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
Spatio-temporal pattern and trend extraction on Turkish meteorological data
Date
2012-12-01
Author
Goler, Isil
Karagöz, Pınar
Yazıcı, Adnan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
132
views
0
downloads
Cite This
Due to increasing amount of spatio-temporal data collected from various applications, spatio-temporal data mining has become a demanding and challenging research field requiring development of novel algorithms and techniques for successful analysis of large spatio-temporal databases. In this study, we propose a spatio-temporal mining technique and apply it on meteorological data, which has been collected from various weather stations in Turkey. In addition, we introduce one more mining level on the extracted patterns in order to discover general trends with respect to spatial changes. Generated patterns are investigated under different temporal ranges, in order to monitor the change of the events with respect to temporal changes. © 2012 Springer-Verlag London Limited.
Subject Keywords
Spatio-temporal data
,
Spatio-temporal data mining
,
Trend extraction
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84887837069&origin=inward
https://hdl.handle.net/11511/96895
DOI
https://doi.org/10.1007/978-1-4471-2155-8-64
Conference Name
26th Annual International Symposium on Computer and Information Science, ISCIS 2011
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
BIG DATA FOR INDUSTRY 4.0: A CONCEPTUAL FRAMEWORK
Gökalp, Mert Onuralp; Kayabay, Kerem; Eren, Pekin Erhan; Koçyiğit, Altan (2016-12-17)
Exponential growth in data volume originating from Internet of Things sources and information services drives the industry to develop new models and distributed tools to handle big data. In order to achieve strategic advantages, effective use of these tools and integrating results to their business processes are critical for enterprises. While there is an abundance of tools available in the market, they are underutilized by organizations due to their complexities. Deployment and usage of big data analysis t...
Semantic concept recognition from structured and unstructured inputs within cyber security domain
Hoşsucu, Alp Gökhan; Baykal, Nazife; Department of Information Systems (2015)
Linked data initiative has been quite successful in terms of publishing and interlinking data over ontological structures. The success is due to answering semantically rich queries over highly structured data. The utilization of linked data structures are widely used in various domains to solve the problem of producing domain specific knowledge which can be interpreted by automated agents without any human interference. Cyber security field is one of the domains that suffer from the excessiveness of the raw...
Efficient adaptive regression spline algorithms based on mapping approach with a case study on finance
Koc, Elcin Kartal; İyigün, Cem; Batmaz, İnci; Weber, Gerhard-Wilhelm (2014-09-01)
Multivariate adaptive regression splines (MARS) has become a popular data mining (DM) tool due to its flexible model building strategy for high dimensional data. Compared to well-known others, it performs better in many areas such as finance, informatics, technology and science. Many studies have been conducted on improving its performance. For this purpose, an alternative backward stepwise algorithm is proposed through Conic-MARS (CMARS) method which uses a penalized residual sum of squares for MARS as a T...
End User Evaluation of the FAIR4Health Data Curation Tool
Gencturk, Mert; Teoman, Alper; Alvarez-Romero, Celia; Martinez-Garcia, Alicia; Parra-Calderon, Carlos Luis; Poblador-Plou, Beatriz; Löbe, Matthias; Sinaci, A Anil (2021-05-27)
The aim of this study is to build an evaluation framework for the user-centric testing of the Data Curation Tool. The tool was developed in the scope of the FAIR4Health project to make health data FAIR by transforming them from legacy formats into a Common Data Model based on HL7 FHIR. The end user evaluation framework was built by following a methodology inspired from the Delphi method. We applied a series of questionnaires to a group of experts not only in different roles and skills, but also from various...
FGPA based cryptography computation platform and the basis conversion in composite finite fields
Sial, Muhammad Riaz; Akyıldız, Ersan; Department of Cryptography (2013)
In the study of this thesis work we focused on the hardware based cryptographic algorithms computation platform, especially for elliptic-curve and hyper-elliptic curve based protocols. We worked for making the hyperelliptic curve based Tate Pairing computation efficient specially for hardware implementations. To achieve this one needs to make the underlying finite field arithmetic implementations efficient. For this we study the finite fields of type $\mathbb{F}_q, q=p^{2pn}$ from the efficient implementati...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
I. Goler, P. Karagöz, and A. Yazıcı, “Spatio-temporal pattern and trend extraction on Turkish meteorological data,” presented at the 26th Annual International Symposium on Computer and Information Science, ISCIS 2011, London, İngiltere, 2012, Accessed: 00, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84887837069&origin=inward.