Project - CUHE -- An explainable recommender system for holistic exploration and curation of media heritage collections
Enable cultural heritage professionals (e.g. museum curators, archivists) as well as researchers to explore existing media and cultural heritage digital collections in a more holistic way.
- Financed by
- Horizon 2020
- Duration
- Keywords
- Culture Recommendations
Overview
Media Heritage collections have become larger and diverse thanks to the recent advancements in AI and automatic metadata extraction techniques. Cultural heritage professionals can create exhibitions and share new insights based on the rich data that they have available. This can advance in multiple ways cultural tourism such as: showcasing rare artefacts under new perspectives, producing stories and exhibitions which present culture in an immersive and engaging way, supporting and enhancing the production of interpretive materials (apps, flyers, audio guides etc. ) and establishing a strong digital presence of destinations by combining different sources and digital channels.
CUHE is an explainable recommendation system that enables browsing and exploring cultural heritage collections which can maximise the potential of presenting them in an engaging and attractive way, surfacing non-obvious connections between records and in- between collections.
The project delivers personalised data-driven storytelling through intelligent story recommendation services. This can be achieved by deploying intelligent methods for connecting various sources such as real time social media posts, geo-location data and promotional stories from local actors, showcase unique offerings and produce memorable experiences.
Our role
- Methods to measure content similarity
- Natural Language Processing
- Topic detection and keyword extraction
- Pilots and Applications with the project's end users
