A ticket-resolution recommender built from clustering, LDA, Siamese and index-embedding models with a high-availability deployment, but the reported 98% accuracy is measured against clusters generated from the same data.
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A Scalable and High Availability Solution for Recommending Resolutions to Problem Tickets
A ticket-resolution recommender built from clustering, LDA, Siamese and index-embedding models with a high-availability deployment, but the reported 98% accuracy is measured against clusters generated from the same data.