Explore 4 real-world AI in manufacturing examples. From defect detection to predictive maintenance in beverage manufacturing, silicone wafer production and automotive production.
text summarization
While much work has been done in the area of extractive summarization, there has been limited study in abstractive summarization as this is much harder to achieve (going by the definition of true abstraction). This page contains a very small collection of summarization methods that are non-extractive…
These are some handy notes for MEAD. What is MEAD? MEAD is a publicly available framework for summarization. It is not really an ‘algorithm’. By default (I guess when it was first implemented) it was developed based on a centroid based approach…
This article talks about how to work with ROUGE for evaluation of summarization tasks. The original ROUGE toolkit uses a perl implementation which is really hard to understand, so I decided to piece together some information that may be helpful to others…
