Meal Finder: fine grained information extraction from web-scale image database

 

Does a restaurant have your favourite dish? What's the price of this
dish? Have they vegetarian options? Do they have a kid's menu?

When looking for a restaurant, all these common questions are not
necessarily answered by your favourite search application or social
web portal So, as a user, when you have found a nice restaurant, you
usually end up using additional sources of information to answer these
questions, because the data is not available directly or in an easy
way. A great place to look at is directly on the restaurant's website,
to see if they provide additional information (like an updated menu).

The goal of this internship is to investigate how to facilitate this
Information Retrieval task by automatically enriching a restaurant
database with unstructured information available on the Internet.

The student will have to help design and implement an information
extraction tool for restaurant menus. More precisely, the tool should
be able to structure a menu, from an image representation, into its
main structures and sections, extracting first information on dishes
(name, description, price(s)) or on the restaurant itself (address,
opening hours, phone number).

The student will work with a multi-disciplinary team with expertise in
Computer Vision, OCR, Document Structure Analysis and Information
Extraction . A production database gathering more than 100 million
places, the associated user reviews, images and menus will be
available to test and develop the system. At Naver Labs Europe we
encourage participation in the academic community and our researchers
publish regularly at top venues in NLP, machine learning and computer
vision.

Start Date asap
Duration 5-6 months

Application instructions

- Student at Master (research-oriented) or PhD level.
- Knowledge of neural networks models and Conditional Random Fields
- Good coding skills in Python

http://www.europe.naverlabs.com/NAVER-LABS-Europe/Internships/Meal-Finder-fine-grained-information-extraction-from-web-scale-image-database