Engineering Commons^™

Application Of Random Indexing To Multi Label Classification Problems: A Case Study With Mesh Term Assignment And Diagnosis Code Extraction, Yuan Lu

Theses and Dissertations--Computer Science

Many manual biomedical annotation tasks can be categorized as instances of the typical multi-label classification problem where several categories or labels from a fixed set need to assigned to an input instance. MeSH term assignment to biomedical articles and diagnosis code extraction from medical records are two such tasks. To address this problem automatically, in this thesis, we present a way to utilize latent associations between labels based on output label sets. We used random indexing as a method to determine latent associations and use the associations as a novel feature in a learning-to-rank algorithm that reranks candidate labels selected …