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Communication Dans Un Congrès Année : 2019

Towards Identifying for Evidence of Drain Brain from Web Search Results using Reinforcement Learning

Résumé

Brain drain is the phenomenon in which experts on a field abandon their origin country to practise their profession in a different country. It forms part of the migration patterns around the world. However brain drain can have damaging effects on the source of origin when it happens at large scale. This has been problem in several countries of latinamerica, particularly at the postgraduate level. The correct characterisation of this phenomena is vital to outline polices that keep or attract the talent needed in these countries. In this research, we propose a methodology to identify evidence of drain brain through results of web search engines which commonly contains links to career information pages given a seed name, however it could be very time consuming explore and analyse all resulting pages. For this reason, in this research we propose to exploit a Reinforcement Learning setting to learn to navigate and extract significant information from the snippet results. In this work we outline the main architecture based on the Dopamine RL framework.
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Dates et versions

hal-02505993 , version 1 (12-03-2020)

Identifiants

  • HAL Id : hal-02505993 , version 1

Citer

Héctor Murrieta, Ivan Meza, Pegah Alizadeh, Jorge Garcia Flores. Towards Identifying for Evidence of Drain Brain from Web Search Results using Reinforcement Learning. LatinX in AI Research Workshop at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada., Dec 2019, Vancouver, Canada. ⟨hal-02505993⟩
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