Search patent of the week: Selecting answer spans from electronic documents using neural networks
Description
The Google patent discussed in this episode describes an innovative system that uses cascaded neural networks to efficiently extract accurate answers from electronic documents in response to user questions. The process involves tokenizing input, identifying candidate text spans, generating numeric representations, and scoring unique spans based on their relevance and context, including how question tokens relate to document segments. The system emphasizes lightweight neural network architectures for efficiency, enabling applications in voice assistants, search engines, and mobile devices. Ultimately, it aims to deliver precise, contextually aligned answer spans, even handling ambiguities by scoring and selecting the best match through a layered approach, with validation against ground truth data to continuously improve accuracy.
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