Sistema de recomendação
Construa um sistema de recomendação que seja ágil e fiável com Zilliz Cloud (totalmente gerido por Milvus) para recomendações de correspondência de utilizadores extremamente rápidas, uma experiência de utilizador óptima e um crescimento empresarial promissor.
Recommender Systems with Zilliz Cloud Vector Database
Explore the key role of Zilliz Cloud in seamlessly retrieving unstructured data and ensuring personalized recommendations across diverse online applications.
Turbocharge Recommendations with Unmatched Speed
Achieve a 10x performance boost on Zilliz Cloud with advanced indexing algorithms, ensuring millisecond-level latency for prompt user interactions. Elevate your experience now!
A Real-Time Personalized Recommender System
Ensure consistently up-to-date recommendation results with unparalleled precision using range search capability, seamless data flows, and streamlined data management within Zilliz Cloud.
Effortless Scaling for Limitless Business Expansion
Say goodbye to data size concerns with Zilliz Cloud. Our clusters seamlessly scale with your budget and evolving needs. Independently scale computing and storage for effortlessly handling tens of billions of vectors.
Start with Simplicity and Amplified Productivity
Launch a large-scale similarity search service in minutes with user-friendly SDKs in multiple languages and streamlined data operations, ensuring an intuitive experience for developers.
Ensure Unwavering System Resilience
Building recommender systems with Zilliz Cloud ensures uninterrupted services even in unexpected events through multiple replicas, component isolation, and robust backup and sync capabilities.
Como é que o Zilliz potencia os sistemas de recomendação
Um motor de recomendação de comércio eletrónico alimentado pelo Zilliz funciona da seguinte forma:
- Os comportamentos de compra dos utilizadores e os dados relacionados com os produtos são transformados em dados incorporados através de um modelo de incorporação.
- Estes dados são introduzidos no Zilliz Cloud (o Milvus totalmente gerido) para armazenamento e recuperação.
- O Zilliz recupera os Top-K resultados mais relevantes comparando a distância espacial entre o utilizador e os vectores do produto.
- Após os processos de filtragem, pontuação e ordenação, o sistema de recomendação fornece aos utilizadores os produtos recomendados em que estão interessados.
Histórias de Sucesso
Os líderes mundiais do sector utilizam o Milvus ou o Zilliz (Milvus totalmente gerido) para reforçar os seus sistemas de recomendação.
10x faster
in vector retrieval speed
> 95%
in news classification accuracy
Less memory consumption
for faster responses and reduced cost
< 10ms
P99 latency to enable real-time data retrieval
100+ Million
Daily vector updates without performance degradation
Increase revenue
Serving more relevant ads led to improved click-through rate
10x Faster Query Speed
than the previous Elasticsearch solution
<30ms Response Time
for searching on millions of vectors
Optimized User Experience
with more accurate recommendations based on users’ purchase behaviors
10x faster
in vector retrieval speed
> 95%
in news classification accuracy
Less memory consumption
for faster responses and reduced cost
< 10ms
P99 latency to enable real-time data retrieval
100+ Million
Daily vector updates without performance degradation
Increase revenue
Serving more relevant ads led to improved click-through rate