NLP and big data

Position research on how NLP models handle large-scale enterprise data to address real implementation challenges that conference attendees face in production environments

Frame a submission around practical applications of NLP in big data pipelines—such as processing unstructured text at scale or improving data quality workflows—rather than purely theoretical advances

Highlight cost-efficiency or performance benchmarks when applying NLP techniques to big data infrastructure, since practitioners attending will evaluate ROI and computational trade-offs