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Automatically Extracting Venue Accessibility Information Noisy Data

Poster by Mylène Brown-Coleman

One of the biggest challenges that people with disabilities encounter in the city is that whenever they go to a location (a restaurant, a library, or any other public building), the process of determining in advance whether they can reach the place, if they could enter it and whether they would feel comfortable inside is too long and not reliable. Previous research by the City of Amsterdam has shown that it is possible to automatically extract venue accessibility information from online reviews.

This poster presents Mylène Brown-Coleman's research plans to adapt the existing pipeline to work with noisy data.

This research was conducted by Mylène Brown-Coleman in collaboration with AI Team, Urban Innovation and R&D, City of Amsterdam.

Involved civil servants: Iva Gornishka

Supervisors: Xander Wilcke & Iva Gornishka

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