Propostas Submetidas - sem aluno

DEI - FCTUC
Gerado a 2024-03-28 13:11:22 (Europe/Lisbon).
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Titulo Estágio

SIENA - Social medIa Emotion aNAlysis

Áreas de especialidade

Sistemas Inteligentes

Engenharia de Software

Local do Estágio

LARN - Laboratorio de Redes Neuronais

Enquadramento

Social media boom has driven the interest in data mining, opinion mining and sentiment analysis as it represents a huge opportunity for marketers to understand consumers, value their feelings and focus on the best solutions to provide them. The inputs from the consumers, including comments, reviews and ratings has become the ultimate voice of the consumer and, ultimately, defines their purchase intent and potentiates the opinion of the masses.

Several research teams and startups are focusing on understanding the dynamics of the consumer’s feedback by analyzing their valuable inputs. One of the key challenges is to take out the most of their information taking advantage of the full text, including abbreviations, cultural differences and expressions, instead of qualifying a few key words.

Objetivo

The main goal of this research project is to develop a framework that identifies the sentiments involved in social media posts, customer’s feedbacks or blog comments. This work intends to use semantic analysis, natural language processing and deep learning techniques in order to analyze and classify consumer’s feedback.

Plano de Trabalhos - Semestre 1

- State of the Art Review (September 2016)
- Dataset Gathering & Model Definition for Anomalies Characterisation (October 2016)
- Evaluation of Classification and Machine-Learning Methodologies (November-December 2016)
- Intermediate MSc Report (January 2017)

Plano de Trabalhos - Semestre 2

- System & Algorithm Implementations (February - May 2017)
- Testing & Results Evaluation (March - May 2017)
- Scientific Article writing
- MSc Dissertation writing (June 2017)

Condições

Depending on the work conducted by the student, there is the opportunity for a one year paid internship in the company after Master’s conclusion. Additionally, the student has the possibility to incorporate in the company for a few weeks during the second semester.

Profile

Student should have:
- Attitude is first on the list!!
- Tons of energy

Student should be:
- Confident
- Ambitious
- Self-motivated
- Highly Adaptable
- Self-starter
- Quick Learner

Student should have interest (or academic experience) in at least one of the following:
- Pattern Recognition
- Artificial Intelligence
- Computer Vision

Observações

EyeSee is a technological startup, funded by Olisipo, focusing on intelligent systems. As of today, EyeSee developed a novel digital advertising solution with unique insertion and interaction features, owning 5 patents in USPTO. Additionally, EyeSee team is working on a smart energy management product and on a smart health monitoring system. Olisipo is an IT outsourcing company with more than 20 years of experience in the Portuguese market and with more than 500 employees in some of the main Portuguese companies. Recently, Olisipo decided to make a very strong bet on innovation and entrepreneurship, creating “Olisipo ADN - Ambiente de Desenvolvimento de Negócios”. Olisipo ADN counts with 6 startups, namely EyeSee, and currently funds ten innovation projects. This bet on innovative products and solutions focus on 4 areas: Better Life, Digital Advertising, Smart Energy and Machine-to-Machine. This is a brilliant opportunity to gain exposure to a dynamic, fun and outstanding technology company.

Orientador

Prof Bernardete Ribeiro (bribeiro@dei.uc.pt) e André Ribeiro Pimentel (andre.pimentel@eyesee.pt)
bribeiro@dei.uc.pt 📩