EWork
The service was delivered according to the following phases:
- Preparation – cleaning the dataset, extraction of relevant information from consultants’ CVs, customers’ feedback and project’ description data.
- Extraction of features for both consultants and projects in terms of numerical Representation. Standard Natural Language Processing and Text Analysis techniques were used for summarization
- Textual summary of each consultant’s CV along with his/her skills extracted
- Textual summary of each project along with required skills extracted
Here is detailed list of extractions:
- Demographic data – Place of birth, Place of living, Country and language
- Education history – Institution, Degree, Period of education, Build Faculties Database and Ranking
- Work experience – Company, Period, Years of experience, Build companies database and Ranking,
Linking hard skills and soft skills to work experience, Introducing new entities –
Position – for instance, someone is software developer, product manager, testing
engineer and similar. - Work Style – Soft skills extraction, Building similar solution as for the hard skills.
- Final submission – System tuning, Integration
The deliverables of each phase contained:
- API for retrieving phase-specific information
- GUI demo for viewing phase-specific information
- Evaluation of the extraction algorithms