End-to-end Aspect Based Sentiment Analysis - Naver Labs Europe
4 October 2019
Meylan, France
Job Type
Start date
November 2019 or otherwise August2020
5-6 months


Aspect-based sentiment analysis (ABSA) is the task of identifying fine-grained opinion polarity towards specific aspects associated with a given target.
The goal of this internship is exploring and implementing a new neural architecture for end-to-end ABSA, where term detection, aspect and polarity classification are jointly modeled. Special attention will be given to data-efficient methods in order to cope with situations where little amount of annotated data is available. Experiments will be conducted and evaluated on multiple datasets from various domains and languages and results will be evaluated not only on specific ABSA subtasks but also on the full chain of annotations.

The expected outcome is, a minima, a multilingual prototype working on different domains.

The successful candidate should be enrolled in a graduate program, at the Master or PhD level, with a focus on NLP and Deep Learning.
Publication of results in major conferences/journals will be strongly encouraged.

Required skills

Good programming skills and proficiency with TensorFlow or PyTorch


Task: SemEval2016 Task 5: http://alt.qcri.org/semeval2016/task5/
[1] Pontiki, Maria, Dimitris Galanis, Haris Papageorgiou, Ion Androutsopoulos, Suresh Manandhar, Mohammed AL-Smadi, Mahmoud Al-Ayyoub, et al. 2016. “SemEval-2016 Task 5 : Aspect Based Sentiment Analysis.” In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), 19–30. Association for Computational Linguistics.

[2] Bailin, Wang  and  Lu, Wei. "Learning Latent Opinions for Aspect-level Sentiment Classification". Proceedings of AAAI 2018, New Orleans.

[3] Chi Sun, Luyao Huang, Xipeng Qiu. "Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence". Proceedings of NAACL-HLT 2019, pages 380–385 Minneapolis, Minnesota, June 2 - June 7, 2019.

Application instructions

Please note that applicants must be registered students at a university or other academic institution and that this establishment will need to sign an 'Internship Convention' with NAVER LABS Europe before the student is accepted.

You can apply for this position online. Don't forget to upload your CV and cover letter before you submit. Incomplete applications will not be accepted.


NAVER LABS is a world class team of self-motivated and highly engaged researchers, engineers and interface designers collaborating together to create next generation ambient intelligence technology and services that are rich with the organic understanding they have of users, their contexts and situations.

Since 2013 LABS has led NAVER’s innovation in technology through products such as the AI-based translation app ‘Papago’, the omni-tasking web browser ‘Whale’, the virtual AI assistant ‘WAVE’, in-vehicle information entertainment system ‘AWAY’ and M1, the 3D indoor mapping robot.

The team in Europe is multidisciplinary and extremely multicultural specializing in artificial intelligence, machine learning, computer vision, natural language processing, UX and ethnography. We collaborate with many partners in the European scientific community on R&D projects.

NAVER LABS Europe is located in the south east of France in Grenoble. The notoriety of Grenoble comes from its exceptional natural environment and scientific ecosystem with 21,000 jobs in public and private research. It is home to 1 of the 4 French national institutes in AI called MIAI (Multidisciplinary Innovation in Ai) It has a large student community (over 62,000 students) and is a lively and cosmopolitan place, offering a host of leisure opportunities. Grenoble is close to both the Swiss and Italian borders and is the ideal place for skiing, hiking, climbing, hang gliding and all types of mountain sports.

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