Çankaya, Hakkı Candan

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Profile URL
https://hdl.handle.net/20.500.14365/7298
Name Variants
Cankaya, Hakki Candan
Cankaya, H. C.
Cankaya, Hakki C.
Job Title
Email Address
hakki.cankaya@ieu.edu.tr
Main Affiliation
05.05. Computer Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
7003929724
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
CHS-3038-2022

Sustainable Development Goals

5

GENDER EQUALITY
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9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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13

CLIMATE ACTION
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8

DECENT WORK AND ECONOMIC GROWTH
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14

LIFE BELOW WATER
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17

PARTNERSHIPS FOR THE GOALS
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NO POVERTY
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2

ZERO HUNGER
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4

QUALITY EDUCATION
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11

SUSTAINABLE CITIES AND COMMUNITIES
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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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GOOD HEALTH AND WELL-BEING
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CLEAN WATER AND SANITATION
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RESPONSIBLE CONSUMPTION AND PRODUCTION
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REDUCED INEQUALITIES
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15

LIFE ON LAND
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AFFORDABLE AND CLEAN ENERGY
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Documents

63

Citations

1654

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Documents

66

Citations

1035

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Scholarly Output

5

Articles

1

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Supervised MSc Theses

1

Supervised PhD Theses

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WoS Citation Count

4

Scopus Citation Count

13

WoS h-index

1

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1

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WoS Citations per Publication

0.80

Scopus Citations per Publication

2.60

Open Access Source

1

Supervised Theses

1

JournalCount
2012 Ieee 36Th Annual Computer Software And Applıcatıons Conference (Compsac)1
Eknow 2011: the Thırd Internatıonal Conference on Informatıon, Process, And Knowledge Management1
Natural Language Engıneerıng1
Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 20101
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Scholarly Output Search Results

Now showing 1 - 5 of 5
  • Thumbnail Image
    Article
    Semantic Composition of At-Location Relation With Other Relations
    (Cambridge Univ Press, 2012) Cankaya, Hakki C.; Blanco, Eduardo; Moldovan, Dan
    This paper presents a method for the composition of at-location with other semantic relations. The method is based on inference axioms that combine two semantic relations yielding another relation that otherwise is not expressed. An experimental study conducted on PropBank, WordNet, and eXtended WordNet shows that inferences have high accuracy. The method is applicable to combining other semantic relations and it is beneficial to many semantically intense applications.
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    Conference Object
    Citation - WoS: 1
    Commonsense Knowledge Acquisition Using Compositional Relational Semantics
    (Iaria Xps Press, 2011) Cankaya, Hakki C.; Blanco, Eduardo; Moldovan, Dan
    A method for the acquisition of commonsense knowledge based on instantiations of metarules is presented. The metarules refer to some properties and objects that have those properties. Metarules are instantiated by automatically identifying objects that have those properties. In order to increase the applicability of a commonsense property to objects, composition of semantic relations is used. The method has been implemented and tested over WordNet. Results show that a commonsense metarule can produce many knowledge base axioms.
  • Thumbnail Image
    Master Thesis
    Customer Churn Prediction for Telecommunications Industry
    (İzmir Ekonomi Üniversitesi, 2014) Yabaş, Utku; İnce, Türker; Çankaya, Hakkı Candan
    Müşteri kaybetmek, telekom firmaları açısından kaybettirdiği para bakımından önemli bir endişedir. Bu tez çalışmasında, en son veri madenciliği yöntemlerini analiz ederek, servislerden ayrılacak veya başka bir firmanın servisini kullanmayı düşünen müşterileri tahmin etmek için yeni metotlar geliştirdik. Önerdiğimiz yaklaşımın performansını yoğun bir şekilde değerlendirdik. Bu değerlendirmeyi yapmak için Orange Telecom tarafından "Knowledge Discovery and Data Mining 2009"(KDD) yarışması için sunduğu gerçek ve kullanıma açık bir veri kümesi kullandık. Bu veri kümesinde toplam 100.000 örnek ve 230 değişken bulunmaktadır. Bu yüzden veri kümesi "büyük veri" kapsamına girmektedir. IBM bu yarışmada birinci olmuştur, ancak önemli ölçüde bilişimsel kaynak kullanmaktadır. Biz alternatif metotlar ve daha uygun kaynaklar kullanarak, yarışmadaki en yüksek skorlara ulaşmayı hedefledik. Bu çalışmada, toplu sınıflandırıcı teknikleri üzerine yoğunlaştık. Tek ve güçlü sınıflandırıcılar ile en son toplu sınıflandırıcıları "müşteri ayrılma" problemi için karşılaştırdık. Ayrıca, bu metotların performanslarını arttırmak için iyi performans gösteren sınıflandırıcıları seçerek; bunları oylayıcı sınıflandırıcı ile birleştirdik. Genel olarak, elde ettiğimiz sonuçlar, yarışmanın en yüksek sonuç alan resmi yarışmacıları ile yakındı. Önerdiğimiz yaklaşımın, "müşteri ayrılması tahmini" dışındaki başka zorlayıcı otomatik öğrenme problem alanları için de değerli olabileceğine inanıyoruz. Yöntemimizin doğruluğunu onaylamak için, UCI Machine Learning kütüphanesinden topladığımız veri kümeleri ile deneyler yaptık. Bu deneyler sonucunda çoğu veri kümesinde yöntemimiz, içinde bulunan toplu sınıflandırıcıdaki bütün algoritmalardan daha iyi sonuçlar elde etmiştir.
  • Thumbnail Image
    Conference Object
    Citation - WoS: 3
    Citation - Scopus: 13
    Customer Churn Prediction for Telecom Services
    (IEEE, 2012) Yabaş, Utku; Cankaya, Hakki Candan; İnce, Türker
    Customer churn is a big concern for telecom service providers due to its associated costs. This short paper briefly explains our ongoing work on customer churn prediction for telecom services. We are working on data mining methods to accurately predict customers who will change and turn to another provider for the same or similar service. Sample dataset we use for our experiments has been compiled by Orange Telecom from real data. They posted the sample dataset for 2009 Knowledge Discovery and Data Mining Competition. IBM has scored the highest on this dataset requiring significant amount of computational resources. We are aiming to find alternative methods that can match or improve the recorded highest score with more efficient use of resources. Dataset has very large number of features, examples and incomplete values. As the first step, we employ some methods to preprocess the dataset for its imperfections. Then, we compare and contrast various ensemble and single classifiers. We conclude the paper with future directions for the study.
  • Thumbnail Image
    Conference Object
    Enhancing Location Information Using Semantic Composition
    (2010) Cankaya H.C.; Blanco E.; Moldovan D.
    This paper presents a method to enhance location awareness by using semantic composition of AT-LOCATION and PART-WHOLE semantic relations. The method generates axioms that infer new location relations based on relations that are extracted by a semantic parser. Experimental study with WordNet glosses shows that the method increases the amount of location knowledge by two orders of magnitude. The precision of the results is 98%. © 2010 IEEE.