Title: Human enhanced machine driven categorization (tentative)

Mentor: Francesco Lelli

Co-Supervisor Emiel Caron  

Machines are better than human in executing repetitive and computational oriented tasks. However, humans are more flexible and can conceptualize and categorize information in a superior way. The candidate will investigate the proper way to combine both the world in the domain of categorization algorithm.

You will focus these studies in the domain of scientometrics, in particular the identification of duplicate scientific references in the patent databases (see this article for more information).

Strings representing references will be adjusted following a similarity algorithm that you will contribute to develop. This particular algorithm that will be partially “human driven”.   

Human enhanced machine driven categorization
Human enhanced machine driven categorization

This project does not involve an internship. Instead, it will try to have a high academic relevance and theoretical contribution and, based on the quality of your work the candidate may be able to publish the results in the proceedings and scientific journals.

If you are curious and you what to know more about the topic, I recommend you the following:

Note: Basic proficiency in a computer languages like JAVA and/or SQL plus the capability of consuming a Web APIs may be beneficial.

If you are interested in the topic, do not hesitate to contact us for more information. Our contact details are: Emiel Caron & Francesco Lelli.

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