification of Turkish texts
Torunoğlu, Dilara; Çakırman, Erhan; Ganiz, Murat Can; Akyokuş, Selim; Gürbüz, Mustafa Z. (IEEE, 2011-06)Preprocessing is an important task and critical step in information retrieval and text mining. The objective of this study is to analyze the effect of preprocessing methods in text classification on Turkish texts. We ... -
An anomaly detection framework for BGP
De Urbina Cazenave, Inigo O.; Köşlük, Erkan; Ganiz, Murat Can (IEEE, 2011-06)Abnormal events such as large scale power outages, misconfigurations, and worm attacks can affect the global routing infrastructure and consequently create regional or global Internet service interruptions. As a result, ... -
An application of community discovery in academical social networks
Arslan, Enis; Akyokuş, Selim; Ganiz, Murat Can (IEEE, 2013)The objective of this study is to discover social communities in a social network using different social network community discovery methods that utilize metrics and structures like degree, clustering coefficient, k-cores, ... -
Application of the SpecHybrid algorithm to text document clustering problem
Uykan, Zekeriya; Ganiz, Murat Can (IEEE, 2011-06)In this paper, we present a relaxed version of the SpecHybrid Algorithm originally proposed for wireless cellular systems, and apply it to text document clustering problem. We conduct several experiments on two different ... -
The benchmark of paragraph and sentence extraction summaries using outlier document filtering based multi -document summarizer
Turan, Metin; Sönmez, Coşkun; Ganiz, Murat Can (Kaunas University of Technology, 2014)We studied outlier document filtering (ODF) for extractive sentence summarization. Our results are superior compared to the average of the participant systems' using DUC 2006. Furthermore, we add extractive paragraph ... -
A corpus-based semantic kernel for text classification by using meaning values of terms
Altınel, Berna; Ganiz, Murat Can; Diri, Banu (Elsevier, 2015-08)Text categorization plays a crucial role in both academic and commercial platforms due to the growing demand for automatic organization of documents. Kernel-based classification algorithms such as Support Vector Machines ... -
Discrete - time hopfield neural network based text clustering algorithm
Uykan, Zekeriya; Ganiz, Murat Can; Şahinli, Çağla (Springer Verlag, 2012-11-11)In this study we propose a discrete-time Hopfield Neural Network based clustering algorithm for text clustering for cases L = 2(q) where L is the number of clusters and q is a positive integer. The optimum general solution ... -
Evaluation of classification models for language processing
Kilimci, Zeynep Hilal; Ganiz, Murat Can (IEEE, 2015-08)Naïve Bayes is a commonly used algorithm in text categorization because of its easy implementation and low complexity. Naïve Bayes has mainly two event models used for text categorization which are multivariate Bernoulli ... -
Exploiting Turkish Wikipedia as a semantic resource for text classification
Poyraz, Mitat; Ganiz, Murat Can; Akyokuş, Selim; Görener, Burak; Kilimci, Zeynep Hilal (IEEE, 2012)Majority of the existing text classification algorithms are based on the "bag of words" (BOW) approach, in which the documents are represented as weighted occurrence frequencies of individual terms. However, semantic ... -
Helmholtz principle based supervised and unsupervised feature selection methods for text mining
Tutkan, Melike; Ganiz, Murat Can; Akyokuş, Selim (Elsevier, 2016-09)One of the important problems in text classification is the high dimensionality of the feature space. Feature selection methods are used to reduce the dimensionality of the feature space by selecting the most valuable ... -
Higher order naive bayes: a novel NON-IID approach to text classification
Ganiz, Murat Can; George, Cibin; Pottenger, William M. (IEEE, 2011-07)The underlying assumption in traditional machine learning algorithms is that instances are Independent and Identically Distributed (IID). These critical independence assumptions made in traditional machine learning algorithms ... -
Higher-order semantic smoothing for text classification
Poyraz, Mitat (Doğuş Üniversitesi Fen Bilimleri Enstitüsü, 2013-01)Text classification is the task of automatically sorting a set of documents into classes (or categories) from a predefined set. This task is of great practical importance given the massive volume of online text available ... -
Higher-order smoothing: a novel semantic smoothing method for text classification
Poyraz, Mitat; Kilimci, Zeynep Hilal; Ganiz, Murat Can (Science Press, 2014-05)It is known that latent semantic indexing (LSI) takes advantage of implicit higher-order (or latent) structure in the association of terms and documents. Higher-order relations in LSI capture "latent semantics". These ... -
Intelligent focused crawler: Learning which links to crawl
Taylan, Duygu; Poyraz, Mitat; Akyokuş, Selim; Ganiz, Murat Can (IEEE, 2011-06)A web crawler is defined as an automated program that methodically scans through Internet pages and downloads any page that can be reached via links. With the exponential growth of the Web, fetching information about a ... -
Metinsel veri madenciliği için anlamsal yarı-eğitimli algoritmaların geliştirilmesi
Ganiz, Murat Can; Altınel, Berna; Yaman, Utku; Çakırman, Erhan; Tutkan, Melike; Poyraz, Mitat; Kilimci, Zeynep Hilal; Tüysüzoğlu, Göksu; Engün, İsmail Murat (TÜBİTAK, 2015)Metinsel veri madenciliği büyük miktarlardaki metinsel verilerden faydalı bilgilerin çıkarılması veya bunların otomatik olarak organize edilmesini içerir. Büyük miktarlarda metinsel belgenin otomatik olarak organize ... -
NMF based dimension reduction methods for Turkish text clustering
Güran, Aysun; Ganiz, Murat Can; Naiboğlu, Hamit Selahattin; Kaptıkaçtı, Halil Oğuz (IEEE, 2013)In this work, we analyze the effects of NMF based dimension reduction methods on clustering of Turkish documents by using k-means clustering algorithm. All experiments are conducted on two different datasets that we call ... -
A novel classifier based on meaning for text classification
Ganiz, Murat Can; Tutkan, Melike; Akyokuş, Selim (IEEE, 2015-09)Text classification is one of the key methods used in text mining. Generally, traditional classification algorithms from machine learning field are used in text classification. These algorithms are primarily designed for ... -
A novel higher-order semantic kernel for text classification
Altınel, Berna; Ganiz, Murat Can; Diri, Banu (IEEE, 2013-11)In conventional text categorization algorithms, documents are symbolized as “bag of words” (BOW) with the fact that documents are supposed to be independent from each other. While this approach simplifies the models, it ... -
A novel semantic smoothing kernel for text classification with class-based weighting
Altınel, Berna; Diri, Banu; Ganiz, Murat Can (Elsevier, 2014-12-24)In this study, we propose a novel methodology to build a semantic smoothing kernel to use with Support Vector Machines (SVM) for text classification. The suggested approach is based on two key concepts; class-based term ... -
A novel semantic smoothing method based on higher order paths for text classification
Poyraz, Mitat; Kilimci, Zeynep Hilal; Ganiz, Murat Can (IEEE, 2012-12-10)It has been shown that Latent Semantic Indexing (LSI) takes advantage of implicit higher-order (or latent) structure in the association of terms and documents. Higher-order relations in LSI capture "latent semantics". ...
