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istanbul, turkey
It's currently 9:10 AM here
Joined December 7, 2012
0 Recommendations
Nildem
@nildem
4.3
4.3
86%
86%
istanbul, turkey
100%
Jobs Completed
100%
On Budget
100%
On Time
13%
Repeat Hire Rate
Java Developer, Translater
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€40.00 EUR
Java
Website Design
Translation
Turkish Translator
+1 more
•
€213.00 EUR
Translation
Data Entry
Blog
Research Writing
Creative Design
•
€51.00 EUR
Translation
Data Entry
Marketing
Research Writing
Article Rewriting
•
$170.00 USD
•
$248.00 USD
•
Experience
Product Development Specialist
Nov 2009 - Present
- Web based Java application development for payment gateways and secure payment solutions
- Working experience with techologies/frameworks: Spring, JSP, Java Servlets, iBatis, Junit/TestNG, HTML, Javascript
- Experience with tools/applications: Eclipse IDE, Apache Tomcat, Atlassian Jira, Confluence
- Experience with ISO-8583 protocol for bank communication
Software Intern
Aug 2008 - Aug 2009 (1 year)
- Implementing a Java Oracle OLAP Cube interface for creating and querying OLAP cubes
- Developing server-side data access modules using Java ( with Hibernate)
- Integrating Oracle Spatial into existing modules, data dump and migration on Oracle database
- User interface design and client-side scripts with Adobe Flex Framework
Education
MSc
(2 years)
Bachelor
(4 years)
Publications
Graph-based sequence clustering through multiobjective evolutionary algorithms for web recommender systems
ACM
In web recommender systems, clustering is done offline to extract usage patterns and a successful recommendation highly depends on the quality of this clustering solution. In these types of applications, data to be clustered is in the form of user sessions which are sequences of web pages visited by the user. Sequence clustering is one of the important tools to work with this type of data. One way to represent sequence data is through weighted, undirected graphs where each sequence is a vertex and the pairw
Multiobjective evolutionary clustering of Web user sessions: a case study in Web page recommendation
ACM
The aim of this study is to automatically generate facial composites in order to match a target face, by using the active appearance model (AAM). The AAM generates a statistical model of the human face from a training set. The model parameters control both the shape and the texture of the face. We propose a system in which a human user interactively tries to optimize the AAM parameters such that the parameters generate the target face. In this study, the optimization problem is handled through using nature-
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