For many organisations, Elasticsearch is no longer suited to AI-centric tasks. Tools like MongoDB with embedding-aware search, PostgreSQL with normalised data models, and Pinot with fast analytical ...

Research indicates deliberate interaction with diverse content sources gradually reshapes recommendation patterns, potentially counteracting natural narrowing tendencies. Platform-level transparency ...

Aiming at the problem that existing knowledge graph-based recommendation algorithms do not fully utilize the interaction information between users and items, this paper proposes a recommendation ...

Google has added a new, experimental 'embedding' model for text, Gemini Embedding, to its Gemini developer API.

This repository builds upon the implementation of "Text Is All You Need: Learning Language Representations for Sequential Recommendation" by adding user data embeddings to enhance the recommendation ...

This paper proposes a relevant movie recommender system emphasizing the role of transformers in converting natural language text inputs, which describe movie features, into processable embeddings.

The online systems that make recommendations to us often rely on their digital footprint — our clicks, views, purchases, and other digital footprints — to infer our preferences. But this means ...