Mining Software Entities in Scientific Literature
Patrice Lopez, Caifan Du, Johanna Cohoon, Karthik Ram, James Howison
Abstract
We present a comprehensive information extraction system dedicated to software entities in scientific literature. This task combines the complexity of automatic reading of scientific documents (PDF processing, document structuring, styled/rich text, scaling) with challenges specific to mining software entities: high heterogeneity and extreme sparsity of mentions, document-level cross-references, disambiguation of noisy software mentions and poor portability of Machine Learning approaches between highly specialized domains. While NER is a key component to recognize new and unseen software, considering this task as a simple NER application fails to address most of these issues.