High Level approach: Module that creates sentence embeddings for every book. This could enable semantic search, clustering, recommendations, anomaly detection, diversity measurement, classification using distance function and could be first step to a “talk to books” or “talk to library” feature.
Disadvantage: Distance functions operate in the high-dimensional space of embeddings and can be computationally expensive, especially for large-scale book datasets.
High Level approach: Module that creates sentence embeddings for every book. This could enable semantic search, clustering, recommendations, anomaly detection, diversity measurement, classification using distance function and could be first step to a “talk to books” or “talk to library” feature.
Disadvantage: Distance functions operate in the high-dimensional space of embeddings and can be computationally expensive, especially for large-scale book datasets.