Opinion Mining & Big Data is a programme conducted by Teamnet in partnership with the Faculty of of Automatic Control and Computers, University Politechnica of Bucharest.
For the students who wanted to be able to detect with precision all the opinions expressed in writing or during the discussions, we launched an academic research programme which can improve and develop the tools currently used on a large scale.
We wished to also approach other topics related to the analysis of large data and text volumes generated nowadays, by applying techniques such as automatic learning, information retrieval, analysis of social networks and predictive modeling.
Opinion Mining & Big Data is a programme that addresses Bachelor and Master students from the Faculty of Automatic Control and Computers, Faculty of Mathematics and Informatics and not only. The results obtained following the research are included as content in their papers.
Currently, we have three main directions in application development:
- Automatic Media Monitoring: detection of the mentioned entities, opinions and quotations for texts in Romanian;
- Public data analysis for Specific Projects:
- Building the graph of businessmen in Romania;
- Bid analysis in Romania;
- Building conversational agents that model a historical, scientific or literary personality.
Being an intern in the Opinion Mining & Big Data project means you’ll manage to develop your business skills in order to:
- Study algorhytms and techniques specific to the field of the internship;
- Work for the development of a software application which includes the algorithms suggested for solving the problem;
- Work in testing and validating the results of the application developed;
- Work for integrating and improving the existing data collection platform and discover opinions in online texts, written in Romanian (using open-source technologies such as Apache Solr, Apache Nutch, Weka, Mallet, etc.);
- Stimulate critical thinking, working for developing their own ideas by improving or combining various existing solving skills.
Among the research topics suggested, a broad range of technologies specific to the following fields:
- Natural Language Processing: lemmatisation, POS tagging, affective scoring, n-gram models etc;
- Information Retrieval: Apache Nutch & Lucene & Solr;
- Machine Learning: Weka, Mallet, clustering (STC, Lingo);
- NoSQL Databases: MongoDB, Neo4j.
Moreover, during the entire internship, you will benefit from a sponsorship from our side.
To enter the programme, you have to go through the following stages:
- Send an application;
- Attend an interview with our HR team;
- Pass a logical and technical test;
- Attend an interview with a specialist in the respective field of activity;
- Integrate in the team.
If you want to apply for a position in this programme, you should have:
- Solid Java knowledge (C and Python are a plus);
- Solid knowledge of data and algorithm structures;
- Desire to broaden your scientifical documentation in a new field and to study the existing open-source programmes in the filed;
It is considered a plus:
- Knowledge of basic text mining concepts, information retrieval or machine learning;
- Involvement in open-source projects or other software projects developed by a team ( for example, in the university);
- 7 students attended the summer internships;
- 6 interns also worked on their papers during their internship in the company;
- 4 students continued the collaboration as fulltime employees.
Session 2012 -2013
- 8 students attended the summer internship classes;
- 7 interns also drafted their paper while working in the company;
- 4 students were hired fulltime after graduation;