With respect to the mass categorization that is central to most computer operations, there are two types of relevant data which affect speed of assimilation as well as information recall: structured data and unstructured data. Structured data refers to information with a high degree of organization, such that inclusion in a relational database. However, unstructured data may have its own internal structure,
but does not conform neatly into a spreadsheet or database. CVs (Curriculum vitae) are this kind of data. Typically, CVs presented in PDF format can be structured using the PDF tagging feature, however most PDF data is untagged and unstructured. It is very difficult for non-technical business users and data analysts to deal with such closed boxes. Within the scope of this study, a web based smart resume designer was developed which will allow people gain time while creating their own resumes according to their own information in different accepted formats. The content structure of the PDF documents, the
text data and the font and location information of this data were extracted and the information obtained was converted into certain structures in the order of reading and a predefined XML based resume template was created. Personal PDF documents are created using this template. PDF analysis and PDF creation was done directly by accessing the content stream of the PDF document with the help of the iText-pdf library, which is the Java library. Presentation templates is served to end-user on a desktop applicaiton with a GUI and users can select any metadata to create own document with select-and-apply approach.
It is predicted that the template obtained from the PDF document will be saved in XML format and the templates in the ready-made XML format will be used for adaptation to different contents. The XML schema (XSD-xml schema definition) is defined for the automatic creation of templates in XML format and subsequent testing of their accuracy. With the application developed, automatic forms of resumes were recognized and different contents were adapted.
Büyük Veri, Paralel İşleme ve Akademisyenlik [Link]
Veri Analitiği & Büyük Veri [Link]