Recommendation
Suggesting items a user is likely to want, from behaviour and content.
Resumen
Recommendation systems rank items for a user using past behaviour, item similarity or both. It solves the problem that a catalogue large enough to be useful is too large to browse. It exists because the ranking signal directly changes engagement, and modern systems increasingly combine collaborative signals from interactions with embedding similarity over item content, which is what makes them useful when interaction data is sparse.
Grafo de tecnologías
Cómo se conecta Recommendation con el resto del stack.
Usa y depende de
- Neural Network concept Algorithms Recommendation uses Neural Network High ✓ source
- Embedding concept Techniques Recommendation based on Embedding High ✓ source