Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Büyük veri anlamlandirmada panoramik yaklaşim
Date
2014-01-01
Author
Doʇan, Ilter Tolga
Doʇan, Yasemin Şahin
Şener, Cevat
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
56
views
0
downloads
Cite This
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84911889048&origin=inward
https://hdl.handle.net/11511/92383
Conference Name
8th Turkish National Software Engineering Symposium, UYMS 2014
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Decoding city squares with big data: A method for urban analytics
Özen, Aslıhan; Gürsel Dino, İpek; Department of Architecture (2022-5-12)
The responsive city nowadays is considered as an assemblage of a large number of complex characteristics. Similar to cities, people's social behavior is a complex system. Seeing cities with Big Data allows architects and urban designers to understand social networks of cities. This study outlines a computational tool to uncover latent characteristics of cities by combining Machine Learning and Social Media Analytics so that it may be possible to render an “image” and visualize a dense web of a city. The the...
Büyük Veri Çağında İşletmelerde Veri Bilimi
Gökalp, Mert Onuralp; Kayabay, Kerem; Çoban, Selin; Eren, Pekin Erhan (null; 2018-11-10)
İçinde bulunduğumuz büyük veri çağında bilgi teknolojisi servislerinden ve nesnelerin interneti kaynaklarından üretilen veri miktarındaki üstel artış ile birlikte şirketlerin veriden elde edebileceği fayda da her geçen gün hızla artmaktadır. Ancak bu mevcut verileri etkin şekilde kullanmak, stratejik üstünlük elde etmek ve kendi iş süreçlerini iyileştirmek isteyen kuruluşların büyük veri ve veri biliminden elde edebilecekleri faydaları doğru tanımlamaları ve şirketlerini bu doğru...
Interacting multiple model probabilistic data association filter using random matrices for extended target tracking
Özpak, Ezgi; Orguner, Umut; Department of Electrical and Electronics Engineering (2018)
In this thesis, an Interacting Multiple Model – Probabilistic Data Association (IMM-PDA) filter for tracking extended targets using random matrices is proposed. Unlike the extended target trackers in the literature which use multiple alternative partitionings/clusterings of the set of measurements, the algorithm proposed here considers a single partitioning/clustering of the measurement data which makes it suitable for applications with low computational resources. When the IMM-PDA filter uses clustered mea...
Structural modification with additional degrees of freedom in large systems
Canbaloğlu, Güvenç; Özgüven, Hasan Nevzat; Department of Mechanical Engineering (2009)
In the design and development stages of mechanical structures, it is important to predict the dynamic characteristics of modified structures. Since time and cost are critical in design and development stage, structural modification methods predicting the dynamic responses of modified structures from those of the original structure and modification properties are very important, especially for large systems. In this thesis structural modification methods are investigated and an effective structural modificat...
Dynamic modularity based community detection for large scale networks
Aktunç, Rıza; Toroslu, İsmail Hakkı; Department of Computer Engineering (2015)
In this work, a new fast dynamic community detection framework for large scale networks is presented. Most of the previous community detection algorithms are designed for static networks. Static modularity optimizer framework (SMO), which is introduced by Waltman & Van Eck, consists of such community detection algorithms. However, large scale social networks are dynamic and evolve frequently over time. To quickly detect communities in dynamic large scale networks, we proposed dynamic modularity optimizer fr...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
I. T. Doʇan, Y. Ş. Doʇan, and C. Şener, “Büyük veri anlamlandirmada panoramik yaklaşim,” Guzelyurt, Türkiye, 2014, vol. 1221, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84911889048&origin=inward.