Cem Gultunca Software Developer

T oday the Internet has become ubiquitous, has touched almost every corner of the globe, and is affecting human life in unimaginable ways. We are now entering an era of even more pervasive connectivity where a very wide variety of appliances will be connected to the web. We are entering an era of the “Internet of Things” (abbreviated as IOT). IOT is defined as a paradigm in which objects equipped with sensors, actuators, and processors communicate with each other to serve a meaningful purpose. Several IOT protocols have been introduced in order to provide an efficient communication for resource-constrained applications. However, their performance is not as yet well understood. I evaluated and compared four communication protocols, namely, AMQP, MQTT, XMPP, and COAP. I implemented a some IOT application using open source software for these protocols and measured their performance. In our tests, we compare AMQP and MQTT protocols. As a result, AMQP protocol transmits data faster than MQTT

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B esides internet is a network that we use in our daily lives, it has become a connection tool not only for shopping and banking operations but also for job seeking. Likewise, employers/companies use Human Resources Websites to publish job advertisements and reach job applicants expeditiously and easily. Human resources websites allow users to represent themselves with a resume which is a brief written formal structure that has basic parts for defining job seeker’s information such as qualifications, personal information, work experience, education information, projects, certificates, references and so on. However, it is a difficult process for a job applicant to find the best matched jobs with his/her work experiences, qualifications, education experiences, projects and so on. At the same time, it is also a difficult and time- consuming task for a company to find the best- qualified candidates among applicants. This project aims to present a system that extracts information from job advertisements and resumes with natural language processing (NLP) methods and, using the extracted information, perform matching to find the most suitable job advertisements for job seekers and to find the most suitable job applicants for employers.

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W hile the Internet takes up by far the most significant part of our daily lives, finding jobs/employees on the Internet has started to play a crucial role for job seekers and employers. Online recruitment websites and human resources consultancy and recruitment companies enable job seekers to create their résumé, a brief written formal document including job seeker's basic information such as personal information, educational information, work experience and qualifications in order to find and apply for desirable jobs, whereas they enable companies to find qualified employees they are looking for. However, résumés may be written in many ways that make it difficult for online recruitment companies to keep these data in their relational databases. In this study, a project that Kariyer.net (largest online recruitment website in Turkey) and TUBITAK (The Scientific and Technological Research Council of Turkey) have been jointly working is proposed. In this mentioned project, a system enables free structured format of résumés to transform into an ontological structure model. The produced system based on ontological structure model and called Ontology-based Résumé Parser (ORP) will be tested on a number of Turkish and English résumés. The proposed system will be kept in the Semantic Web approach that provides companies to find expert finding in an efficient way.

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