Discovering Culture through Smart Semantic recommendations

Have you ever found yourself exploring a digital museum or online archive, amazed by the vastness of cultural content available, yet unsure of what to look at next? You’re not alone. With more than 800 diverse cultural artifacts available on the MuseIT platform, choosing your next discovery can become overwhelming.

But what if the platform itself could intelligently guide you, turning each visit into a personalized journey?

Introducing Smart Semantic Recommendations

At Catalink, we’re proud partners in the MuseIT project, dedicated to making cultural heritage accessible and meaningful through advanced technologies. One of our key innovations is a powerful recommendation system integrated within MuseIT’s web interface, designed to help you effortlessly navigate the richness of cultural heritage artifacts.

The Challenge: Finding Meaning in abundant Data

MuseIT brings together artifacts from diverse cultural sources, each rich in its context and significance. Without intelligent guidance, exploring such an extensive collection can feel random, even overwhelming. Our goal was clear: to build a recommendation system that feels intuitive, engaging, and meaningful.

Our Solution: The Semantic Knowledge Graph

At the heart of our recommendation system is a semantic Knowledge Graph—powered by our flagship data integration platform, CASPAR+. Using the Cultural Heritage Ontology we previously designed, this Knowledge Graph connects artifacts through meaningful relationships.

Each artifact isn’t just an isolated piece of data; it’s interconnected through historical contexts, creators, periods, styles, and more. This graph transforms scattered cultural data into an insightful web of relationships, empowering discovery and exploration.

Recommendations Powered by KG Embeddings

To effectively recommend related artifacts, we harness the power of Knowledge Graph embeddings. Using the TransE model, we convert semantic relationships within the graph into vector representations—allowing us to measure semantic similarity easily. Artifacts created by the same artist, belonging to similar periods, or sharing thematic elements naturally cluster together.

Through cosine similarity, we identify and suggest artifacts closely related to your current selection, guiding you smoothly through your cultural exploration.

Supercharging Recommendations with Text Embeddings

We didn’t stop there. Recognizing that many artifacts come with rich descriptive texts, we utilize state-of-the-art transformer-based models to generate text embeddings. These embeddings capture the nuances and contexts described in artifact descriptions, enhancing our recommendations further.

By combining these text embeddings with the semantic power of the Knowledge Graph, we offer users uniquely precise, meaningful, and engaging recommendations.

Experience Cultural Heritage Like Never Before

With our smart semantic recommendations, browsing through MuseIT becomes more than just an activity—it transforms into a personalized experience of discovery. Whether you’re exploring ancient sculptures, historic paintings, or intriguing artifacts, each recommendation is a thoughtful guide pointing you toward new insights and connections.

Ready to Explore?

Curious about how semantic technology and smart recommendations can elevate your digital cultural experiences or your own projects?

We’d love to discuss how we can help bring semantic clarity and intelligence to your data-driven platforms.