CUHE

Culture Recommendations

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.

CUHE aims to develop and demonstrate a web-based application of AI explainable recommendations allowing cultural heritage professions to more easily curate new galleries or create digital stories and exhibitions which can showcase and share the new insights gained.

While the recommendation system will enable the automatic linking of curated editorials to create “Story Spaces” and surface non-obvious connections between records and between collections, it will be important to provide users with the necessary information to understand why they are given such recommendations. In this way CUHE takes one step towards more explainable AI and answers the challenge of navigating multi-perspectivity in media heritage collections.

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StoM

Events Community Engagement AI Indexing & Discovery Recommendations

Semantic Technology at your service

StoM applies semantic intelligence to improve search, browsing, and discovery across digital archives.

StoM builds on top of the research results of a previous Research for SME project called SEMLIB that produced two software components: a semantic annotation system and a semantic recommendation engine. These solutions improve searching and web browsing of digital archives for different user groups.

IN2 develops EventPlace, the solution on top of semantic technology services that allows event and destination managers who want to organise their event content (e.g. presentations, video recordings, video promotions, documents) and combine it with user-generated content (for example photos and videos from participants, sharing impressions of the surroundings) for an engaging experience for everyone.

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